3896 results about "Thermal resistance" patented technology

The invention discloses a radiator salt spray corrosion life prediction method based on dynamic time warping, which belongs to the technical field of material corrosion test and life prediction, and comprises the following steps: collecting time sequence data of surface impedance and thermal resistance change of a radiator, constructing a dual-channel corrosion characteristic data set, and recording a salt spray concentration data value. The temperature data value and the humidity data value are combined, and an environment sensitivity weight vector is established. Accelerated corrosion in a salt spray environment is simulated, a laboratory accelerated corrosion test spectrum is generated, meanwhile, an actual environment fluctuation spectrum is monitored, the two spectrums are aligned by using a weight vector, accelerated corrosion data are obtained, and a basic life prediction value is calculated. And calculating an environment-structure coupling factor by combining the interaction between the three-dimensional structure characteristic parameters of the radiator and the temperature and humidity data values, correcting the basic life prediction value, and generating a final life prediction result. According to the method, double-channel feature alignment and coupling factor correction are adopted, and the corrosion life of the radiator of the specific structure under the actual working condition can be predicted.

The invention relates to the technical field of power equipment monitoring, in particular to a 10kV cable joint temperature inversion correction method based on environmental heat exchange conditions, which comprises the following steps: measuring surface temperature data through a sensor array, and analyzing material layering characteristics in combination with X-ray imaging; then, establishing an electromagnetic-thermal-fluid field coupling model, and calculating a dynamic thermal resistance coefficient and a heat flow distortion index; thirdly, optimizing surface temperature distribution and iteratively updating thermal resistance parameters by utilizing a bidirectional feedback correction strategy, and finally generating a high-precision internal temperature field; through adaptive temperature compensation and multi-source data fusion, the accuracy of temperature prediction is improved, long-term monitoring errors are reduced, the method can be widely applied to intelligent operation and maintenance and fault early warning of cable joints, and the safety and stability of a power system are improved.

The invention relates to a thermal insulation evaluation method for a light recycled building block based on thermal coupling simulation, which comprises the following steps: modeling the recycled building block into a heterogeneous multiphase complex, and introducing a three-layer structure field of micro pores, mesoscopic aggregates and macroscopic blocks; a partition coupling strategy is adopted, a microstructure variability-heat flux density disturbance-stress field reconstruction causal chain is constructed, and macroscopic thermal insulation performance fluctuation caused by thermal deformation is captured; tracking a thermal stress concentration area caused by temperature difference change through thermal and force coupling simulation; analyzing the influence of a thermal stress migration path on local structure integrity, pore change and crack evolution; constructing a thermal stress and structure disturbance factor framework, and evaluating the influence degree of the structure local deformation on the thermal resistance; extracting high-dimensional feature data; establishing a heat and force characteristic space; constructing a response surface equation, and mapping a change track of the thermal insulation performance in a heat and force coupling response space; a time and structure response composite scoring system is formed, real coupling of multiple physical fields is achieved, and limitation of traditional evaluation is broken through.

The invention relates to the technical field of chip temperature control, and discloses a chip temperature regulation and control system and method, and the method comprises the steps: building a thermal field dynamic model, integrating real-time power consumption data and environment heat dissipation parameters, and generating a thermal resistance adjustment coefficient and a power consumption correction coefficient; establishing a temperature prediction network to perform multi-source temperature field prediction; a dynamic regulation and control strategy is set according to a prediction result, and heat dissipation control parameters are optimized to achieve thermal field balance control; and executing feedback calibration and model iteration. The system comprises a thermal field dynamic modeling module, a multi-source temperature field prediction module, a dynamic regulation and control strategy execution module, a feedback calibration module and an iteration module. The method can accurately predict the heat distribution of the chip, realizes real-time and intelligent temperature regulation and control, improves the performance and reliability of the chip, reduces the energy consumption, and has good adaptability and universality.

The invention discloses a charging pile intelligent heat dissipation method and device based on heat conduction line optimization and a medium, belongs to the technical field of charging pile heat dissipation, and aims to solve the technical problem of how to avoid the defects of high thermal resistance, response lag and large energy consumption in a traditional charging pile heat dissipation scheme and improve the heat dissipation efficiency and operation reliability of a charging pile. According to the technical scheme, a heat conduction structure is optimized; deploying a thin film thermocouple and constructing a three-dimensional temperature field model through infrared thermal imaging; establishing a thermal resistance-flow-power transfer function model by adopting a fuzzy PID (Proportion Integration Differentiation) and model predictive control hybrid algorithm; historical charging data are analyzed based on an LSTM neural network, a power peak value is predicted 300 ms ahead of time, and heat dissipation equipment is pre-started.

