992 results about "Heat flux" patented technology

The invention relates to the technical field of data center heat dissipation, and particularly provides a single-phase and two-phase immersion liquid cooling method and system based on AI intelligent decision, and the method comprises the steps: injecting coupled data into a dynamic feature extraction engine, and outputting a thermodynamic state evolution tensor which comprises the characteristics of a temperature change rate, a load-heat flux density coupling coefficient and the like; the thermodynamic state evolution tensor is input into the deep neural network model, the temperature and pressure matched with the current thermodynamic state evolution tensor are calculated, and a closed-loop control instruction set capable of being executed by equipment is generated; a closed-loop control instruction set is injected into an execution mechanism set, execution mechanisms execute power reconstruction and flow channel switching according to instructions, gaseous fluorinated liquid is liquefied and flows back through an efficient condenser in a two-phase mode, and heat dissipation mode self-adaptive switching and heat cycle reconstruction are achieved. The system comprises a server, an AI algorithm controller, a cooling liquid storage device, a condenser, a circulating pump, an electric valve, a pressure release valve and a temperature sensor. The heat dissipation efficiency and the system reliability are remarkably improved.

The invention provides a fire early warning method and system based on three-dimensional modeling, and the method comprises the steps: determining the transaction indexes of fire danger at different space units through the spatial structure characteristics of a three-dimensional digital twin model in combination with the state evolution mode of a physical field, and determining a risk cloud picture through all transaction indexes; extracting a risk sub-domain of the fire according to the risk cloud picture, and further generating a heat flux density field matrix among different space units; determining risk fitting degrees of different space units by combining the heat flow diffusion information with the monitoring information of the fire behavior in the target building, and performing time sequence aggregation on the fire risk in the target building according to all the risk fitting degrees and the local temperature field of each space unit to obtain fire danger propagation potential energy; and performing fire diffusion situation monitoring on the target building according to the fire danger propagation potential energy, and outputting a fire diffusion early warning signal. By adopting the scheme of the invention, the diffusion track of the fire heat flow can be accurately identified in the three-dimensional model.

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 the technical field of material testing, and discloses a coating performance simulation method based on high and low temperature circulation and prestress loading. The method comprises the following steps: constructing a coating matrix composite geometric model containing a microporous structure by acquiring actually measured working condition data of a pipeline or a part, and quantifying surface roughness and interface curvature characteristics in combination with reverse engineering; a dynamic temperature-pressure coupling equation is generated based on the thermal expansion effect of a high-pressure medium, a micropore optical load is converted into equivalent heat flux density through a ray tracing algorithm, transient boundary conditions of a temperature field and a stress field are associated, a crack initiation path is simulated through an extended finite element method, and a life attenuation curve is predicted in combination with a Paris formula. And material parameters are dynamically corrected based on experimental data, and a multi-parameter collaborative optimization model is generated. According to the method, the problems of interface stress evaluation distortion and life prediction deviation under the combined load are solved, and multi-physics field co-simulation support is provided for coating compression resistance optimization.

The invention relates to the field of industrial automation and intelligent control, and discloses an intelligent temperature automatic control system for a digital glass mold. The method comprises the following steps: acquiring mold surface temperature and heat flow data through a thermocouple array and a thermal infrared imager, and constructing heat flux and a disturbance coefficient; forming state vectors are established in combination with the forming process parameters and the heat flow distribution, and forming stability levels are generated through support vector regression; building a heat balance deviation model based on the thermophysical parameters and the environment variables, and predicting a temperature trend; a temperature control instruction is generated through the fuzzy neural controller, and temperature dynamic closed-loop control is achieved. The system improves the temperature control precision and thermal field balance of the glass mold, and is suitable for intelligent temperature control management in the glass container forming process.

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 provides a north pole atmosphere coupling forecasting method capable of automatically fusing sea ice concentration and thickness, which belongs to the technical field of meteorology, and comprises the following steps: firstly, acquiring GFS background field data and correcting by applying an ice-sea heat exchange correction equation; and then sea ice concentration and thickness information is extracted, and physical consistency verification is carried out based on a thermodynamic equilibrium equation. Performing multi-element fusion through an Arctic ice sea assimilation model, calculating the sea ice surface temperature by applying a polar region sea ice heat flux equation, and establishing a sea ice concentration thickness boundary layer interaction equation set to describe the modulation effect of sea ice on a boundary layer; the method comprises the core steps of performing deep fusion on various sea ice features by applying a feature fusion model, adaptively adjusting the weight based on an ice-gas interface balance index, generating an optimized mode initial field and boundary conditions, and finally setting a parameter scheme to execute an integral program to obtain a forecasting result. The technical problem of low forecasting accuracy caused by insufficient physical consistency of sea ice information is solved.

