5534 results about "Control data" patented technology

The invention discloses a geographic information big data-oriented multi-source data processing system, and relates to the technical field of data acquisition and sensors, and the system comprises a data acquisition module which accesses a remote sensing satellite, an unmanned aerial vehicle, an Internet of Things sensor and social media in real time through a multi-source heterogeneous interface, and carries out the adaptive analysis of a data format and metadata marking; the distributed storage module is used for performing partition storage on the geographic information data based on a space-time database and an object storage architecture, and establishing dynamic space-time index and version control; the data fusion module is used for realizing coordinate system conversion, time sequence calibration and semantic knowledge graph matching based on a multi-source data alignment method of dynamic weight distribution; and an intelligent analysis module and a security control module. According to the method, core pain points such as data splitting, low storage efficiency, extensive analysis and compliance risks in the geographic information field are systematically solved, and a full-stack type technical base is provided for scenes such as smart cities, emergency disaster relief and environment monitoring.

The invention relates to the field of power equipment control data processing, in particular to a boiler combustion optimization control method based on data driving, which comprises the following steps of: acquiring multi-source data such as temperature field distribution, air and smoke pressure, smoke components and coal quality characteristics, and eliminating noise interference by adopting sliding window mean filtering; generating a standardized feature matrix in combination with principal component analysis and a dynamic time warping algorithm; constructing a dynamic coupling model fusing a gradient boosting decision tree and a long short-term memory network, analyzing a nonlinear relationship between pulverized coal particle size distribution and a wind-coal ratio, and predicting combustion efficiency, pollutant concentration and temperature field uniformity; and model parameter self-correction and weight dynamic adjustment are triggered through actual combustion data feedback, and a closed-loop control link is formed. According to the method, accurate modeling of the multi-physical field coupling characteristic of the combustion system is achieved, the time sequence generalization ability under the dynamic working condition is improved, and the purposes of heat efficiency improvement and pollutant emission reduction are effectively balanced.

Job clusters take time to instantiate. A computing system is provided comprising a plurality of non-interactive job clusters, a control database storing a task queue, and a controller. The controller instantiates one or more clusters of the plurality of non-interactive job clusters based on a size of the task queue and monitoring if the one or more clusters are successfully instantiated. Each of the one or more clusters, after successfully being instantiated by the controller, executes a dispatcher process that includes: querying the control database to identify an available task from the task queue; obtaining and processing the available task; and, after completion of the available task, further querying the control database prior to terminating.

The invention relates to a display screen backlight brightness adjusting method and system based on a Mini QLED technology. The method comprises the following steps: dividing a display image signal into a brightness signal, a chrominance signal and a saturation signal, and generating image feature data; performing sub-pixel-level boundary detection to obtain a plurality of initial backlight sub-regions, and calculating region brightness distribution data; executing region clustering operation and region merging to obtain a plurality of target backlight sub-regions and calculating backlight partition mapping data; carrying out nonlinear feature transformation, and calculating backlight unit control data of the Mini LED backlight unit; outputting the backlight compensation amount of each target backlight sub-region by adopting a deep Q network; and performing real-time feedback correction, calculating a deviation value between an actual display parameter and a target parameter of each target backlight sub-region, and outputting a backlight optimization control signal. According to the invention, the backlight brightness is accurately adjusted, and the consistency of the display effect is improved.

The invention provides a satellite measurement and control data anomaly detection and intelligent diagnosis early warning method and system, and relates to the technical field of satellite measurement and control, and the method comprises the steps: obtaining multi-source heterogeneous data in a satellite measurement and control system, and carrying out the preprocessing of the multi-source heterogeneous data; constructing a multi-level space-time fusion network model, inputting the preprocessed multi-source heterogeneous data into the multi-level space-time fusion network model, and extracting high-dimensional space-time features; based on the extracted high-dimensional spatial-temporal features, designing a dynamic adaptive anomaly detection algorithm, and performing anomaly detection on the satellite measurement and control data; according to an anomaly detection result, performing intelligent diagnosis by using a pre-constructed multi-level satellite system knowledge graph; based on the intelligent diagnosis result, multi-level early warning information is generated; a distributed edge computing architecture is designed, and partial data processing and anomaly detection tasks are deployed to a ground station and a satellite end; and presenting the generated multi-level early warning information through a visual interface, and automatically triggering a corresponding emergency plan according to the early warning level.

