3906 results about "Thermal conduction" patented technology

The invention discloses a directional detection method and system for a power supply shell based on a multi-source heterogeneous sensor, belongs to the field of material characteristic detection, and aims to solve the problems of single dimension, weak anti-interference performance, data isomerism and poor adaptability in traditional industrial detection. Through systematic innovation of multi-source sensor collaboration, dynamic mode control, cross-modal data fusion and self-learning optimization, a high-precision, high-efficiency and high-reliability solution is provided for the precision manufacturing field, and an optical, infrared and ultrasonic multi-modal collaborative detection framework is constructed; the optical unit realizes accurate capture of surface texture and morphology through polarized light imaging and 3D structured light scanning, the infrared thermal imaging unit analyzes the heat conduction characteristic of a material, and the ultrasonic array analyzes internal structure defects to form a surface-material-internal full-dimension detection capability; and nine types of defects such as scratches, pits, weld marks, bubbles, sink marks, material layering, stress cracking, thermal stress abnormity and material pollution are covered.

The invention provides a color steel plate coating thickness dynamic monitoring method and system based on artificial intelligence. According to the method, the temperature distribution data of the surface of the color steel plate coating is obtained, the thermal response map is generated in a pulsed eddy current excitation mode, then the temperature distribution data and the thermal response map are subjected to time sequence correlation processing, the heat conduction characteristics are extracted, and then the heat conduction characteristics are synchronously analyzed; color steel plate coating defect types and thickness abnormal grades are distinguished through a dynamic weight distribution mechanism, a detection result containing defect positions, sizes and thickness deviation values is generated, and finally a coating thickness dynamic compensation instruction is generated according to the detection result; according to the technical scheme provided by the invention, the online control precision and the production efficiency of the coating quality are remarkably improved, and a closed-loop feedback system from detection to control is formed.

The embodiment of the invention discloses an outer wall thermal insulation defect diagnosis method and system based on artificial intelligence, and the method comprises the steps: firstly obtaining an infrared thermal imaging and visible light image sequence of a target building outer wall, the former comprising continuous temperature distribution data, and the latter comprising textural feature data in time-space alignment with the latter; performing dynamic temperature gradient analysis on the infrared thermal imaging image sequence to generate a three-dimensional heat conduction abnormal map, extracting surface deformation characteristics from the visible light image sequence to generate a structure deformation distribution map, and performing multi-modal characteristic fusion on the two to obtain a joint defect characteristic matrix; performing defect type classification and region positioning on the matrix based on a pre-trained deep residual neural network model, outputting a defect type identifier and a corresponding region boundary coordinate, and finally generating a diagnosis report containing a repair priority score and a material matching suggestion according to the defect type identifier and the corresponding region boundary coordinate, and sending the diagnosis report to a user terminal for visual display. And efficient and accurate external wall thermal insulation defect diagnosis is realized.

The invention provides a multi-source biological signal fusion moxibustion electric control method and system. In the moxibustion applying process, a multi-source biological signal flow is formed by obtaining an epidermal impedance dynamic waveform and a heart rate variability signal, a skin impedance baseline map of a physiological feature parameter library and a heart rate variability association rule are dynamically matched, and an acupoint sensitivity index and a heat tolerance threshold value are generated; triggering an infrared thermal imaging device to scan a moxibustion application area based on the sensitivity index, reconstructing a heat conduction model in combination with the epidermal layer thickness and the acupoint distribution density, comparing an epidermal impedance dynamic waveform with a skin impedance baseline map through a phase offset, and calculating a targeted thermal field compensation gradient of the acupoint area; and finally, coupling the thermal tolerance threshold and the space-time parameters of the target thermal field compensation gradient to generate a control instruction set. According to the technical scheme, accurate regulation and control of thermal field distribution and optimization of the motion path of the mechanical arm in the moxibustion applying process are achieved.