The invention discloses a method for online reconstruction of a temperature field of a cutting area of a temperature measurement end mill. The method comprises the following steps: constructing a milling cutter three-dimensional model; establishing a milling heat conduction model; finite element analysis software is used for conducting heat conduction positive problem simulation under different heat flow densities; extracting a temperature value of each node and calculating a temperature sensitivity coefficient; acquiring a temperature data sequence at the temperature measurement position; establishing and training a heat conduction inverse problem algorithm model; acquiring real-time temperature data and predicting heat flux density through a temperature measurement module; and on-line reconstruction of the temperature field of the cutting area is realized in combination with the temperature sensitivity coefficient and the predicted heat flux density. The method can monitor the cutting temperature in real time, optimize the machining parameters, prolong the service life of the cutter and improve the machining precision.

The invention belongs to the technical field of hypersonic flight vehicle design, and discloses a design method for a thermal experiment model of a front body and an air inlet channel of a high-speed wind tunnel. The design verification method comprises the following steps: determining an overall structure and design requirements; determining a heating structure; determining a pressure measuring point and a temperature measuring point; determining an independent temperature control adjusting device; verifying the influence of the heat insulation groove on temperature gradient distribution; verifying the heat insulation effect of the heat insulation measures; model structure deformation generated by temperature is investigated; obtaining a heat flux density and surface temperature relation curve; the influence of model structure deformation on the flow field is studied. The design verification method proves that the precursor of the high-speed wind tunnel and the air inlet duct thermal experiment model have accurate temperature control and thermal insulation protection capabilities, and verifies the obvious influence of wall temperature change on the flow field structure; the aerodynamic thermal coupling effect can be effectively reproduced, a hypersonic air inlet heat-flow coupling experimental platform is established, and the experimental platform has engineering practical value.

The invention provides a multi-section collaborative dynamic adjustment temperature control system and method, and relates to the technical field of multi-section temperature adjusting.According to the multi-section collaborative dynamic adjustment temperature control system and method, division and data acquisition of a screw rod section, a barrel section and a machine head section are achieved through the thermodynamic state of materials of all sections, and after thermodynamic state data of all the sections are obtained, the temperature of the materials of all the sections is obtained; based on shear heat modeling of a compression section, heat source distribution and axial temperature change of a screw area are obtained, a two-dimensional heat conduction model of a barrel section is established, heat flux density in an axial partition structure is continuously solved, flow coupling calculation is further introduced into a machine head area, outlet temperature fluctuation characteristics are extracted, and a heat flow distribution model is established. And finally, by uniformly fusing the output parameters of each section, a dynamic thermal potential energy function is constructed, and the system can realize overall quantification and uniform expression of the thermal state of each temperature control section. The real-time responsiveness and the global heat balance level of the multi-section temperature control system are effectively improved.

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 provides a thermal behavior experiment system and method under a narrow rectangular channel reflooding cooling condition. The system comprises a heating water storage tank, a nitrogen tank, a steam tank, a shield pump, a preheating section, a first direct-current power supply, a second direct-current power supply, a narrow rectangular channel test section, a steam-water separator, a surge tank, a flow control valve, a silencer and an electromagnetic valve. The experimental working medium is deionized water, and re-submerging cooling experiments under different system pressures, working medium supercooling degrees, heating wall surface heat flux densities, working medium submerging speeds, heating wall surface initial temperatures and channel interior initial liquid levels can be carried out on an experimental section of a narrow rectangular channel structure. The device is suitable for narrow rectangular channel structures with different sizes, and can be used for carrying out re-submerging experiments on experiment sections with single-plate double-channel, double-plate three-channel and more channels. The system pressure and the inlet flow in the submerging process can be kept stable, and it can be ensured that the supercooling degree of a working medium, the heating wall surface temperature and the initial liquid level are controllable.