The invention provides an intelligent regulation and control method for a three-stage constructed wetland recirculating aquaculture system, and belongs to the technical field of machine learning. The method comprises the following steps: firstly, continuously collecting water quality data and operation control data of each control unit, and constructing a multi-source heterogeneous data set under a unified time scale; then, constructing a pollution evolution trend prediction model, and capturing a dynamic evolution trend of water quality along with time and control behavior changes; then, under the guidance of a prediction result, analyzing the similarity of historical states and the sensitivity of regulation and control response, automatically identifying key control parameters which influence the water quality change of the system at present, and reasoning the dynamic adjustable boundary of the key control parameters; and finally, constructing a reinforcement learning strategy network fusing state prediction, a parameter boundary and a control target, realizing multi-target tradeoff among pollutant removal efficiency, a water quality standard-reaching rate and operation energy consumption, and outputting an efficient and steady control strategy through continuous interactive training. According to the invention, efficient, accurate and robust operation of the wetland system can be realized.

The present application relates to the field of wire laying control technology, and discloses a composite material automatic wire laying forming optimization method, system, medium and wire laying machine. The method comprises: inputting dynamic tension control data into a fuzzy neural network calculation engine to obtain a dynamic compensation model for the retraction and release speed; based on the dynamic compensation model for the retraction and release speed, using a reinforcement learning engine to calculate the shearing sequence of multiple bundles and generate an intelligent shearing instruction set; constructing a re-delivery trajectory mapping relationship based on the intelligent shearing instruction set, and forming a re-delivery path matrix after iterative calculation by a digital twin engine; establishing a temperature field distribution prediction model based on the re-delivery path matrix, and constructing a temperature field dynamic control sequence after finite element analysis and calculation; substituting the temperature field dynamic control sequence into a multi-objective constraint equation, and outputting a laying strategy data packet after deep reinforcement learning iterative optimization. The present application realizes the precise coordination of multiple process parameters such as tension control, speed compensation, shear control, and temperature control.

The invention relates to a control method and device for wind load resistance of a mooring unmanned aerial vehicle and a storage medium. The method comprises the following steps: collecting and modeling a mooring unmanned aerial vehicle to obtain a system dynamics model; state estimation is carried out to obtain system wind load disturbance data and expected attitude data; performing optimal control solution on the plurality of mooring points to obtain tension distribution control data of each mooring point; inputting into a discrete time neural network controller for attitude compensation calculation to obtain thrust vector compensation control data; performing adaptive robust control on the attitude of the mooring unmanned aerial vehicle to obtain a rotating speed control instruction of each motor of the four rotors; and performing safety threshold judgment, and when any monitoring data exceeds a preset threshold, outputting a working mode switching instruction and executing safe landing control. According to the invention, a multi-stage safety protection mechanism is established, and reliable operation of the mooring unmanned aerial vehicle under extreme conditions is ensured through real-time monitoring and mode switching.

Systems and methods for providing efficient remediations for cloud environment vulnerabilities. The present systems and methods are configured to calculate the most efficient remediations to reduce cloud environments' risks, calculate a cloud environment's biggest risks and weaknesses, and provide a holistic overview of a cloud environment across different service providers. In an embodiment, steps include scanning a cloud environment for posture control data; identifying a plurality of security risk events based on the scanning; calculating a risk score for each of the plurality of security risk events; and determining and recommending one or more remediations based on the risk score of each of the plurality of security risk events and how efficient each remediation is.

The invention relates to the technical field of light emitting devices, and discloses a control method for a silicon light integrated multi-wavelength light emitting device, and the method comprises the steps: carrying out the grating coupling processing and polarization state separation processing of a plurality of wavelength channels of the silicon light integrated multi-wavelength light emitting device, and obtaining an initial optical characteristic data set; performing temperature response characteristic analysis to obtain a temperature field characteristic parameter set; performing spectral characteristic analysis on the plurality of wavelength channels to obtain wavelength channel characteristic vectors; a wavelength drift coefficient matrix and a refractive index change coefficient matrix are calculated, and a multi-wavelength linkage control data model is generated; according to the method, a hierarchical control structure comprising a quick response layer, a temperature compensation layer and a polarization optimization layer is constructed, multi-wavelength cooperative control operation is executed, and a steady-state control parameter set is output, so that the wavelength stability control precision and the temperature control precision are improved, the adaptive capacity to disturbance of different time scales is enhanced, and the stability of the system is improved. And stable operation under complex working conditions is ensured.

