68results about How to "Realize dynamic tracking" patented technology

The invention relates to the technical field of motor control, and discloses a control method and system of a permanent magnet direct current brushless slotless motor. The method comprises the following steps: performing temperature compensation and signal filtering on voltage data of a Hall sensor to obtain rotor position information and temperature characteristic data; performing magnetic field intensity dynamic compensation calculation according to the rotor position and the temperature data to obtain magnetic field intensity parameters; adjusting the amplitude and phase of the three-phase current according to the magnetic field intensity parameter, and generating a current control quantity; extracting and compensating a harmonic component to obtain a torque smooth control instruction; all losses are calculated and optimized, and efficiency optimization parameters are generated; and performing feature extraction and anomaly judgment on the operation parameters, and outputting a protection control strategy. Accurate detection of motor position signals, stable control of torque, optimal control of loss and real-time monitoring and protection of abnormal states are achieved under the high-temperature working condition, and therefore stable operation and the service life of the motor under the high-temperature environment are guaranteed.

The invention relates to the technical field of smart communities, and discloses a smart community target identification tracking method based on big data, which comprises the following steps: constructing an omnibearing monitoring network in a community, collecting real-time video and sensor data in the community, obtaining feature data of a target through an edge computing technology, and carrying out target identification tracking on the feature data; transmitting the target feature data to a cloud server through a network, identifying and classifying the target feature data, judging the type and identity of the target, analyzing the current behavior of the target according to a preset target historical behavior pattern library, and determining whether the behavior is abnormal or not; and if the behavior of the target is not matched with the normal mode in the historical behavior mode library, judging that the behavior is an abnormal behavior, and triggering an early warning mechanism. According to the invention, intelligent identification, dynamic tracking and timely early warning of the abnormal behavior of the smart community are realized, and the intelligent level and response efficiency of community safety management are improved.

The invention discloses a container tracking management system and method. The method comprises the following steps: S1, carrying out dynamic encryption binding and multi-dimensional data acquisition on an RFID chip; s2, realizing real-time position data acquisition of the container under different environmental conditions through a multi-source signal fusion and error correction algorithm; s3, various sensor modules are installed inside and outside the container, and data processing is carried out through distributed edge nodes; s4, performing on-chain storage on total data generated in the transportation process through a Hash encryption algorithm, and realizing automatic data verification, state tracking and abnormity alarm in combination with an intelligent contract; s5, carrying out real-time dynamic modeling analysis on the transportation path and resource allocation, and dynamically adjusting the transportation plan by using a distributed scheduling strategy; and S6, integrating the real-time state data, the path optimization model and the transportation scheduling decision, and providing a report for a user. The method has the advantages of high positioning precision, high data security, high transportation efficiency and good real-time performance.

The invention provides an electronic book data pushing method, device and equipment, belongs to the technical field of computer information processing, and solves the problem that a recommendation result is inaccurate when books are recommended to a user. The method comprises the following steps: acquiring log data and book feature data; processing the log data to obtain user preference data; processing the user preference data and the book feature data to obtain book pushing data; and sending the book pushing data to a client. According to the scheme, dynamic tracking and attenuation processing of user preferences are achieved, and the effect of recommending and displaying books to users in a personalized mode is achieved.

The invention discloses a data processing method and system of a chromatographic instrument, and relates to the technical field of data processing, and the method comprises the following steps: collecting whole-course original detection signals and external interference signs generated in a chromatographic analysis process, carrying out time alignment under a unified time scale, generating an interference rhythm index, and calculating the interference rhythm index; the reference is used as a unified reference for subsequent signal comparison; and based on the interference rhythm index, performing phase drift comparison on the acquired signal, calculating the phase difference between the detection signal and the interference signal, drawing a beat frequency wandering graph, extracting candidate signal segments of pseudo-period interference according to beat frequency change, and generating a pseudo-period candidate segment list. According to the invention, by establishing the interference rhythm index and comparing the interference rhythm index with the phase drift, the time decoupling of the detection signal and the interference signal is realized, and the sampling anti-interference capability is improved; and through dynamic control of a false peak characteristic fingerprint draft and a misjudgment reason table, signal rhythm correction and peak identification optimization are completed, so that the detection accuracy and the data stability are improved.