The invention discloses an electric arc additive manufacturing temperature field and stress field real-time reconstruction method, which comprises the following steps of: 1, constructing a sequential coupling finite element model in which heat conduction analysis and thermoelastic-plastic mechanical analysis are combined on the basis of process parameters of an electric arc additive manufacturing process and three-dimensional geometry of parts, generating a multi-physical field coupling data set among heat flux density, temperature and stress; step 2, constructing and training a neural network model based on a multi-physics field coupling data set, and realizing mapping from heat flux density to temperature and stress; 3, dynamically optimizing heat source model parameters in combination with real-time monitoring data and process parameters in the electric arc additive manufacturing process; and 4, based on the optimized heat source model parameters and the trained neural network model, real-time reconstruction of a temperature field and a stress field in the electric arc additive manufacturing process is achieved. According to the invention, the requirements of rapid sensing and intelligent regulation and control of temperature and stress states on an additive manufacturing site are met.

Provided in the present invention are a three-phase flow and heat transfer coupling simulation method and system based on an IBM-VOSET-DEM. The method comprises: determining a computational domain and dividing the grid of the computational domain; initializing parameters; reconstructing a liquid-liquid interface; determining a fluid volume fraction at an (n+1)th moment; determining a boundary grid, and determining a signed distance function of a grid cell at an nth moment; determining an interface curvature of the grid cell of the interface; smoothing abruptly changing physical quantities of the interface; determining the surface tension of the interface; determining a fluid intermediate velocity; obtaining fluid volume fractions and fluid intermediate velocities of all of the grid cells in the computational domain; determining the velocity of a particle; determining the displacement of a pth solid particle at the (n+1)th moment and a solid volume fraction of the grid cell at the (n+1)th moment; determining the final velocity of the computational domain at the (n+1)th moment; and solving for a temperature and an interface heat flux density. In the present invention, a DEM soft-sphere model is used to calculate a collision force of a solid, such that microscopic motion information of a solid particle can be accurately obtained and tracked; and an interface heat flux density model is used to take the conjugate heat transfer effect of an interface into consideration.

The invention relates to the technical field of thermotechnical measurement and signal processing, in particular to a multi-sensor linkage heat flux density-temperature real-time acquisition and error compensation method, which comprises the following steps: S1, constructing an embedded sensing array on a surface to be measured; s2, synchronously acquiring original measurement values of the sensors by taking 10ms as a period, and generating an original data matrix with a timestamp identifier; s3, extracting a three-dimensional temperature gradient field, and calculating to obtain a convective disturbance intensity coefficient of each measurement point; s4, establishing a dynamic error compensation model, and performing point-by-point error correction on the original data matrix; s5, cross validation is carried out, and credibility evaluation parameters are generated; and S6, carrying out weighted fusion, and outputting a final heat flux density-temperature coupling measurement value. According to the invention, through multi-sensor array cooperative acquisition, dynamic error compensation and credibility weighted fusion, high-precision, strong-anti-interference and high-credibility output of heat flux density and temperature measurement is realized.

The invention discloses an on-orbit spacecraft temperature prediction method and device based on a physical information neural network. The method comprises the following steps: S1, constructing an object model and an orbit heat source model according to a spacecraft to be predicted; s2, solving a space external heat flow of the orbit heat source model, and converting the space external heat flow into a volume heat flow of the object model; s3, constructing a physical information neural network; wherein a three-dimensional transient heat conduction equation is embedded in the physical information neural network; s4, designing a total loss function according to the volume heat flow and the physical information neural network; and S5, training the physical information neural network according to the total loss function to obtain a temperature prediction result of the spacecraft to be predicted. According to the method, the situation that model grids need to be divided in traditional finite element simulation is avoided, the calculation efficiency is improved, the calculation time is shortened, the temperature result can be predicted in real time, and the generalization ability and accuracy of the model are improved.

The invention discloses a hot-pressing control method and system for a flexible circuit board, and particularly relates to the technical field of flexible electronic manufacturing process control, and the method comprises the following steps: calculating a heat conduction equilibrium coefficient through collecting the temperature and heat flux density data of each region in the flexible circuit board, and achieving the real-time evaluation of a heat diffusion characteristic; in combination with an infrared scanning mode, acquiring reflectivity data, analyzing dynamic change of the reflectivity data along with time, and identifying an abnormal region in which coating residues possibly exist; further comparing the position relationship between the thermal diffusion anomaly and the infrared reflection anomaly, screening a space overlapping region as a high-risk point, and executing a preset regulation and control strategy; according to the method, the heat conduction equilibrium coefficient is calculated by collecting heat flow and temperature data, the coating residue abnormal area is recognized by combining infrared reflectivity time sequence characteristics, the high-risk area is screened based on the space overlap ratio for dynamic regulation and control, accurate recognition, differential control and closed-loop optimization of hot pressing defects are achieved, and the hot pressing quality and consistency are improved.