The invention discloses a pepper freezing temperature gradient dynamic adjusting method and system, particularly relates to the technical field of industrial freezing temperature control, and is used for solving the problem of temperature gradient misalignment caused by the fact that a static model does not sense dynamic changes of material thermodynamic parameters in real time in an existing freezing control method. Temperature distribution and gas flow rate data in the freezing process are collected in real time, a high-confidence-coefficient data subset of a low-flow-rate area is screened based on spatial correlation, the dynamic heat conduction coefficient of the material is identified online through a recursive algorithm, and the dynamic heat conduction coefficient of the material is identified through a double-threshold-value judgment mechanism of the energy release rate and the phase lag angle. Performing segmentation fitting to generate a stable parameter sequence; further dynamically adjusting a preset temperature gradient model through a nonlinear correction strategy to generate a self-adaptive gradient control curve, and finally driving heat exchange rate adjustment to realize closed-loop tracking of the actual temperature gradient on a target curve; the freezing uniformity and energy efficiency of the high-moisture material are remarkably improved, and the control precision caused by thermal response mismatch is improved.

The invention relates to the technical field of mode recognition, in particular to a transformer substation equipment temperature measurement method and system based on visible light guidance. Firstly, a visible light image, an infrared thermogram and vibration spectrum data are synchronously collected, a dynamic compensation coefficient matrix is constructed through illumination intensity analysis, the dynamic compensation coefficient matrix is applied to the infrared thermogram, and illumination interference compensation is achieved. And then, inputting the corrected infrared thermogram and visible light image into a pre-trained heterogeneous atlas matching model, and identifying the category and three-dimensional coordinates of the target equipment. And based on the equipment category information, calling a standard temperature field template in the digital twin model library, establishing a heat conduction path model in combination with the vibration spectrum data, and generating a temperature field prediction reference map of the equipment. And finally, through pixel-by-pixel deviation analysis, inputting the temperature deviation value, the image features and the vibration data into the probability graphic model, and outputting equipment fault information. The method can realize high-precision temperature measurement and fault diagnosis.

The invention discloses a digital intelligent management method and system for hydraulic engineering construction, particularly relates to the technical field of hydraulic engineering construction management, and is used for solving the problems of regulation lag and insufficient environmental disturbance adaptability of an existing method under the action of multi-physics field coupling. According to the method, a concrete three-dimensional temperature field model is established, initial regulation and control parameters are generated, and a heat conductivity coefficient under the seepage influence is corrected based on space-time relevance of pore water pressure and temperature data; the constraint boundary is dynamically adjusted in combination with the construction progress and the material strength curve, a cooling water pipe coordinated regulation and control matrix is constructed, and target flow instructions of space differentiation are generated through the included angle between the distance and the water flow direction; setting a lag time threshold and optimizing an execution time sequence according to the thermal inertia parameter, splitting the threshold and allocating a weight coefficient when the environmental wind speed suddenly changes, and finally updating the model parameter and the regulation and control instruction; accurate temperature control response and abnormal heat conduction suppression under multi-field coupling are achieved, and the structural safety and construction efficiency under complex working conditions are improved.

The invention discloses a temperature measurement precision optimization method based on multiple sensors, and belongs to the technical field of temperature measurement, and the method specifically comprises the steps: deploying a temperature monitoring array which comprises a fixed position basic sensor group and a position adjustable auxiliary sensor group; scanning the target area through an infrared thermal imaging device to generate a thermal field temperature gradient distribution map; identifying a high dynamic change region boundary based on the thermal field temperature gradient distribution map, and extracting geometric feature parameters of the boundary; constructing a heat flow propagation prediction model according to the boundary geometric feature parameters, and calculating a key monitoring node space coordinate set on a heat conduction path; generating a sensor deployment instruction according to the key monitoring node space coordinate set, and dynamically scheduling an auxiliary sensor group to move to a target position; fusing the temperature data streams of the basic sensor group and the auxiliary sensor group, and executing space-time calibration calculation to generate an optimized temperature field distribution diagram; according to the invention, the coverage integrity and the result accuracy of temperature measurement in a dynamic scene are improved.

The invention relates to the technical field of process parameter design, and discloses a silver electrolysis process parameter design method and system based on multi-objective optimization. The method comprises the following steps: performing differential time sequence parameter decomposition on operation data of the silver electrolysis process to obtain a sensitive parameter set and a reference parameter set; performing reweighted periodic feature extraction on the sensitive parameter set and the reference parameter set, and establishing a dynamic mathematical model of the silver electrolysis process parameters; based on the dynamic mathematical model of the silver electrolysis process parameters, physical and chemical process numerical simulation is conducted through COMSOLMultiphysics software, and a response curved surface model is obtained; and according to the response curved surface model, a process parameter combination evaluation value sequence is generated, silver electrolysis process parameter multi-objective optimization is carried out based on the process parameter combination evaluation value sequence, and a silver electrolysis process parameter optimization scheme is output. According to the application, multi-physical-field collaborative simulation of electrode reaction, ion transmission, heat conduction and the like is realized, and performance index responses under different process parameters are accurately predicted.