The invention relates to the technical field of chip testing, and discloses an LED driving chip testing method, device and equipment and a storage medium, and the method comprises the steps: carrying out the multi-point temperature excitation and constant-current output synchronous collection of an LED driving chip, and obtaining electrothermal coupling test data; performing thermal resistance network decomposition on the temperature field in the chip to obtain temperature distribution characteristic parameters; performing nonlinear function fitting on the temperature-constant current coupling relation to obtain an electrothermal coupling transfer coefficient; performing four-dimensional coupling calculation on the temperature distribution characteristic parameter and the electrothermal coupling transfer coefficient to obtain four-dimensional coupling response characteristic data; and partial differential sensitivity calculation is carried out based on the four-dimensional coupling response characteristic data, and an electrothermal coupling sensitivity analysis result is obtained.According to the method, the problem of test errors caused by time desynchrony in a traditional separated temperature-current test is solved, quantitative sensitivity analysis of electrothermal coupling parameters is achieved, and the sensitivity of the electrothermal coupling parameters is improved. Therefore, the test accuracy of the LED driving chip is improved.

The invention relates to the technical field of power system state monitoring, in particular to an intelligent fault detection method and system for a power distribution cabinet, and the method comprises the steps: setting a to-be-detected point and a reference point in the power distribution cabinet, and enabling the load current of the to-be-detected point and the instantaneous thermal resistance ratio to form a characteristic tuple at the current moment; obtaining an actual joint probability density value and a theoretical joint probability density value of the feature tuple at the current moment through two-dimensional joint probability density estimation based on space-time self-adaption; and determining an abnormal score of the feature tuple at the current moment through abnormal analysis, and determining a fault risk index at the current moment according to a relative deviation between the instantaneous thermal resistance ratio of the to-be-detected point at the current moment and the theoretical instantaneous thermal resistance ratio and the abnormal score, and according to the continuous change trend of the fault risk index, calculating an early warning index to determine whether the power distribution cabinet has a fault. The method improves the fault detection accuracy of the power distribution cabinet.

The invention relates to a thermal coupling over-reduced order prediction method and system for a multi-component assembled nonlinear system. The method comprises the following steps: collecting multi-scale physical field data; constructing an intrinsic orthogonal decomposition basis function space of a temperature field and a stress field, and establishing a double-field coupling constraint equation; constructing contact thermal resistance parameterized proxy models of a cylinder contact area, a bolt area and a free deformation area by adopting a domain discrete empirical interpolation method; constructing a parametric intrinsic mode tensor network to obtain a decline model which is used for realizing real-time reconstruction of a mode basis function through acquired tensor slices in an online stage; performing dynamic inversion based on a modal basis function reconstruction result, and outputting a predicted transient displacement field, a predicted temperature gradient field and a predicted contact stress field; and obtaining real-time parameters, and calculating a residual error with a corresponding prediction result so as to dynamically update the primary function and interpolation point distribution. Compared with the prior art, the real-time prediction of the transient thermal coupling of the multi-component contact system is realized on the premise of ensuring the precision.

The invention discloses an airport ground air conditioning unit multi-system energy-saving control method and system, and the method comprises the steps: collecting refrigerant flow data, temperature monitoring data and load demand data of an airport air conditioning system, recognizing a phase change boundary, extracting a gas-liquid conversion point, and carrying out enthalpy value coupling in combination with superheat degree distribution to generate a phase change energy field; identifying heat transfer bottleneck points based on the phase change energy field, generating an equivalent thermal resistance network, and extracting heat capacity characteristic parameters to construct a thermal response path diagram; refrigerant shunting analysis is carried out to extract primary and secondary loops, and an optimal distribution point is identified to generate a load balance matrix; reconstructing a compressor adjusting curve, and identifying a high-efficiency operation interval to generate a frequency conversion adjusting sequence; determining an energy storage window period, and obtaining a dynamic buffer threshold to construct a peak clipping and valley filling instruction set; and an execution deviation track is monitored, the optimal convergence path is recognized, self-adaptive correction is conducted, an energy-saving control instruction is generated, and intelligent multi-system coordination efficient energy-saving control over the airport ground air conditioning unit is achieved.