The invention relates to the technical field of multi-modal data, provides a pilot competency dynamic evaluation method, system and device based on multi-modal data and a storage medium, and solves the problems of low accuracy of pilot competency evaluation and poor pertinence of training guidance. The method comprises the steps of collecting flight control data, physiological signal data, psychological assessment data, subjective scale data and international civil aviation organization core competency information, performing alignment fusion on multi-source data by adopting a time synchronization algorithm, and identifying an attention fixation mode based on a hidden Markov model. And constructing a workload index by fusing a subjective scale and a physiological entropy value, inputting the multi-modal features into a pre-trained competency assessment model, outputting three levels of psychological assessment indexes including a basic ability layer, a dynamic presentation layer and a risk early warning layer, and finally generating a personalized training report. According to the invention, the accuracy of pilot competency evaluation and the pertinence of training guidance are improved.

Provided are a device and a method for controlling data traffic by a core network control plane node. The method may include receiving, from an application function control entity, one or more pieces of information among help information on application traffic characteristics, a PDU-Set QoS parameter, an identifier for grouping flows belonging to a multi-modal application, and a synchronization threshold; transmitting, to a base station, one or more pieces of information among help information on application traffic characteristics, a PDU Set QoS parameter, an identifier for grouping flows belonging to a multi-modal application, and a synchronization threshold during a PDU session establishment or modification procedure; and instructing transmission of a user packet including PDU-Set information to a core network user plane node.

The invention discloses a data security management method and system based on cloud computing, and relates to the technical field of data management, and the method comprises the following steps: S1, making a security policy; s2, performing security assessment on the cloud infrastructure; s3, performing identity authentication and access control; s4, data encryption and key management; s5, data classification and level-to-level management; s6, data leakage detection and defense; s7, performing auditing and compliance management; s8, abnormal behavior monitoring and threat response; and S9, an elastic backup and recovery mechanism. According to the data security governance method and system based on cloud computing, the elasticity and dynamic response capability of data security are remarkably improved by setting the distributed key management system and the intelligent monitoring model. The distributed key management system dispersedly stores the keys in different physical areas, so that the risk of single-point fault and attack is reduced; the AI-based intelligent behavior monitoring system analyzes user behaviors in real time, predicts abnormal operation and automatically responds.

The invention discloses a digital financial data sharing system and method, and belongs to the technical field of digital financial data analysis, and the system comprises a data standardization management module, a data access conversion interface module, a cross-mechanism authentication authority management module, a safety audit risk control module and an intelligent analysis cooperation platform module. The data standardization management module is used for unifying a data format to be XBRL, metadata definition and cleaning rules and eliminating data semantic differences between mechanisms, and the data access conversion interface module is used for supporting multi-source heterogeneous data access and providing a standardized output interface. The cross-institution authentication authority management module is used for realizing decentralized identity authentication based on a block chain technology, zero-knowledge proof and a federated learning technology, and controlling a data access range in a hierarchical manner in combination with role authority, and the security audit risk control module is used for monitoring data flow in real time. According to the invention, on the basis of realizing digital financial data sharing, the problem of data islands can be solved, and cross-mechanism data authentication can be facilitated.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a low-power-consumption unmanned aerial vehicle concealed control and encrypted communication method and system based on BLE 5.0. According to the method, link quality is dynamically evaluated based on a BLE node detection frame, a path decision result is generated, and a self-adaptive scattering network topological structure is constructed in combination with the real-time position of an unmanned aerial vehicle and electromagnetic environment changes; packaging the unmanned aerial vehicle control instruction into a GATT feature value update message, and generating a hidden control data stream; combining time, space and channel dimensions to generate a frequency hopping sequence parameter set; performing dynamic slicing and pseudo-random recombination on the hidden control data stream through a space-time dual encryption mechanism to generate an encrypted control instruction data stream; and transmitting the encrypted control instruction data flow to an unmanned aerial vehicle execution layer through a dynamic scattering network. On the premise of keeping the low power consumption characteristic, the unmanned aerial vehicle control system has high concealment, high reliability and high safety, and meanwhile, a tracking path of an enemy to a real flying hand is cut off through the dummy flying hand layer.