The invention relates to the technical field of intelligent control, in particular to a composite material forming process intelligent control system which comprises a micro-scale deformation detection module, a stress offset correction module, a temperature gradient regulation and control module, an interlayer curing balance module and a forming intelligent control execution module. According to the method, a deformation rate sudden change area is accurately positioned through micro-scale detection, and stress concentration is found in advance, so that stress adjustment is more targeted, the local stress overload influence is reduced, real-time pressure feedback is combined with target pressure offset analysis to optimize a loading mode, uniform stress in the curing process is ensured, and the defect risk is reduced; high-precision temperature gradient monitoring and thermal diffusion rate analysis improve temperature control precision and improve interlayer temperature equilibrium, curing rate change rate calculation and heat conduction path optimization dynamically adjust a heat dissipation channel and promote uniform curing, stress-temperature distribution equilibrium degree analysis is combined with a deformation trend to optimize heating and pressure parameters, and uniform curing is achieved. And the forming stability and the quality consistency are improved.

The invention discloses a hydration heat monitoring and dynamic regulation and control method and system in a mass concrete pouring process, and relates to the technical field of concrete pouring, and the method comprises the steps: pre-burying a plurality of dual-mode temperature measurement probes in concrete, collecting dual-mode temperature field data in the concrete in real time, and synchronously collecting environmental parameters; carrying out preprocessing, dynamic weight distribution and data fusion on the obtained dual-mode temperature field data; according to the unsteady state heat transfer equation and the hydration heat model, a finite element heat conduction model is constructed, and the total hydration heat and the temperature difference trend are inverted through actually measured temperature field data; predicting a concrete core and surface temperature difference and a surface and environment temperature difference in a future set time period by combining an LSTM neural network model; and according to the predicted temperature difference result, the cooling water flow rate and the cooling water temperature are subjected to closed-loop regulation. Through the combination of dual-mode sensor temperature measurement and heat inversion, the hydration heat temperature difference in the concrete can be predicted in advance, a cooling scheme is regulated and controlled in real time in a linkage mode, and temperature stress cracks are avoided.

The invention provides a power management chip pin state intelligent detection method and system. The method comprises the steps that temperature difference quantity is input into a gradient heat conduction compensation structure, and compensation current opposite to a temperature gradient vector is generated based on temperature field distribution in the copper-based composite material; superposing and coupling the voltage fluctuation signal and the compensation current to generate a reference voltage signal; performing frequency component separation processing on the reference voltage signal, and extracting electromagnetic interference characteristic data in a frequency component; performing time sequence correlation on the electromagnetic interference characteristic data and the temperature distribution data, dynamically adjusting an interference suppression parameter through closed-loop control, and acting the adjusted interference suppression parameter on an interference suppression process of a reference voltage signal to generate a pin state detection signal; and detecting the pin state of the power management chip according to the pin state detection signal. According to the invention, the pin voltage stability and the state detection precision of the power management chip are improved.

The invention relates to the technical field of automatic detection, in particular to a multi-station PCBA (printed circuit board assembly) detection method based on machine vision, which comprises the following steps: acquiring a multi-station reference pulse period, dividing a time window, comparing starting time difference, controlling image acquisition to synchronize, locally imaging a PCBA based on a synchronizing signal, extracting temperature response of a welding spot, and constructing a heat conduction path. Mapping to a visible light image, evaluating welding spot symmetry, extracting welding spot hue change, marking abnormal frames, recording defect path nodes, and generating a defect path structure. According to the method, the temperature response coordinate points in the welding spot area are extracted and the heat conduction direction vector path is constructed, so that the welding quality is evaluated more carefully and accurately, the thermal grid chart is mapped to the visible light image frame, the image analysis process is further optimized, the defect detection accuracy is enhanced, and the potential defect area is effectively identified; the efficiency and reliability of PCBA board detection are significantly improved, and powerful technical support is provided for high-quality production.