The invention relates to an automatic identification control method and system based on heat dissipation of a liquid cooling plate in a heat exchange system. The method comprises the following steps: acquiring real-time operation data of a target liquid cooling plate; establishing a dynamic thermal resistance network model, and calculating a current thermal resistance value; refrigeration demand parameters are obtained, and a demand weighted thermal resistance value is generated in combination with the current thermal resistance value; thermal resistance deviation is obtained based on the demand weighted thermal resistance value, and the opening degree of a cooling liquid flow valve in the heat exchange system is dynamically adjusted through a fuzzy PID controller; the PID parameters are updated through a preset optimization algorithm, and the fuzzy PID controller is optimized; according to the automatic identification control method and system based on heat dissipation of the liquid cooling plate in the heat exchange system, real-time dynamic adjustment of the flow of the cooling liquid is achieved by establishing the dynamic thermal resistance network model and combining fuzzy PID control, the problems that a traditional method lags in response and is insufficient in control precision are solved, and the control efficiency is improved. The method has the effects of improving the dynamic response speed, improving the control precision and optimizing the energy efficiency.

The invention discloses a new energy commercial vehicle fast charging working condition thermal management control method and system, and relates to the technical field of new energy vehicle thermal management and fast charging control, and the method comprises the following steps: collecting the temperature, voltage and current data of each subarea of a battery in a fast charging process, forming a time synchronization sequence, and based on the sequence, obtaining a new energy commercial vehicle fast charging condition; calculating internal thermal resistance and thermal capacity parameters of the battery in real time by using an online identification algorithm, updating a basic thermal model to obtain a corrected thermal dynamic model reflecting actual thermal characteristics of the current battery, importing the corrected model into a model prediction controller, constructing a multi-objective optimization function, and performing rolling solution in a prediction time domain to obtain a prediction model; and outputting an optimal target charging current instruction and a cooling total demand, adjusting the charging power according to the target current, and combining the temperature difference distribution of each partition. Accurate prediction and partition cooperative control of the thermal state of the battery in the fast charging process are achieved, the temperature rise and the temperature difference are effectively restrained while the charging efficiency is guaranteed, the service life of the battery is prolonged, and the system safety is improved.

The invention discloses an axial flux motor temperature prediction method based on equivalent thermal circuit method calculation, and the method comprises the following steps: 1, motor thermal circuit unit division: decomposing a motor into a stator unit, a rotor unit, an air gap unit and a housing unit, and constructing an equivalent thermal network through a node-branch method; 2, calculating a multi-physics coupling heat source; 3, thermal resistance parameter dynamic calculation and CFD coupling optimization: calculating conduction thermal resistance, convection thermal resistance and contact thermal resistance; and 4, parameter self-calibration based on machine learning: constructing a PINN model according to a physical law and known physical parameters, introducing a Bayesian optimization algorithm on the basis of the PINN model, adjusting and optimizing the parameters of the PINN model by using Bayesian optimization, designing a reinforcement learning algorithm, and carrying out self-calibration on the parameters of the PINN model. Enabling the reinforcement learning algorithm to dynamically adjust parameters according to the real-time operation data of the system and the prediction result of the PINN model; 5, constructing and solving a heat balance equation; and step 6, visualizing and verifying the temperature field.

The invention discloses a high-strength and high-toughness aluminum nitride ceramic and a preparation method thereof, and relates to the technical field of ceramics, a sol-gel method is adopted to coat the surface of aluminum nitride with a stable shell layer to form a core-shell structure, meanwhile, the low lattice mismatch rate of a core-shell interface is utilized to reduce thermal resistance, and toughness and thermal conductivity are both considered; according to the external magnetic field tape casting method, the magnetic dipole moment orientation principle is utilized, an external magnetic field is applied in the tape casting stage, the in-plane mechanical property is improved, and the fracture toughness is improved through the magnetism of aluminum nitride whiskers; a reinforcement is introduced to improve the mechanical property and corrosion resistance of the aluminum nitride ceramic material, multi-granularity powder is compounded, large-particle aluminum nitride powder is used as a sintering and heat-conducting framework material, and high activity provided by submicron particles is utilized to promote sintering, so that the sintering temperature of aluminum nitride can be remarkably reduced, and the performance is greatly improved; and the aluminum nitride substrate expands more application fields on a future packaging circuit.