The invention provides an electromagnetic thermal multi-physical field simulation method based on an FDTD / FVTD algorithm, and belongs to the technical field of electromagnetic simulation. Performing time domain finite difference discretization on the established spatial discrete model by adopting a Yee cellular structure, and calculating electromagnetic field distribution according to a Maxwell rotation equation; constructing an adaptive steady-state judgment criterion based on the instantaneous total energy change rate, and updating electromagnetic field distribution of the spatial discrete model by adopting an FDTD explicit method; calculating the electromagnetic loss power density of the spatial discrete model, and transmitting the electromagnetic loss power density into a thermal field for calculation; based on an FVTD method, thermal field distribution of the discrete model is calculated through an explicit or implicit format, and thermal field distribution information is obtained. The FDTD method is based on explicit time domain iteration, transient behaviors such as electromagnetic wave propagation and scattering can be visually captured, and the FDTD method has broadband response capability and complex medium adaptability and is especially suitable for the high-frequency electromagnetic problem. The FVTD method strictly ensures energy conservation, directly treats boundary heat flux and is suitable for non-uniform materials and complex heat transfer boundary conditions.

The invention relates to the technical field of automatic control, in particular to an automatic control method and system for intelligent cooking equipment, and the method comprises the following steps: obtaining the liquid mass change and diffusion area based on a to-be-cooked food material, calculating the diffusion rate ratio, recognizing the structure type, calculating the fire power initial gradient, and generating the initial power; and constructing a composite expression quantity by combining a thermal expansion monitoring value, judging regional softening response information, identifying a heat flux gradient anomaly and marking an overheating trend, implementing offset stirring adjustment output, and generating dynamic regulation and control information. In the invention, based on food material structure feature information identification, classification number identification aiming at different structure types is realized, accurate matching of an initial control strategy is realized, fine control of heat energy supply at the initial stage of cooking is ensured, and the cooking efficiency is improved. Based on the thermal expansion coefficient, combined with the tissue compactness grade coefficient and the water activity change rate, composite calculation is carried out, and local over-cooking or under-cooking of food materials caused by insufficient expansion monitoring is avoided.

The invention discloses a flood lake wetland heat flux simulation method in a watershed hydrological model, and relates to the technical field of heat flux simulation, and the method comprises the following steps: dispersing a watershed space into a slope river channel and a lake wetland, simulating the water movement of a slope river channel unit, and simulating the water movement of the lake wetland; the method comprises the following steps: simulating surface energy exchange for a lake wetland unit on the basis of simulating a hydrological process, simulating land hydrology and lake inflow runoff of a sub-basin by adopting a grid-based distributed hydrological model, respectively dividing simulation grid units for a slope river channel and a lake wetland, establishing evapotranspiration, infiltration and surface runoff models, and establishing an evapotranspiration, infiltration and surface runoff model; a two-dimensional shallow water equation is used for processing slope confluence, a one-dimensional hydrodynamic model is used for calculating river channel confluence, a lake water quantity balance model is established for calculating the lake water level, the lake submerging process is simulated, and the lake wetland distributed heat flux process is simulated. And the technical blank of flooding wetland hydrothermal simulation is filled.

The invention provides an intelligent semiconductor chip and a thermal management method thereof, and the method comprises the steps: extracting the gradient features of the interlayer temperature of each semiconductor chip from the temperature information of each barrier layer of a three-dimensional stacked chip in a high-power-consumption module under a current working condition; constructing a temperature coupling field of the high-power-consumption module in the current working condition through each gradient feature and the heat dissipation feature of the packaging layer; a plurality of heat flux concentration areas of the high-power-consumption module in the current working condition are positioned based on the temperature coupling field and the specified sampling frequency, and thermal runaway risk points in the high-power-consumption module are screened out from all the heat flux concentration areas through peak characteristics in junction temperature information of all the heat flux concentration areas; and determining the vector distribution characteristics of the heat flux density in each thermal runaway risk point, and performing layered heat dissipation on the three-dimensional stacked chip in the high-power-consumption module through the vector distribution characteristics of the heat flux density in each thermal runaway risk point. Based on the scheme, thermal field reconstruction of dynamic thermal management in the three-dimensional stacked chip can be realized.