The invention provides an equipment health examination method and system based on multi-agent collaboration. The method comprises the following steps: a data acquisition step: acquiring target data to generate a multi-dimensional feature vector; the target data comprises frequency data, process data and control data; an equipment monitoring step: monitoring the equipment based on the generated multi-dimensional feature vector, and outputting a monitoring result; and a deployment processing step: deploying and implementing a corresponding processing scheme according to a monitoring result. The invention provides an equipment early warning and diagnosis method and system based on multi-agent cooperation, and the method comprises the steps: combining the advantages of a professional mechanism model, an AI model and a large language model through the multi-agent cooperation of feature extraction, threshold adjustment, fault diagnosis, decision generation, summary review and closed-loop feedback; the problems that a traditional method is single in model, high in false alarm rate, lagged in decision and the like are solved.

The invention provides a power grid frequency modulation power energy coordination control method and system based on a super capacitor, and relates to the technical field of power grid frequency modulation, and the method comprises the steps: carrying out the time-frequency analysis of a collected power grid frequency signal, obtaining a frequency disturbance characteristic value, and determining power control data through combining with an electrical parameter value of a super capacitor group; and performing nonlinear programming calculation based on the power control data to obtain a power distribution sequence, dividing the power distribution sequence into a quick response section, a dynamic transition section and a steady state maintenance section according to a preset threshold value, and solving a control value by adopting an augmented Lagrange equation, recursive least square operation and a Lyapunov function respectively. Obtaining a power control instruction; and inputting a power control instruction into the disturbance observer, calculating a dynamic error value, constructing a nonsingular terminal equation, and outputting a power regulation signal in combination with recursive minimum entropy calculation and a superhelix algorithm.

The invention relates to the technical field of system control data processing, in particular to a waste heat recovery heat supply system based on an injection type heat pump, which comprises a multi-source data acquisition module, a genetic algorithm optimization module, a dynamic mode switching module, a thermal stress suppression module and a self-learning updating module. The multi-source data collection module collects industrial waste heat temperature, power grid load and heat supply network backwater flow data through a temperature sensor array and a flow metering device, and feature vectors are extracted through sliding window standardization and principal component analysis. And heat transfer end difference fluctuation is restrained through closed-loop feedback. And the self-learning updating module constructs a multi-parameter incidence matrix to dynamically adjust the weight of a fitness function, and realizes parameter iterative optimization in combination with a historical optimal solution caching mechanism. The problems that the industrial waste heat recovery efficiency is low, thermoelectric coupling adjustment is delayed, and thermal stress of equipment is accumulated are solved.

The invention discloses a digital twinborn-based irrigation area water distribution scheduling method and system, and relates to the technical field of water distribution scheduling, and the method comprises the steps: collecting data, and constructing a digital twinborn model; dynamically simulating water resources in an irrigation area by using a hydrological model simulation technology based on a digital twinborn model; performing irrigation demand prediction by using a machine learning algorithm according to a simulation result; optimizing a water distribution scheduling model according to a prediction result; performing real-time scheduling control according to the scheduling strategy; performing scheduling effect evaluation according to the scheduling control data; adjusting a scheduling strategy according to an evaluation result; and performing irrigation area water resource management and long-term optimization by using an irrigation area water distribution scheduling system based on digital twinning according to an adjustment result. According to the method, the limitation of static weight distribution of a traditional method is overcome, the accuracy and flexibility of water distribution scheduling are improved, the actual requirements of a complex irrigation area environment are met, the maintenance cost and the operation risk are reduced, and efficient and stable operation of an irrigation area water distribution system is guaranteed.

The invention discloses a multi-parameter MPC two-phase liquid cooling energy efficiency optimization distribution control system and method, and relates to the technical field of liquid cooling energy efficiency optimization. The multi-parameter MPC two-phase liquid cooling energy efficiency optimization distribution control system and method comprises the following steps: S1, collecting and preprocessing two-phase liquid cooling control data; s2, the thermal load level of each area is evaluated periodically, a discrete time linear state space model is constructed, and the thermal load change rate is extracted; s3, the cold distribution amount of each area is quantified periodically, the pump speed and the valve opening target value are calculated, and an adjustment control instruction is generated; and S4, high heat risk and low heat stability areas are recognized, the cooling capacity compensation requirement is evaluated, a cooling capacity enhancement and recovery distribution value is output, and a corresponding control instruction is generated. The problems that an existing two-phase liquid cooling system generally only depends on temperature feedback for adjustment, so that cooling capacity distribution response lags behind, a short-time overheating phenomenon is prone to occurring in a high-heat area, and cooling capacity waste exists in a low-heat area at the same time are solved.

