44results about How to "Realize dynamic tracking" patented technology

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 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 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.

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 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 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.

The invention discloses a gas pipeline leakage judgment method and a storage medium. The method comprises the steps that S1, adaptive background concentration extraction is carried out; for the data points one by one, taking the median in the sub-window as an initial background concentration value, and further correcting the background concentration by adopting the change condition of the initial background concentration in the main window to obtain a background concentration value adapted to the data points one by one; s2, judging a methane source; the methane source is judged by comprehensively considering the ratio of methane to ethane enhancement value, methane and ethane change synchronism and the ethane change condition at the methane peak value. The storage medium is realized based on the method. The method has the advantages of simple principle, wide application range, easiness in implementation, high detection precision and the like.

The application discloses a shared space health condition automatic evaluation and cleaning scheduling method and system based on image recognition, a computer device and a storage medium. The method comprises the following steps: acquiring real-time space images in a shared space; performing multi-task identification and cross-task collaborative calibration on the real-time space images to generate health state data; calculating a dynamic health index based on historical health state sequences and spatial correlation between adjacent areas according to the health state data; when the dynamic health index is lower than a threshold, marking a region to be cleaned and encoding the health state data of the region to a cleaning demand feature vector; calculating the similarity between the vector and each candidate strategy feature vector in a strategy library, determining a target cleaning strategy according to the matching result and sending the target cleaning strategy to a cleaning execution end to perform cleaning work; and acquiring cleaning result data to update the dynamic health index. The application realizes real-time perception, scientific evaluation and accurate scheduling of the health condition of the shared space, and improves the utilization efficiency of cleaning resources.

The present application relates to the technical field of intelligent monitoring of electric power metering equipment, in particular to a mutual inductor full life cycle uncertainty tracking method and system based on physical information neural network. The method realizes real-time tracking of uncertainty through data preprocessing, data noise reduction processing, physical equation definition, physical information neural network construction and uncertainty calculation. The present application is economical and practical. A system framework based on physical information neural network is proposed. Through the combination of the full life cycle monitoring of the data analysis module, the calibration efficiency and result reliability are improved. Not only can the limitations of traditional technology be solved, but also the uncertainty tracking can be optimized through physical constraints, providing more accurate full life cycle management, significantly reducing maintenance costs and improving system stability.

The invention relates to the technical field of carbon emission monitoring, and discloses a high-carbon enterprise carbon emission monitoring method and device based on electric carbon data fusion, and the key point of the technical scheme is that the method comprises the following steps: S1, obtaining the characteristics of a target enterprise, and determining the carbon emission source of the target enterprise; s2, deploying a data acquisition system according to the carbon emission source, accessing a full-dimensional data source, and acquiring target data; s3, performing data processing and integration on the acquired target data, and constructing a standardized data set; s4, constructing an electricity and carbon calculation model, training through the standardized data set, and performing carbon emission accounting through the trained electricity and carbon calculation model; and S5, correcting the trained model, outputting a monitoring result after correction is completed, and performing real-time calculation and analysis by using an advanced mathematical model through deep integration of enterprise power consumption data and multi-source production and energy data so as to realize refined and dynamic monitoring of carbon emission of high-carbon enterprises.

This invention discloses a method for evaluating the effect of forest vegetation restoration, comprising: determining the study area for evaluating the effect of forest vegetation restoration; calculating the vegetation community index and ecological function index of the control area based on time series; calculating the extreme values ​​of fluctuation of the vegetation community index and ecological function index; calculating the influence weights of environmental factors and disturbance factors on vegetation community and ecological function; constructing a calculation model for calculating the forest vegetation restoration index based on the influence weights; uniformly selecting several sampling areas within the study area; calculating the forest vegetation restoration index of each sampling area using the calculation model; constructing a semi-variogram function; and evaluating the effect of forest vegetation restoration in the study area. This invention, starting from a four-dimensional index system of vegetation community-ecological function-environmental factors-disturbance factors, comprehensively evaluates the effect of forest vegetation restoration, obtains the spatial differences in the effect of forest vegetation restoration, and provides a basis for differentiated restoration management.

The present application relates to the technical field of heat digital twinborn analysis, in particular to a three-dimensional electro-catalytic oxidation device temperature field collaborative regulation method based on digital twinborn. The specific implementation process includes: extracting current ripple features and fluid damping fluctuation data in the operation process of the three-dimensional electro-catalytic oxidation device, and constructing an energy distribution domain in the digital twinborn body; tracking the energy accumulation center in the energy distribution domain and correcting the heat conduction; carrying out evolution simulation to predict the spatial migration and temperature change trend; superimposing based on the prediction result to generate control waveform flow for device regulation; constructing an energy interaction link to collaboratively regulate the global temperature field. The present application combines multi-source data fusion, full-field reconstruction and prediction-driven control strategy, improves the limitations of relying on limited measurement points and lag feedback regulation, realizes high-precision perception, prediction and collaborative optimization control of the three-dimensional electro-catalytic oxidation device temperature field, and improves the stability of the device operation.