The invention provides an all-silicon carbide double-sided heat dissipation module packaging method based on gradient thermal resistance optimization, and belongs to the technical field of electronic component packaging. Establishing a thermal resistance characteristic curve, and calculating a gradient thermal resistance vector to determine a heat flow path; constructing a heat dissipation temperature distribution matrix; obtaining thermal diffusion data; heat dissipation path thermal resistance is calculated by combining the thermal diffusion matrix and the temperature distribution matrix, and a thermal resistance sparse matrix is established and is dimensionally reduced into a thermal resistance low-dimensional matrix; calculating an optimal heat dissipation path parameter set; inputting the parameter set into a thermal resistance prediction deep attention network model for verification and fine tuning, and generating a final thermal resistance distribution scheme; a module structure and a material ratio are designed according to the scheme to form a sandwich structure; a silver paste sintering process is adopted to realize low thermal resistance connection and complete packaging, and the technical problems of non-uniform thermal resistance distribution and difficulty in optimizing a heat flow path in a double-sided heat dissipation structure of a silicon carbide power module in the prior art are solved.

The invention discloses a liquid cooling charging gun temperature control method for charging an electric vehicle, and relates to the technical field of liquid cooling control, and the method comprises the steps: carrying out the liquid cooling initialization, detecting the integrity of a bionic fractal microchannel and the distribution of phase change microcapsules, calibrating a magnetic field parameter, loading a pre-trained prediction model and a thermal resistance network model, and outputting a ready signal to a charging pile; after the charging pile communicates with a vehicle, according to charging power and environmental parameters, matching an initial flow, a magnetic field intensity threshold value and a piezoelectric vibration frequency, and activating a phase change microcapsule latent heat mode and pulse cooling; and executing pulse cooling and magnetic field fluctuation in a low-flow latent heat mode to remove sediments, recovering a full-flow mode when the temperature falls back, and monitoring an abnormal event to trigger grading protection at the same time. The dynamic heat dissipation performance and working condition adaptability of the liquid cooling charging gun are improved by constructing bionic fractal flow channel-phase change microcapsule-magnetic field regulation and control.

The invention discloses a horizontal shell and tube heat exchanger, which relates to the technical field of heat exchangers and comprises a shell, two sides of the shell are fixedly connected with a first tube box and a second tube box respectively, an inner cavity of the shell is provided with a plurality of baffle plates, each baffle plate is provided with a plurality of heat exchange tubes, and one side of each baffle plate is provided with a control assembly mounted in the second tube box. According to the horizontal shell and tube heat exchanger, the scraping ring can move left and right along with the movable rod, impurities on the outer wall of the heat exchange tube can be scraped away, in the long-term operation process of heat exchange equipment, various impurities are prone to being accumulated on the outer wall of the heat exchange tube, the impurities can reduce the heat exchange efficiency and increase the energy consumption of the equipment, and the scraping ring can slide to clean the heat exchange tube. The impurities can be effectively removed in time, the surface of the heat exchange pipe is kept clean, it is ensured that heat exchange equipment is in a good working state all the time, good heat exchange between a heat exchange medium and the heat exchange pipe can be ensured through the clean outer wall of the heat exchange pipe, heat resistance is reduced, and therefore the heat exchange efficiency is improved.

The invention belongs to the technical field of evaporation-boiling heat dissipation in a limited space, and relates to a heat dissipation device of a capillary core coupling manifold microchannel, and the heat dissipation device realizes vapor-liquid efficient separation and thermodynamic equilibrium regulation and control through the synergistic effect of thin film evaporation of a capillary core structure and boiling heat exchange of the manifold microchannel. The capillary core structure utilizes high porosity and strong capillary force to realize rapid liquid supplementing and uniform spreading of a working medium, so that local dryness is avoided; the radial manifold structure reduces the flow resistance and improves the temperature uniformity through the topological optimization of the flow channel; the directional exhaust design of the steam channel fundamentally inhibits steam bubble backflow. In a multi-heat-source scene, the device can dynamically adjust the branch flow through a thermal resistance-flow resistance coupling model, and the system stability is remarkably improved. The invention has the advantages of high heat flow bearing capacity, low energy consumption and strong environmental adaptability, and provides an innovative solution for reliable heat management of high-power electronic devices.