The invention provides a power business anti-quantum cryptography migration progressive control method based on risk awareness, and belongs to the technical field of migration control, and the method comprises the steps: collecting key parameters of all to-be-migrated businesses in a power system, carrying out the standardization preprocessing of the collected key parameters, and constructing a business feature matrix; acquiring relevant parameters of quantum attacks in real time, and calculating a real-time quantum attack risk value of each service to be migrated; based on the service feature matrix and the real-time quantum attack risk value, constructing a dynamic migration rhythm adaptation model, and calculating a migration priority, a migration rate and a migration interval of each service to be migrated; and constructing a migration fault-tolerant and recovery model, monitoring the migration process in real time, calculating a fault influence range and recovery cost based on fault information, and executing corresponding adjustment operation. Accurate, dynamic and high-reliability control of anti-quantum password migration of the power business is realized, safe and stable operation of the power business in the migration process is guaranteed, and the migration efficiency and the anti-quantum attack capability are improved.

The invention discloses a wind turbine generator component life probability prediction method and system, and a wind power plant energy control method and system. The prediction method comprises the steps of constructing a state space model of a degradation process of a wind turbine generator component; acquiring real-time state information of the component; inputting the real-time state information into the state space model, evaluating the degradation state of the component by adopting a sequential data assimilation algorithm, and outputting posterior probability distribution of the degradation state; and based on the posterior probability distribution, forward simulating a future degradation path of the component by adopting Monte Carlo simulation until the future degradation path exceeds a preset failure threshold, and obtaining residual life probability distribution of the component. According to the method, the personalized residual life of each unit can be accurately evaluated, and an innovative wind power plant energy management control strategy is created on the basis, so that the absolute maximization of the full-life-cycle economic benefit of the wind power plant in a complex market environment is realized.

The invention discloses a bonding silver wire accurate material taking method and system based on computer vision, and relates to the technical field of semiconductor packaging, and the method comprises the steps: collecting image features between a bonding silver wire and a material taking device through a sensor module; based on the image features, the position and morphological features of the bonding silver wire are judged; establishing a virtual material taking characteristic table to judge the real-time state of the bonding silver wire; and the material taking type is judged according to the real-time state of the bonding silver wire, and accurate material taking is carried out. According to the invention, image features are collected through the sensor module, and high-precision real-time monitoring of the bonding silver wire is realized; an advanced computer vision algorithm and a deep learning technology are utilized to accurately judge the position and morphological characteristics of the bonding silver wire; a virtual material taking feature table is established, dynamic tracking and prediction of the state of the bonded silver wire are achieved, and the stability and controllability of the material taking process are improved; and according to the real-time state of the bonding silver wire, a grading processing mechanism is adopted for accurate material taking, so that the material taking precision is improved, and the response capability of the system to abnormal conditions is enhanced.

The utility model provides a monitoring and early warning device for a debris flow gully in a canyon fall section, and relates to the technical field of natural disaster early warning. The device comprises a supporting column, a connecting frame, a sliding rail, a debris flow monitoring module and a rainfall monitoring module. Wherein the supporting columns are embedded and fixed on the two sides of a debris flow gully; the connecting frame is fixedly connected to the upper end of the supporting column. The sliding rail is fixed to the lower end of the middle of the connecting frame and extends in the same direction as the debris flow gully. The debris flow monitoring module is slidably connected to the sliding rail and can follow the debris flow state in the debris flow gully when the debris flow disaster occurs. And the rainfall monitoring module is fixed at the upstream position of the debris flow gully. According to the scheme, the debris flow monitoring module can move along the channel for monitoring through the sliding track, dynamic data collection is achieved in combination with the rainfall monitoring module, the problem that traditional fixed-point monitoring cannot adapt to complex canyon terrains is solved, and the accuracy and timeliness of early warning are improved.

The application provides a belt type pellet roasting parameter dynamic tracking method and device and related equipment, relates to the metallurgical industry manufacturing and informatization technical field, and first collects the operation parameters of the belt type roaster at detection points, wherein the operation parameters include roasting parameters and machine speeds at each detection time; then, based on the positions of the detection points and the machine speeds at each detection time, the target detection time when the pellets arrive at the detection points is determined; further, the roasting parameters and the machine speeds at the target detection time are extracted and recorded. The application can realize dynamic tracking of the pellets after entering the belt type roaster, has very important significance for optimizing and stabilizing process parameters and improving production management and control ability.