The invention provides an internet-of-things data transmission method and system for exoskeleton state monitoring, and relates to the technical field of exoskeleton internet-of-things transmission, and the method comprises the steps: obtaining the monitoring data of a wearer through an exoskeleton detection device, recognizing a gait intention, and synchronously predicting a relation between a relative motion trend and a signal shielding between communication nodes; controlling the nodes to broadcast and package beacons of motion vectors and link detection results periodically, and exchanging the beacons by the nodes to construct a local network topological graph of edge weight fusion detection results and link stability parameters; a hierarchical clustering structure is formed through distributed consensus optimization, and a high-stability cluster head is selected; establishing a multi-hop transmission path taking a cluster head as a relay based on the structure, and maintaining a path concentration value representing transmission quality; and when the cooperative control instruction is forwarded, the next hop is selected in a probabilistic manner according to the value to complete instruction distribution, so that self-adaptive and high-stability multi-hop transmission of the cooperative control instruction in the exoskeleton Internet of Things can be realized.

This invention relates to the field of big data processing technology, specifically disclosing an artificial intelligence-based method and system for optimizing municipal engineering construction plans. The method includes the following steps: S1: Obtain the total length of the construction section, periodically obtain the traffic flow of the construction section, calculate the traffic flow threshold based on the total length of the construction section and the number of remaining lanes, and mark the congestion cycle; S2: When a congestion cycle is detected, obtain monitoring images of the two intersections with the shortest distances from the start and end points of the construction section, obtain the changing patterns of the intersection traffic lights, and determine the number of vehicles waiting to enter based on the direction of the directional arrows; S3: Calculate the theoretical traffic flow and the comprehensive traffic flow, calculate the overflow traffic flow, and adjust the changing patterns of the intersection traffic lights. By judging the road congestion situation based on the traffic flow of the construction section, the corresponding two intersections are linked, and the changing patterns of the intersection signals are reasonably adjusted to reduce the probability of congestion in congested sections and avoid regional traffic paralysis.

This invention relates to the field of intelligent diagnostic technology and discloses a quantitative X-ray scattering intensity anisotropy assessment system based on free-electron lasers. The system includes a signal excitation and acquisition end, a dynamic quantitative analysis end, and a power distribution station assessment adaptation end. By employing a free-electron laser source, the generated X-rays possess intrinsic high throughput and ultrashort pulse characteristics, laying the foundation for obtaining high-contrast scattering signals within materials. The system further introduces background noise filtering and data layering techniques to preprocess and hierarchically separate the acquired scattering signals, thereby supporting early identification and assessment of equipment status. Through signal synchronization and time series construction, the system can correlate external field loading with the material's scattering response, achieving dynamic tracking of the material's anisotropic evolution process under external field action, providing dynamic data support for predicting equipment lifespan and formulating maintenance strategies.

The application discloses a kind of drying device for silt and its use method, belong to silt processing technical field.The device includes network electricity, rectifier filter circuit, DC-DC converter, DSP processor, single-chip microcomputer control system, PWM amplification circuit, full-bridge inverter circuit and electrode.Network electricity is converted into direct current by rectifier filtering, and voltage conversion is carried out by DC-DC converter;DSP processor evaluates silt state and generates pulse signal, and single-chip microcomputer generates PWM signal, which is amplified to drive full-bridge inverter circuit to convert direct current into bipolar pulse voltage output to electrode, forming alternating electric field.Use method includes placing silt between electrodes, starting device, detecting humidity, optimizing tracking optimal drying point by resistivity-frequency closed loop, accelerating moisture migration, until resistivity is greater than 200Ω·m and humidity reaches 40% to complete drying.The device has the characteristics of low energy consumption, high efficiency, accurate control and no electrode corrosion.

The application relates to a kind of power grid resilience evaluation method and system based on urban lifeline cross-system interconnection, method includes: the connected network model of the to-be-evaluated power grid in target area is built;Through the preset cascading failure mechanism, the fault propagation of the to-be-evaluated power grid under the preset disaster situation is carried out, and the fault propagation result is obtained;Through the preset recovery mechanism, the recovery simulation of the to-be-evaluated power grid under the preset disaster situation is carried out, and the recovery simulation result is obtained;Based on the predefined structural resilience index, the fault propagation result and the recovery simulation result are analyzed, and the structural resilience of the to-be-evaluated power grid is obtained;Based on the predefined functional resilience index, the fault propagation result and the recovery simulation result are analyzed, and the functional resilience of the to-be-evaluated power grid is obtained;The structural resilience and functional resilience are fused to obtain comprehensive resilience, and the resilience evaluation of the to-be-evaluated power grid is completed.Compared with prior art, the comprehensiveness and accuracy of the power grid resilience evaluation are significantly improved.

This invention relates to the field of edge computing technology and discloses a real-time data processing and intelligent analysis system for an IoT platform based on edge computing. The system includes: acquiring multi-source sensor data from a distribution transformer and performing time-scale normalization; performing frequency domain transformation on electrical parameter waveforms to extract multiple types of heat generation power and superimposing them to generate a total heat source; combining the total heat source and component metadata to recursively calculate the heat-retaining particle state quantity reflecting heat transfer hysteresis; obtaining the temperature distribution of hidden hotspots through a swarm optimization algorithm; generating insulation aging and damp heat activation indicators based on the extreme temperatures and locations of the hotspots, combined with moisture activity; calculating the sensitivity of each data point to the hotspots to allocate edge computing power and upload bandwidth; updating the device parameter library based on algorithm evolution and generating asset maintenance ranking scores. This invention effectively reduces the spatiotemporal lag of data under conditions of limited computing power and bandwidth, realizing dynamic analysis and adaptive resource allocation of hidden thermal states.