The invention provides a performance optimization and regulation method for a high-temperature sintering furnace, and belongs to the technical field of intelligent regulation, and the performance optimization and regulation method comprises the following steps: arranging sensors in each heating area of the high-temperature sintering furnace, and monitoring the heating areas in real time; constructing a heating area operation state database, comparing the collected real-time data with a preset sintering process parameter range, and analyzing to obtain a performance analysis set of each heating area; establishing a three-dimensional heat conduction model, simulating heat flow distribution of each heating area under different heating powers and temperature settings, determining a thermal coupling effect of each heating area in different stages, and determining a heat transfer coefficient between adjacent heating areas; and an initial strategy of the high-temperature sintering furnace is determined, the initial strategy is optimized based on the auxiliary parameters of all the heating areas, and all the heating areas of the high-temperature sintering furnace are regulated and controlled according to the optimization strategy. The problems of inaccurate temperature control, single parameter analysis, insufficient thermal coupling effect processing and the like in the traditional regulation and control technology are effectively solved.

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 electronic packaging, in particular to a welding process applied to a double-mesa device. The technology comprises the following steps that firstly, a heat conduction model of a double-table-board device is built, a temperature field prediction system is built in combination with measured data, secondly, an asymmetric double-pulse-current welding strategy is adopted, differential pulse waveforms are loaded to an upper table board and a lower table board respectively, independent temperature control over all welding areas is achieved, a temperature difference closed-loop feedback mechanism is introduced in the process, and the temperature field prediction system is obtained. Pulse parameters are dynamically adjusted according to real-time temperature deviation, a stress prediction and weld penetration monitoring module is used for assistance, the welding spot forming quality and heat stress balanced release are ensured, a staged annealing type cooling mode is adopted after welding, and the structural stability is improved. The method can be widely applied to MEMS modules, SiC power devices and heterogeneous chip laminated packaging double-mesa structure devices, and has the advantages of being high in welding precision, high in reliability and wide in process adaptability.

The invention relates to a tin ring automatic focusing laser soldering tin fixing and 3D welding spot detecting system, and belongs to the technical field of industrial automatic laser processing. The system is characterized in that a tin ring preparation module identifies pins in real time and dynamically optimizes winding parameters through visual positioning and a self-adaptive winding head, and performs defect identification and pre-repair analysis through multispectral imaging; the soldering tin positioning module is used for switching stations through a rotary table, and precise positioning and clamping of a product are realized by combining laser contour sensing and a focusing compensation algorithm; the laser tin soldering module can visually identify tin materials and automatically call welding parameters, laser power and action time are regulated and controlled in real time by establishing a regional heat conduction model, and gradient cooling is implemented after welding; and the 3D detection module adopts dual-mode scanning, constructs a welding spot three-dimensional model based on fusion data, recognizes microcracks through super-resolution processing, and discriminates the welding spot quality. And automation and intellectualization of the whole process from tin ring preparation to welding spot quality detection are achieved.

The invention relates to the technical field of arc discharge control, in particular to an arc discharge machine control method based on multi-parameter collaborative optimization, which comprises the following steps of: generating a first regulation and control instruction by adopting a fuzzy PID (Proportion Integration Differentiation) algorithm based on a deviation value between a dynamic parameter feedback signal and a preset threshold value, the axial feeding speed of the servo motor, the power output curve of the arc generator and the coolant spraying time sequence are synchronously adjusted, so that the arc energy density gradient and the workpiece heat conduction rate form dynamic balance, the mechanical resonance frequency in the machining process is monitored through the vibration spectrum analysis unit, and when it is detected that the resonance intensity exceeds a safety threshold value, the coolant spraying time sequence is started. And a second regulation and control instruction is generated by triggering a frequency compensation algorithm, and the driving frequency of the servo motor is corrected in real time, so that the control precision is improved, the arc discharge process is more stable, the response speed is increased, the arc discharge time is shortened, the adaptability is enhanced, the requirements of different materials and processes can be met, the energy consumption is reduced, and the production efficiency is improved.

The invention provides a method and equipment for predicting the heat exchange performance of a buried pipe ground source heat pump thermal camouflage system. The method comprises the steps that S1, a multi-physics field coupling heat exchange mathematical model of a buried pipe heat exchange system is established; s2, based on the multi-physics field coupling heat exchange mathematical model, a control equation and boundary conditions are constructed; s3, on the basis of the control equation and the boundary conditions, a multi-physics field numerical model is constructed, and simulation and calibration are carried out; and S4, based on the calibrated numerical model, designing a simulation test and carrying out main control factor analysis to obtain a prediction effect of the heat exchange performance. By establishing a rock-soil body-fluid multi-physical field coupling model, the interaction mechanism of underground heat conduction, working medium flow and ground surface heat radiation is completely represented, and the hiding efficiency of the thermal camouflage system is remarkably improved.