The invention discloses a method for simulating phosphorus and chromium migration during farmland irrigation with acid mine wastewater, which comprises the following steps: mixing a plant-derived organic material with deionized water to obtain a soluble organic matter; h2O2 oxidizes Fe < 2 + > to prepare pure Schwertmannite, and the pure Schwertmannite is placed in a phosphate solution to obtain phosphorus-loaded Schwertmannite; mixing the phosphorus-loaded Schwertmannite and the soluble organic matter with a chromate solution, carrying out oscillation adsorption, carrying out solid-liquid separation after adsorption, carrying out CrO and POconcentration change test on filtrate, and carrying out mineral characterization on separated solids; a three-dimensional fluorescence spectrum is adopted to track composition conversion of the soluble organic matter in the reaction process; and analyzing the component change of the supernate before and after the reaction by adopting Fourier transform ion cyclotron resonance mass spectrometry. The influence mechanism of DOM on phosphorus and chromium fate in mineral / water interface molecular fractionation is disclosed from the molecular level, and a scientific basis is provided for collaborative migration risk assessment of phosphorus and heavy metal in acid mine wastewater irrigation area farmland.

The application relates to the technical field of intelligent diagnosis, and discloses a quantitative X-ray scattering intensity anisotropy evaluation system based on a free electron laser, which comprises a signal excitation and collection end, a dynamic quantitative analysis end and a power station evaluation adaptation end; the free electron laser light source is adopted, X-rays generated by the free electron laser light source have intrinsic high-flux and ultrashort pulse characteristics, and the X-rays lay a foundation for obtaining high-contrast scattering signals inside materials. The system further introduces background noise filtering and data layering technology, pre-processes and hierarchically separates the collected scattering signals, thereby supporting early discrimination and evaluation of the equipment state; through signal synchronization and time sequence construction, the external field loading can be corresponded to the scattering response of the material, the dynamic tracking of the anisotropy evolution process of the material under the action of the external field is realized, and dynamic data support is provided for predicting the equipment life and formulating a maintenance strategy.

The application relates to the technical field of data center thermal management and intelligent control, in particular to a cold and electricity linkage group control method applied to micro data module center fusion feedforward control and hotspot tracking, which obtains IT load node computing power task scheduling intention sequence, real-time power consumption data, refrigeration terminal operation state and sparse environmental sensing data; a multi-dimensional thermal load feedforward tensor is output through a computing power-heat flow double-driven space-time graph convolution network; a three-dimensional temperature field is reconstructed and a hotspot drift vector field is extracted by fusing a physical information neural network and a fluid mechanics control equation; a model predictive control and multi-agent reinforcement learning fusion decision model with cold energy transmission lag compensation is constructed, and a cold and electricity collaborative action sequence is output; instructions are sequentially issued to realize dynamic matching of cold energy arrival and power consumption peak. The application deeply couples computing power scheduling and refrigeration control, feedforward predicts thermal load change, realizes accurate on-demand cooling and hotspot advance suppression, and significantly improves energy efficiency and thermal safety level.

The present invention discloses a data mining method and system based on self-learning, which collects time series image data of different fresh products at various freshness stages, extracts static features and dynamic features from them, and defines labels by analyzing these features, which associate static features with dynamic features to form a comprehensive description; according to the changing rules of dynamic features, products with similar change patterns are classified into the same similarity group; on this basis, the self-learning mining model is trained using these labels and similarity group data, focusing on improving the recognition ability of similar group products; the mining results are fed back to the dynamic spatiotemporal graph of the system to update the node attributes in the graph, thereby continuously optimizing the recognition algorithm. The present invention can not only effectively overcome the recognition difficulties caused by the change of dynamic features, but also provide a stable recognition benchmark through static features, thereby significantly improving the accuracy and reliability of fresh product recognition at different freshness levels.

The application relates to a kind of unmanned aerial vehicle dynamic path planning methods based on hybrid intelligent optimization, introduce multi-stage hybrid intelligent optimization algorithm, on the basis of static path planning based on particle swarm optimization, consider the dynamic target condition of real-time change, when unmanned aerial vehicle gradually approaches target and needs to carry out dynamic path adjustment, utilize A* algorithm mechanism to give more accurate tracking path planning scheme, so that unmanned aerial vehicle can dynamically adjust path, effectively coordinate and complete task in overall task execution. The application comprehensively considers various complex multi-constraint conditions and coordination relationship, solves the multi-unmanned aerial vehicle dynamic target tracking path planning problem, so that unmanned aerial vehicle can quickly respond when finding out the latest position of target, dynamically and real-timely adjust the track of unmanned aerial vehicle.