The invention discloses a high-temperature surface contact thermal resistance elimination method based on double thermocouple compensation, and belongs to the technical field of material thermal property characterization and testing. The method comprises the following steps: synchronously acquiring double-thermocouple temperature, and obtaining a temperature difference signal through filtering calibration and environment correction; calculating the real-time heat flux density according to the corrected temperature difference, the Seebeck coefficient and the dynamic correction factor; establishing a nonlinear dynamic coupling model containing contact thermal resistance parameters, and performing temperature interval division; identifying a contact thermal resistance parameter on line by adopting a self-adaptive recursive least square algorithm, and generating a dynamic thermal resistance compensation value; and applying the compensation value to a double-thermocouple signal according to the weight, and outputting accurate high-temperature surface temperature. According to the method, data acquisition and preprocessing, dynamic heat flow correction, nonlinear segmented modeling, self-adaptive online identification and refined compensation output strategies are adopted, the influence of high-temperature surface contact thermal resistance can be effectively eliminated, and the accuracy and reliability of temperature measurement in the high-temperature environment are remarkably improved.

The invention relates to the technical field of intelligent temperature control, in particular to an industrial mainboard computer heat dissipation optimization method and system based on AI intelligent regulation and control, and the method comprises the steps: obtaining mainboard real-time temperature data, carrying out time sequence preprocessing, and generating distributed time sequence data; extracting thermal features and classifying and identifying the thermal features to obtain coordinate distribution of the high-energy-consumption area; inputting a classification model to output a classification result, and screening areas exceeding a preset threshold to determine a priority regulation label; performing spatial interpolation based on the label to generate a heat map, and extracting heat distribution boundary data; analyzing thermal resistance according to the boundary data and identifying a bottleneck region to obtain thermal resistance distribution; performing fan parameter optimization based on the thermal resistance to obtain an optimized heat dissipation strategy; inputting a load model, and outputting dynamic load adaptation regulation and control parameters; and real-time regulation and control and energy efficiency evaluation are executed according to the regulation and control parameters, and final heat dissipation operation parameters are screened and solidified. The method can solve the problem of heat dissipation control lag.

The invention belongs to the technical field of building heat supply and intelligent power grid demand response control, and particularly relates to an intelligent power grid-oriented heat pump dynamic preheating and demand response control method, which comprises the following steps of: identifying building thermal characteristic parameters, introducing real-time environment variables such as external meteorological parameters and the like and thermal resistance and thermal capacity characteristics of a building, excessive or insufficient preheating caused by only relying on a timer is effectively avoided, and the balance of accurate heat supply and energy conservation is achieved; by adjusting the preheating starting time and the peak period temperature control strategy, the heat pump can dynamically respond according to the electricity price or the power grid demand signal, and the peak load is translated or reduced, so that the dual purposes of economic benefits, energy conservation and emission reduction are achieved; and formulating a peak period control strategy and formulating a non-peak period control strategy. According to the control method, actual thermal characteristics and external meteorological conditions of a building are taken as cores, load reduction in the peak period of a power grid and indoor thermal comfort are taken as double targets, and preheating time self-adaption, demand response flexibility and system operation reliability are achieved at the same time.

The invention provides a soot blowing control method, device and equipment for a boiler and a storage medium, and the method comprises the steps: collecting a soot deposition state image of a heating surface of the boiler in real time through visual equipment, carrying out the segmentation and feature extraction of the image, and generating an initial detail feature vector; reconstructing a dust deposition feature image based on the feature vectors, further segmenting and extracting basic local feature vectors, and generating a final dust deposition state image; and classifying the ash deposition state images corresponding to all the visual devices, calculating the ash deposition thermal resistance value corresponding to the target image, and comparing the ash deposition thermal resistance value with a preset threshold value so as to intelligently decide whether to start the ash blower to remove the deposited ash. By the adoption of the technical scheme, redundant soot blowing operation is reduced, the steam consumption of the soot blower and the blowing damage risk of the heating surface are effectively reduced, meanwhile, safety accidents caused by soot deposition are avoided, and the safety and economical efficiency of boiler operation are improved.