The invention provides a biological blood vessel bionic liquid cooling network heat dissipation method for a humanoid robot, and belongs to the technical field of robot heat dissipation. The biological blood vessel bionic liquid cooling network heat dissipation method for the humanoid robot comprises the following steps: carrying out embedded near-node heat dissipation with a driving source by utilizing a first heat dissipation unit according to the aorta-level local high-heat-flow heat dissipation requirement of a chip located at the brain of the humanoid robot through biological bionic mapping and global partition cascade thermal control; aiming at the high-dynamic multi-heat-source heat dissipation requirement of a joint motor located at a movable joint part of the humanoid robot, indirect heat dissipation with a driving source is carried out by utilizing a second heat dissipation unit; according to the capillary-level low-heat-flux heat dissipation requirement of a power battery located on the chest of the humanoid robot, self-driven indirect heat dissipation is conducted through the capillary pump effect by means of a third heat dissipation unit; and for vein-level liquid cooling backflow, large-area natural convection air cooling heat dissipation on the skin surface is simulated for global heat discharge, and finally the bionic liquid cooling heat dissipation method for the system-level humanoid robot is formed.

The invention discloses a new energy building integration energy-saving design analysis method, and relates to the technical field of new energy building integration, and the method comprises the following steps: carrying out the time sequence alignment and unit normalization processing of collected heat flow data, temperature rise data and power output data; according to the heat conduction characteristic of the heat conduction structure and the thermal inertia parameters of the building enclosure structure, a heat flux track and a thermal response profile with a unified thermal resistance reference axis are constructed; and based on the heat flux track and the thermal response profile, extracting a reverse heat flux strength parameter and a heat flux continuous influence duration parameter, and combining the parameters with a temperature control target and a heat conduction structure attribute set in the building to construct a reverse heat conduction interference atlas for judging the heat conduction interference degree of the cold load in the building. The problem of cold load misjudgment caused by the fact that photovoltaic heat is transmitted through a high-heat-conduction structure is solved, and cold and heat conduction accurate recognition and energy consumption dynamic regulation and control are achieved.

The invention relates to a physical-data dual-drive heat supply system heat demand prediction and optimization control method and system, and belongs to the technical field of intelligent regulation and control of regional energy systems. A multivariable time sequence is given, the forward LSTM and the backward LSTM respectively process the multivariable time sequence, and bidirectional hidden state splicing is output; constructing a decoder layer by using a multi-head self-attention mechanism, and parallelizing attention heads; the re-attention module dynamically adjusts attention distribution based on physical constraints derived from fluid thermodynamics, realizes deep learning to pay attention to related key physical parameters in a prediction process, and generates a physical vector P through heat flux Q and inertial delay tau; and fusing and outputting the predicted temperature of the secondary return water. According to the method, physical knowledge and depth sequential modeling are combined, prediction precision and physical interpretability are combined, and the interpretability, robustness and generalization of thermal dynamics of a heat supply system in an actual area are enhanced.

The invention discloses a vacuum brazing quality detection method for a heat dissipation structure and related equipment, and the method comprises the steps: obtaining heat flux density distribution data of the heat dissipation structure, and dividing the heat dissipation structure into different functional regions according to a thermal efficiency index; differential thermal pulses are applied to the heat dissipation structure in the vacuum brazing process, and thermal pulse response data and technological process monitoring data are obtained; calculating a thermal response characteristic parameter, comparing the thermal response characteristic parameter with a preset parameter range, identifying an abnormal state and generating a process adjustment instruction; performing time-space synchronization processing on the thermal response characteristic parameters and technological process monitoring data, and determining defect types, positions and severity; and performing a thermal load test to obtain heat conduction characteristic data, and quantitatively evaluating the structural integrity and the heat conduction performance of the brazed joint surface. According to the method, the defects of the internal joint surface can be detected in real time in the vacuum brazing process, the heat dissipation performance is accurately evaluated, and the limitation of a traditional detection method in coping with a complex geometric structure is solved.

The invention provides a sensor-based seasonal frozen soil monitoring method and system, and the method comprises the steps: dividing a monitored region into grids, deploying a sensor group in the monitored region, obtaining the geographic parameters of the monitored region, and obtaining the terrain impact factors of seasonal frozen soil according to the geographic parameters; acquiring heat flux between two points of the sensor monitoring point i and the sensor monitoring point j in the monitored area; calculating a final weight matrix, and calculating spatial autocorrelation among the sensor monitoring points based on the terrain influence factors, the heat flux and the final weight matrix; unnecessary monitoring points are screened out according to spatial autocorrelation, the monitoring points are sequenced according to spatial autocorrelation values, the monitoring points with larger absolute values are sequenced in the front, and the monitoring points with higher sequencing are preferentially monitored. According to the method and the corresponding system, redundant monitoring points in seasonal frozen soil monitoring are screened, so that the deployment number and the maintenance cost of the sensors can be reduced, and the operation cost of the whole monitoring system is reduced.