This invention relates to the field of tobacco procurement information technology, and discloses an intelligent processing system for weighing information and a weighing and sealing device for tobacco leaf pre-inspection. The system includes data acquisition, processing, interaction, and execution control modules. The data acquisition module performs time-series alignment of continuous weight data and identity data. The data processing module uses a peak-valley range algorithm to determine stability and lock the net weight, while simultaneously performing tare deduction and compliance verification. The data interaction module, based on visual anchor point positioning technology, establishes a non-intrusive transmission channel with external business systems, automatically corrects control coordinates, and simulates data entry. The execution control module, based on a finite state machine, drives seal generation and data entry when verification is successful, and triggers an audible and visual alarm and forcibly blocks the entry signal and sealing command when verification fails. This invention solves the problems of difficult integration with heterogeneous systems and error-prone manual data entry, achieving automated and accurate acquisition of weighing data and closed-loop quality control.

The invention discloses a progress-visualized data governance optimization system, which comprises a problem data state acquisition module used for acquiring a data record label of problem data and a problem data state of each current unit; the data governance trend display module is used for generating a problem data rectification rate trend chart and a stage governance effect comparison chart based on the data governance progress trend analysis result; the governance state recognition module is used for recognizing the governance state of each unit and judging the lag reason of the lagging unit; the lagging unit reminding module is used for generating lagging reminding content of each lagging unit and sending the lagging reminding content to the corresponding business domain responsible person and the governance responsible person; and the rectification efficiency identification module is used for generating new lag reminding contents for units which do not reach the preset treatment standard. According to the invention, through optimizing the display of the data management condition, the management layer can comprehensively master the management progress of each unit, the real-time, dynamic and visual display of the information is realized, and the efficiency and quality of the data management work are obviously improved.

The application relates to an image recognition-based intelligent inspection method and system for urban barrier-free facilities, and relates to the technical field of image recognition, which comprises the following steps: acquiring a time-series inspection image sequence in a plurality of continuous inspection periods; outputting a defect recognition result by using a pre-trained defect change tracking model, analyzing a diffusion trend, and calculating a deterioration rate; inputting a surrounding image into a scene occupation evaluation model to obtain a natural elimination probability evaluation value; calculating an emergency treatment priority index based on the deterioration rate and the elimination probability, and generating a maintenance work order with a differentiated treatment sequence according to the emergency treatment priority index. The application solves the technical problem that a traditional barrier-free facility inspection strategy may cause the maintenance resource allocation to deviate from the actual situation.

This invention discloses a battery state cycle monitoring method and system based on charge / discharge behavior, belonging to the field of battery state monitoring technology. It configures state attribute codes describing abnormal charge / discharge states of the battery, forming stage-specific labels. Within one state recording cycle of battery charge / discharge, it performs several cyclic captures of abnormal charge / discharge states of the battery under monitoring. It counts the captured abnormal states, quantifies the marginal probabilities of each stage's label and the joint probabilities between labels from different stages, uses a normalized point mutual information model to measure the first charge / discharge correlation between two stage labels, and uses an exponentially weighted moving average model to obtain the second charge / discharge correlation. Based on the comparison results with a preset threshold, it generates a battery state monitoring report. This invention achieves accurate identification and correlation analysis of abnormal patterns at different stages during battery charge / discharge, improving the accuracy and reliability of battery state monitoring.

The present invention discloses a material management system based on digital intelligence drive, which relates to the technical field of enterprise-level material optimization management, including: an enterprise material management platform, a mobile terminal, an external terminal and an internal terminal; the enterprise material management platform is integrated in a cloud server; the enterprise material management platform is used for comprehensive management of materials; the mobile terminal is used to scan the warehousing and outbound delivery of tools, materials and equipment, and detect the position information of the working surface where the operator is located, and transmit the read material QR code information, RFID electronic tag information and storage location QR code information to the enterprise material management platform; the external terminal is used to access the enterprise material management platform to manage materials; the internal terminal is used to manage and maintain the enterprise material management platform. The present invention can dynamically monitor the status of personnel and tools through the mutual cooperation of the above modules, improve the use saturation of personnel and tools, and realize the intensive and intelligent management of materials.