The invention discloses reflection-heat insulation dual-functional aluminum oxide ceramic and a preparation method and application thereof.The method comprises the steps that after surface silanization treatment is conducted on nanoscale hollow oxide filler, surface-modified nanoscale hollow oxide filler is prepared; and then adding the surface-modified nanoscale hollow oxide filler into a high-molecular polymer and a mixed polar solvent to obtain the thermal insulation coating. The method comprises the following steps: coating the surface of aluminum oxide ceramic with a heat insulation coating to form a primary coating, and carrying out gradient heating curing to obtain aluminum oxide ceramic with a functionalized heat insulation coating; and coating the surface of the thermal insulation coating functionalized aluminum oxide ceramic with an infrared reflection coating, and carrying out annealing treatment in a nitrogen atmosphere to prepare the reflection-thermal insulation dual-functionalized aluminum oxide ceramic. By constructing a double-layer composite structure, enhancing interface thermal resistance through chemical bonding, directionally distributing the nanofiller and designing a low-radiation layer structure, heat conduction and radiation heat transfer of the aluminum oxide ceramic-based material are synergistically reduced, and the high-temperature heat insulation performance of the aluminum oxide ceramic-based material is improved.

The invention discloses a self-correction optimization method and system for heat transfer boundary conditions of a water jacket heater, and particularly relates to the technical field of condition optimization control. The method comprises the following steps: constructing a thermal fatigue deformation trend estimation model by collecting a furnace wall surface temperature sequence, furnace wall surface heat flux distribution information and a furnace wall thermal stress response curve of a furnace body structure component, and generating a geometric parameter drift vector; performing structure equivalent mapping analysis on the geometric parameter drift vector, and extracting contact thermal resistance change information; performing furnace wall heat flow field reconstruction on the geometric parameter drift vector to obtain a dynamic correction vector; and the contact thermal resistance change information and the heat flow correction vector are comprehensively analyzed, a time-varying boundary condition inversion model is constructed, and a multi-parameter coupling boundary correction set is output and used for updating the boundary conditions in the water jacket heating furnace heat transfer simulation model, so that identification and self-adaptive correction of the boundary conditions are realized, and the heat transfer control precision and the heat efficiency are improved.

The invention relates to the technical field of metal material welding, and discloses a welding method for a precise heat dissipation tooth-shaped plate. The method comprises the following steps: carrying out primary welding on a precise heat dissipation tooth-shaped plate, collecting multi-source original sensing data of a welding joint, and carrying out multiple preprocessing and three-dimensional structure reconstruction and image enhancement on the welding joint; performing defect partition segmentation on the obtained three-dimensional defect fusion data, extracting various defect characteristic parameters from a welding abnormal region, performing comprehensive calculation and defect type judgment, performing heat conduction path calculation and thermal resistance value evaluation based on the obtained fine welding defect characteristic type and spatial position information, and predicting the heat dissipation performance. Generating a primary welding quality report; and according to the welding quality report and the associated database, welding process control parameters and welding optimization control are adjusted, and the heat dissipation tooth-shaped plate with the target welding quality is obtained. Accurate detection of welding defects of the heat dissipation tooth-shaped plate and closed-loop optimization of technological parameters are achieved, and the heat dissipation performance and the welding reliability are improved.

The invention discloses a thermal insulation performance detection method and system for a composite wallboard, and relates to the technical field of building material detection, and the method comprises the steps: dividing a composite wallboard sample into a plurality of grids, setting an inversion starting point for each grid according to initial data, starting an inversion algorithm to gradually adjust the heat conductivity coefficient of each grid, and generating a heat conductivity coefficient distribution diagram, calculating the average heat conductivity coefficient and the overall thermal resistance value of the sample; the test platform applies full-automatic thermal excitation and sound wave excitation to a sample, collects sound signals and thermal imaging data related to internal defects of the composite wallboard, calculates the optimal matching time point of the sound signals and the thermal imaging data, and extracts defect related characteristics in the sound signals and temperature anomaly characteristics in thermal imaging in a double-flow processing mode. Generating a comprehensive defect distribution diagram, and comparing the comprehensive defect distribution diagram with the heat conductivity coefficient distribution diagram and the average heat conductivity coefficient to obtain preliminary judgment; through acoustic-thermal multi-mode cooperative detection, the spatial distribution of tiny defects in a sample is accurately positioned, and the influence of the tiny defects on the heat-conducting property is judged.

The invention discloses a high-precision power supply output correction method based on a digital pre-distortion technology, and relates to the technical field of power electronics, and the method comprises the steps: integrating an electricity-heat-magnetism real-time combined observer, and inputting parameters including a power supply output voltage, a current, a power device junction temperature, a magnetic element surface temperature, an environment temperature, and an input voltage ripple; using a hierarchical memory depth pre-distortion compensator to generate an anti-phase pre-distortion signal containing long time domain thermal constant compensation and short time domain capacitance energy storage compensation based on modeling engine output; based on a double-ring adaptive updating module, an inner ring updates electrical parameters, including on resistance and dead time, by taking a switching period as a reference, and an outer ring updates thermomagnetic parameters, including thermal resistance and a magnetic core saturation point, in a minute-level period; and the DAC is connected in series with a pre-distortion signal output end through an anti-interference execution channel, and comprises a noise shaping DAC and a driving stage for delay matching. According to the invention, through an electric-thermal-magnetic three-field combined observation architecture, the limitation of traditional single physical field monitoring is broken through.