The invention relates to the technical field of robots, and discloses a robot nondestructive testing method and system based on artificial intelligence, and the method comprises the steps: obtaining multi-modal sensing data and motion state parameters; constructing a three-dimensional material feature model and analyzing to generate an initial defect feature evaluation model; loading material attributes and detection precision constraints to generate a comprehensive model, and combining motion parameter simulation to obtain path regulation and control data; training the dynamic defect prediction model to obtain a detection path correction model and generating initial detection parameters; obtaining dynamic correction simulation information based on the initial parameters and the like; constructing a multi-objective optimization model, and optimizing to obtain an optimal detection path parameter; and generating a safety detection probability by combining real-time model reasoning, and adjusting a detection strategy to realize dynamic path matching. The system comprises a data acquisition module, a feature modeling and analysis module, a comprehensive evaluation and simulation module and the like. The method improves the detection precision, efficiency and adaptability, and is suitable for nondestructive detection of complex targets.

The invention provides a flow limiting method and system based on a distributed cache strategy, belongs to the technical field of distributed flow limiting, and is applied to a distributed cache system which comprises a plurality of cache partitions. The method comprises the following steps: acquiring real-time traffic and historical traffic of each cache partition; inputting the real-time traffic and the historical traffic into a traffic prediction model to obtain predicted traffic at the next moment; and determining a flow limiting parameter of the cache partition based on the predicted flow, and limiting the flow at the next moment based on the flow limiting parameter. According to the method, the flow limiting parameters are automatically adjusted by using the machine learning technology, the data flow can be accurately controlled, the system overload is prevented, the resource waste caused by excessive limitation is avoided, and the flow management efficiency and effect of the distributed cache system are remarkably improved.

The invention discloses an adaptive modulation anti-multipath unmanned aerial vehicle swarm communication method and system based on MIMO-OFDM, and relates to the technical field of wireless communication, and the method comprises the steps: receiving a down-conversion baseband; synchronization and compensation are carried out; removing a cyclic prefix and carrying out fast Fourier transform; estimating a channel and noise on the training and pilot frequency, and correcting a common phase; performing frequency domain equalization and soft decision, forward error correction and cyclic redundancy check according to the estimation to obtain a control parameter, decoding a payload according to the control parameter, and performing statistics to form a link quality indication; modulating coding, bandwidth and spatial mode, configuring mapping, power and weight, and packaging physical layer protocol data; carrier sensing conflict avoiding sending, confirmation and retry are adopted to generate media access statistics; and the routing selects the next-hop multi-hop forwarding according to the transmission quality, and performs end-to-end statistics and recharge. Through cooperation of hierarchical synchronization and phase correction with cyclic prefix and FFT, crosstalk is suppressed, channel noise scale optimization soft decision is robust, data decoupling is controlled, and end-to-end availability is improved through multi-hop self-healing recharge.

Examples described herein relate to a switch or router. In some examples, the switch or router is to: based on receipt of a control packet associated with a first link, store the control packet into a first region of memory associated with the first link; based on receipt of a data packet associated with the first link, store the data packet into a second region of memory associated with the first link; based on the control packet and data packet to egress from a same output port, insert a strict subset of content of the control packet into the data packet to form a second data packet; and cause transmission of the second data packet to a device from the output port.

The invention discloses an industrial control data processing system and method based on an embedded real-time operating system, and relates to the technical field of industrial automation control, and the industrial control data processing system comprises a dynamic weight evaluation module, a resource elastic distribution module and a dual self-healing verification module; and the dynamic weight evaluation module is used for generating a dynamic weight value according to the task type, the data security level, the deadline margin and the historical execution abnormal rate. According to the industrial control data processing system and method based on the embedded real-time operating system, the task criticality is quantified in real time through the dynamic weight evaluation module, and the real-time response capability and the resource utilization efficiency of the industrial control system are improved in combination with elastic resource allocation driven by load prediction. A dynamic weight mechanism ensures that the emergency task can instantly preempt resources, and the problem of low-priority task blocking caused by traditional static priority scheduling is avoided.