The invention belongs to the technical field of port intelligent transportation, and particularly discloses an in-port vehicle trajectory deduction method based on space-time correlation analysis, and the method comprises the steps: receiving multi-dimensional data of a vehicle in a port; determining historical passage data and real-time passage data based on the level data, determining an inter-region transition probability based on the historical passage data and the real-time passage data, and determining image similarities of different positions and different time points based on the image data; performing weighted fusion on the inter-region transition probability and the image similarity to obtain the degree of association of the vehicle transferred from the first region to the second region at the target moment so as to construct a space-time association matrix; and generating a vehicle driving track in a node-by-node prediction mode based on the space-time incidence matrix, and dynamically correcting the vehicle driving track through a double triggering mechanism of checkpoint passing recording and road monitoring to obtain final space-time track data. According to the invention, data reliability and time-space relevance can be improved, and accurate simulation of the vehicle motion trail is realized.

This invention relates to the field of big data analytics, specifically to a big data-based residual oil hydrotreating analysis system, comprising a data acquisition module, a path identification module, a disturbance confirmation module, an efficiency evaluation module, and a section output module. In this invention, multi-source dynamic data from the residual oil hydrotreating process is synchronized in time and reconstructed periodically. Path deviation behavior is screened based on dual thresholds for the direction and magnitude of feed rate changes. Disturbance trends are classified and identified by combining rate difference gradients. Furthermore, the directional matching relationship between aromatic concentration and hydrotreating efficiency is correlated, constructing a coupling response labeling mechanism among multi-source indicators. This enables dynamic tracking of the intrinsic causal relationship between feed disturbances and efficiency changes, clearly distinguishing between trend fluctuations and random disturbances. High-confidence coupling identification labels are output within the overlapping intervals of multi-source data, enhancing the perception of complex changes in the reaction process and improving the real-time performance and accuracy of operational condition judgment.

The utility model relates to engineering machinery safety technical field, concretely is a greenhouse inside loader operation anti -injury system, including loader car body and camera, the bottom side fixed connection of loader car body has the frame, the surface of frame is provided with adjusting mechanism and multifunctional component, and the adjusting mechanism is used for adjusting the shooting angle of camera, this adjusting mechanism, through control first motor, will swivel frame and camera turn to the horizontal position of personnel, simultaneously, control second motor, through first connecting rod and second connecting rod adjust the pitch angle of camera, ensure that personnel is always in the center position of camera picture, realize dynamic tracking, and then camera obtained the motion ability on two degrees of freedom of horizontal and pitch, not only can look around, but also can lift head (observe higher or distant target) and bow head (observe near, car bottom blind area or ground target), formed a spherical monitoring range.

The present application relates to the technical field of coal mine underground mining safety, and proposes a thick hard rock stratum anti-burst monitoring and supporting method, the steps of which include: implementing regional rock burst monitoring and local rock burst monitoring on the mining area, the regional monitoring uses a microseismic monitoring system to make the mining area covered by at least five monitoring points with a maximum distance between adjacent monitoring points not greater than 500 meters, and the local monitoring includes coal body stress monitoring and roadway displacement monitoring; according to the monitoring results, pre-decompression boreholes are implemented on the mining face and the excavation face; when the impact danger is monitored, large-diameter borehole danger relief or blasting danger relief is implemented; the effect of the danger relief measures is tested by using the microseismic monitoring method, the drilling cuttings method and the stress online monitoring method; and reinforced support is implemented in the roadway and the mining intensity of the mining face is limited. The present application effectively reduces the occurrence probability and harm degree of rock burst under the condition of thick hard rock stratum, and ensures the safety production of the mining face.

The invention discloses an automatic coprocessing system and method for an automobile financial process, and belongs to the technical field of automobile finance. The system comprises a data acquisition standardization module for integrating multi-dimensional data and outputting a standard data set; the risk portrait module extracts parameters, generates labels and constructs a dynamic network; the risk prediction module quantifies the default probability and generates a personalized strategy; the intervention execution module automatically propels a process and records a log; the model strategy iteration module adjusts the edge weight, optimizes the strategy library, forms closed-loop iteration, and improves the risk management and control efficiency; according to the invention, through multi-dimensional data integration and dynamic risk network construction, comprehensive risk perception and tracking are realized, and the limitation of traditional single assessment is broken; in combination with risk conduction analysis and personalized intervention, by means of an automatic execution and closed loop iteration mechanism, manual deviation is reduced, market changes are dynamically adapted, decision accuracy and system performance are improved, and automobile financial risk management and control are enhanced.