The invention relates to the technical field of thermal management material preparation, solves the technical problems of loose heat conduction network structure and non-uniform heat conduction direction of a flexible composite phase change material, and particularly relates to a magnetic polymer-based flexible composite phase change material and a preparation method thereof. Comprising the following steps: preparing a modified polydimethylsiloxane prepolymer from a carbon nanotube dispersion liquid and a polydimethylsiloxane prepolymer; adopting a Pickering emulsion method to mix 42 # paraffin, the modified polydimethylsiloxane prepolymer and nano cellulose to prepare a composite phase change material emulsion; silver mirror reaction is adopted to carry out surface silver plating on the magnetic neodymium iron boron particles; the magnetic polymer-based flexible composite phase change material is prepared from the composite phase change material emulsion and the surface-silvered magnetic neodymium iron boron particles. The high flexibility and magnetism of the prepared material in a normal temperature state endow the material with a more convenient installation mode and lower contact thermal resistance, the heat conduction network structure and component compatibility of the material are improved, and the application requirements of a phase change thermal management technology can be met.

The invention relates to the technical field of facility management, in particular to a prediction-driven data center thermal resistance control system which comprises an airflow response acquisition module, a thermal hysteresis offset correction module, a heat flux trend extraction module, an air volume priority allocation module and an airflow execution verification module. According to the method, through extraction and sorting of air supply trigger time and thermosensitive node temperature response differences, the temperature control sensing precision is improved, the corrected time sequence is input into the model, the prediction accuracy is enhanced, and dynamic identification of the high-heat-load area and the early warning capability are enhanced in combination with the area temperature change trend and the heat dissipation capability upper limit; the distribution sequence is sorted according to the heat flux trend and the air volume resource relation, the air volume allocation efficiency and the matching degree are improved, the temperature change trend is compared after execution, the adjusting effect reliability is improved, a data closed loop with response recognition, trend extraction, resource sorting and feedback verification as the core is constructed in the whole process, and the initiative and stability of system heat management are enhanced.

The invention belongs to the technical field of PCB testing, and discloses a performance testing method of an AI server PCB. Comprising the following steps: acquiring power-on operation temperature data of the PCB to construct a temperature distribution image, determining hot spot region characteristics based on the temperature distribution image to obtain heating test parameters, performing heating test on the PCB based on the heating test parameters, acquiring thermal resistance of each position of a hot spot region, drawing a thermal resistance characteristic curve, and analyzing the thermal resistance characteristic curve to obtain a thermal performance grade of the PCB. The bending rate of the bending test is determined according to the basic parameters of the PCB, the bending force is adjusted in real time according to the bending rate during the test, the test is stopped when the stress or the strain reaches a threshold value, the test data is analyzed to obtain the bending resistance grade of the PCB, and the PCB is divided into different grades by combining the thermal performance grade. According to the method, the efficiency and reliability of PCB testing are remarkably improved.

The invention relates to the technical field of state monitoring, in particular to an electric drive system overheating protection monitoring method and system based on big data, and the method comprises the following steps: obtaining a power rising section and extracting a temperature curve, judging whether the temperature rise lags behind or not, marking response delay, recognizing thermal fluctuation lag through an expansion window, and extracting peak valley to judge trend deviation. And the positioning node tracks the heat path, identifies the interrupt structure and generates an early warning identifier. In the electric drive system operation process, the coupling relation between the power change trend and the temperature rise time sequence is combined, accurate recognition of temperature rise response delay is achieved, the position distribution of a heat path interruption structure is defined through continuous tracing of the heat node temperature rise sequence relation, and linkage performance between heat interruption structures is combined, so that the reliability of the electric drive system is improved, and the reliability of the electric drive system is improved. Concurrent characteristics of overheating abnormity are identified, the response capability and early warning accuracy of an electric drive system in the early stage of overheating risks are improved, and rapid positioning of potential thermal fault risks and intelligent division of risk levels are achieved.