The invention belongs to the field of pollution prevention and control data processing, and particularly relates to a laboratory instrument data automatic acquisition and quality tracing system and a laboratory instrument data automatic acquisition and quality tracing method. A distributed search traceability mapping space is constructed through the storage mapping module to realize space-time-semantic composite indexing and classification detection of data, and a causal reasoning model of the quality judgment module is used for performing anomaly judgment; a reverse Hash traceability mechanism is innovatively designed, an index-traceability node graph and a segmented Hash heterogeneous node anchoring strategy are combined, Hash head, body and tail fragments are stored in three types of nodes of acquisition, storage and detection, and tamper-proof traceability of abnormal data and dynamic optimization of acquisition parameters are realized through cross-node aggregation verification; according to the invention, the problems of low data credibility and poor abnormal traceability efficiency in ecological environment monitoring are solved, and full-chain closed-loop management of data acquisition-analysis-traceability-acquisition configuration adjustment is supported.

The invention belongs to the technical field of low-orbit satellite communication, and discloses a satellite system for jointly improving measurement and control data transmission and communication application efficiency. A control unit is responsible for completing satellite calendar attitude calculation of satellite broadcast, analyzing a satellite working mode switching instruction according to ground station information stored by a storage unit, and then sending the instruction to each module unit; the two baseband processing units both support on-orbit reconstruction and loading, wherein the baseband processing unit A is used for completing measurement and control signal processing or user wide beam access signal processing; the baseband processing unit B is used for completing communication service signal processing or data transmission signal processing; the two up-conversion units respectively carry out up-conversion processing on a service link signal and a measurement and control link signal in the signal processing module, and the two down-conversion units respectively receive signals of the phased array transceiver antenna and the wide beam transceiver antenna and complete down-conversion processing. The measurement and control link can support a satellite measurement and control function and a communication wide beam access function in a time-sharing manner.

The invention discloses a remote wireless heat supply valve control system based on Internet of Things, which relates to heat supply system application and comprises an intelligent communication management module, a real-time environment sensing module, a self-adaptive frequency distribution and spectrum management module, an equipment control and execution module and a system monitoring and maintenance module. According to the remote wireless heat supply valve control system based on the Internet of Things, the problem that control instruction transmission of a heat supply system is unstable due to wireless interference in a complex environment is effectively solved through the self-adaptive multi-band dynamic switching and intelligent interference recognition technology; the system not only improves the reliability and stability of heat supply control data transmission, but also optimizes heat energy distribution and resource utilization, reduces the operation cost of the system, and obviously enhances the competitiveness and adaptability of the system in the fields of central heating, commercial mansions and large residential areas.

The invention relates to the technical field of data monitoring and analysis, and discloses a hemodialysis care unit extracorporeal circulator monitoring method and system and a storage medium. The method comprises the steps that vital signs and identity features of a patient are collected, a sign feature data set is obtained through fusion processing, and initial dialysis parameters are generated; analyzing the sign feature data set to obtain blood vessel state parameters; adjusting a circulation system based on the blood vessel state parameters and the initial dialysis parameters to obtain circulation control data; monitoring a dialysate path by using the circulation control data, and generating a liquid path operation parameter; the circulation control data and the liquid path operation parameters are integrated to analyze the system state, and equipment early warning indexes are formed; and evaluating equipment operation according to the early warning index and generating an automatic control instruction. According to the method, deep integration of the physical sign characteristic data of the patient and the equipment operation data is realized, a data-driven objective decision basis is provided for the dialysis process, and the safety and effectiveness of dialysis treatment are improved.

The invention discloses a hybrid encryption method based on an industrial bus, and the method comprises the following steps: S1, generating an initial session key through a multiple elliptic curve algorithm, and generating an initial key pair through a pseudo-random number generator; s2, encrypting the control data by using a first-level key; s3, generating a secondary key to encrypt common transmission data; s4, dynamically generating a third-level temporary session key by using a pseudo-random number generator, and encrypting real-time transmission data of a large data volume; s5, realizing collaborative key generation and synchronous updating of a plurality of communication nodes through a distributed key management system; s6, periodically utilizing a probability density regression forest algorithm to dynamically update the key, and triggering key re-negotiation when communication abnormity is detected; and S7, integrating a classifier based on the combination of a deep forest and a gradient boosting decision tree, automatically classifying the data and dynamically adjusting an encryption strategy. According to the method, a multiple elliptic curve algorithm, dynamic key management and the like are combined, and efficient encryption in industrial bus communication is achieved.