This invention discloses a pediatric jaundice treatment device and method for pediatric clinicians, relating to the field of medical device technology. The invention includes a base with an outer shell fixedly connected to its top. An opening and closing plate is connected to the inner wall of the outer shell via hinges. An inner light-transmitting shell is located on the top of the base, slightly smaller than the outer shell, and has a gap in between. This invention achieves dynamic tracking of the infant's torso by setting a U-shaped block and a rotating alignment mechanism. When the infant's sleeping position changes from supine to lateral, the pressure-sensing mattress detects the change in torso position in real time. A second controller transmits this signal to a first controller, driving a micro-motor to rotate a second lead screw, causing the U-shaped block to rotate to the corresponding angle. Simultaneously, the first motor drives the first lead screw to lower the mounting shell and rotating block to a position facing the side of the torso, ensuring that the light group is always aligned with the core area of ​​bilirubin accumulation.

The invention discloses a photovoltaic safety early warning method based on Bayesian dynamic belief propagation, and relates to the field of photovoltaic safety early warning. According to the method, a dynamic Bayesian network model of which the risk evolves along with time is constructed, belief propagation reasoning is performed on multi-source heterogeneous data by using a BD-BP algorithm, and risk weighted convergence is performed in combination with network topology centrality. Therefore, false alarms caused by environmental noise are effectively suppressed, dynamic tracking and accurate positioning of the gradient risk of the photovoltaic equipment are realized, the early warning has the characteristics of strong anti-interference capability and accurate key node identification, and the crossing from single-point passive alarm to system-level active situation awareness is realized.

The invention discloses an intelligent electrochromic glasses control method based on health monitoring, glasses, a medium and a processor, and relates to the technical field of intelligent glasses color change control. According to the method, physiological health data and ambient light data of a wearer are synchronously collected, a user regulation and control instruction is combined, a visual load state is analyzed in real time, a lens adjustment requirement matched with the physiological state is generated, a coloring and fading control threshold value of an electrochromic lens is adaptively adjusted, and finally the lens is driven to dynamically adjust the coloring state. The system comprises an acquisition module, a main control module and a control module, and realizes intelligent and personalized color change control. The problem that traditional electrochromic glasses only depend on ambient light and cannot adapt to the physiological state of a user is solved, and the visual comfort and health adaptability are improved.

The application provides a full-industry-chain lithium product trade security evaluation method, and relates to the technical field of international trade security evaluation. The method comprises the following steps: based on price change information and trade scale change information in the trade state sequence of the industry chain, combining the structure characteristic parameters, performing dynamic risk conduction analysis on the conduction process of trade risks between different trade subjects and different industry chain links, and generating risk conduction representation results. The full-industry-chain lithium product trade security evaluation method constructs a lithium product full-industry-chain division framework, forms an industry chain trade state sequence based on multi-source data cleaning and standardization, provides accurate basic data for subsequent risk evaluation, comprehensively monitors and analyzes the trade states of each industry chain link, and realizes dynamic tracking and risk identification of the full chain of lithium product trade.

The invention discloses a network intrusion tracing method and system based on behavior analysis, and relates to the technical field of network security. The method comprises the following steps: S1, constructing an attack activity propagation graph and calculating an attack propagation coefficient between nodes; s2, according to behavior data and attack propagation coefficients of each node in the attack activity propagation graph, calculating behavior pulse factors of the nodes, and determining attack participation nodes; s3, calculating a time propagation coefficient of an attack path and constructing an attack time trajectory according to interaction time difference characteristics and behavior pulse factors among the nodes; s4, according to the flow rate, the attack propagation coefficient and the time propagation coefficient between the nodes, calculating a traceability flow overflow index, and generating a potential attack source set; and S5, calculating an attack intensity adjustment coefficient according to the traceability flow overflow index and the flow rate, and triggering a defense strategy response mechanism based on the attack intensity adjustment coefficient. Precise traceability and real-time defense are realized through multi-dimensional behavior analysis, and the network intrusion response efficiency is improved.