The invention discloses an infrared inspection equipment transformer energy efficiency grade determination method based on deep learning. The method comprises the following steps: 1, collecting data and synchronizing the data; 2, preprocessing the original infrared image; 3, constructing a steady-state heat conduction model, and generating a simulated heat flux diagram; 4, constructing a response function, and performing position alignment through affine transformation to obtain a registration image pair; 5, generating an infrared characteristic tensor and a heat flux characteristic tensor; step 6, generating a heat loss offset feature map; 7, inputting the heat loss offset feature map into an improved SAM Adapter model, and introducing a guide type structure perception mechanism to generate a heat dissipation anomaly representation tensor; and 8, inputting the heat dissipation abnormity representation tensor into the classifier, and obtaining an energy efficiency grade determination result of the transformer. According to the method, steady-state heat conduction modeling and the improved SAM Adapter model are fused, and intelligent judgment of the energy efficiency level of the transformer is achieved.

The present application relates to a semiconductor temperature control device and a control method thereof. The device includes: a temperature detection module, which is used to perform multi-point detection on the temperature field of a semiconductor laser to obtain multiple temperature measurement values, so as to perform thermal field simulation calculation on the temperature distribution of the semiconductor laser to obtain a temperature field distribution matrix; a heat flow analysis module, which is used to perform heat flux density calculation on the semiconductor laser according to the temperature field distribution matrix to obtain the heat flux density distribution, so as to perform multi-channel pulse width modulation processing on the thermoelectric refrigeration component to obtain a temperature regulation drive signal; a closed-loop control module, which is used to perform adaptive regulation processing on the thermoelectric refrigeration component according to the temperature regulation drive signal to generate a temperature regulation feedback signal, so as to perform closed-loop adjustment on the drive current of the thermoelectric refrigeration component until the thermoelectric refrigeration component maintains the temperature of the semiconductor laser within the target temperature range based on the adjusted drive current. The use of the device can ensure the dynamic balance of temperature regulation.

The invention discloses a liquid hydrogen container heat leakage prediction and boost characteristic detection method and system. The method comprises the following steps: establishing a three-dimensional heat flow field model of a liquid hydrogen container; calculating the heat flow density of a gas-liquid interface based on the three-dimensional heat flow field model so as to adjust the liquid hydrogen evaporation capacity; total heat leakage is obtained through finite element simulation and experimental data collaborative calibration; calculating a static evaporation rate according to the total heat leakage; establishing a nonlinear mapping model of the static evaporation rate and the boost rate through a response surface regression method; the wall temperature distribution of the liquid hydrogen container is monitored in real time, thermophysical parameters are calibrated through the LSTM neural network by adopting a dynamic calibration algorithm, and the output result of the three-dimensional heat flow field model is corrected. By establishing a three-dimensional heat flow field model of the liquid hydrogen container, determining a nonlinear response relationship between the evaporation rate and the pressure rising rate of the liquid hydrogen container, and constructing a cloud-edge collaborative detection system, the heat leakage performance of the liquid hydrogen container is accurately predicted, and efficient pressure rising rate detection is realized.

The present application provides a dynamics analysis method for an ammonia combustion refrigeration system in large park cooling. The method comprises: on the basis of a geometric structure of an ammonia combustion chamber and a fuel supply amount, calculating the heat generated by ammonia combustion and analyzing the heat transfer mode between the combustion chamber and a desorption tower, the heat transfer mode comprising direct contact type heat transfer and partition type heat transfer, and simulating the heat transfer process to obtain and draw the heat flux distribution of the tower wall surface; on the basis of the flow state and a relationship curve between the pressure drop and the flow velocity, analyzing the desorption process of a refrigerant in a solution, and on the basis of the concentration of the solution, a boiling point of the refrigerant, and the vapor pressure, calculating local desorption rates at different positions in the desorption tower and the refrigerant vapor generation amount; and on the basis of the heat flux distribution, calculating the temperature distribution of the solution, and analyzing the heat transfer and mass transfer processes in the desorption tower to obtain a local heat transfer coefficient and the mass transfer efficiency distribution of the surface of a filler.