The invention relates to the technical field of transformers, and provides a transformer load capacity prediction method and device, equipment and a storage medium, and the method comprises the steps: obtaining current data, winding temperature data, oil temperature data, environment temperature data and historical load records of a target transformer; calculating a temperature rise correction value based on the winding temperature data and the oil temperature data; after the temperature rise change rate in unit time is calculated through the current data, the environment temperature data and the temperature rise correction value, time sequence matching analysis is carried out on the temperature rise change rate and historical load records, after the load capacity change trend is obtained, comparative analysis is carried out on the load capacity change trend and the historical load records, and a load capacity prediction result is generated. By utilizing collaborative analysis and heat conduction characteristic calculation of multi-source data and comprehensively constructing a time delay interval and a load capacity evaluation method, the precision and applicability of transformer load capacity prediction are improved, and the problem that the prediction precision is insufficient due to the fact that operation data and environment data of the transformer cannot be fully fused during multi-source data processing is solved.

The invention discloses an energy-saving control method based on a building group spatial form, which relates to the technical field of energy-saving control, and comprises the following steps: constructing an airflow track analysis region based on a region with hot pressure difference direction change in a spatial pressure covering sensing matrix, and collecting continuous wind direction and wind speed data; judging whether the airflow direction is abnormal or not according to the change of the flow direction consistency entropy; performing spatial coincidence processing on the spatial pressure shielding sensing matrix and the airflow direction abnormal region, and generating an air outlet ventilation and heat extraction efficiency evaluation index based on the heat conduction rate in the coincidence region and the stability of an airflow output path; and on the basis of the ventilation and heat removal efficiency evaluation index of the exhaust outlet, an exhaust response condition matrix containing a space pressure shielding parameter, an airflow disturbance level and a heat retention level is constructed, and a ventilation control judgment sequence is generated. According to the method, the problem of air exhaust failure under pressure shielding interference is solved, ventilation efficiency accurate judgment and energy-saving regulation and control optimization are achieved, and the ventilation stability and the energy utilization efficiency of the building group are guaranteed.

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 relates to the technical field of control and adjustment, in particular to a steam turbine fault diagnosis system based on multi-parameter fusion monitoring, which is characterized in that a quantum hybrid sensing module is used for establishing a picosecond-level space-time reference through entangled photon pair distribution, and unifying a time sequence label of multi-source heterogeneous data; the hypergraph feature extraction module loads the coefficient to a vibration measurement point vertex attribute channel, dynamically calculates a heat conduction hyperedge weight according to a rotor eccentricity inversion value, aggregates temperature field, vibration spectrum and magnetic domain features in a space-time hypergraph which retains physical topology, outputs a cross-scale aligned fusion feature tensor, and outputs a vibration measurement point vertex attribute channel; generating a diagnosis feature vector to drive a multi-scale twin experience certificate; and the federation decision module triggers a load reduction instruction according to the microscopic crack cloud picture to inhibit thermal stress sudden change, and meanwhile, the feature representation precision is improved through cloud federation optimization hyperedge weight parameters. According to the method, the problem of characterization distortion caused by time sequence asynchronization and scale mismatch of heat and machine coupling data is solved.

The invention provides an electric energy metering box temperature field simulation analysis method based on finite elements, and relates to the technical field of electrical equipment fault diagnosis. The method comprises the following steps: constructing a three-dimensional structure model considering asymmetric layout and material attributes of internal elements; identifying key heating elements and establishing a dynamic heat source; constructing an unsteady state heat conduction model by combining a Fourier law and an energy conservation equation; setting environment related boundary conditions; and outputting a temperature distribution diagram and an abnormal hot spot early warning result, thereby realizing accurate modeling and risk pre-judgment of the thermal behavior of the electric energy metering box.

The invention discloses a numerical simulation-based roadway surrounding rock deformation monitoring method and device. The method comprises the following steps of: constructing a three-dimensional geologic model of a roadway area; based on the three-dimensional geologic model, establishing a numerical model of heat conduction, stress action and seepage multi-physics field coupling, and based on elastic-plastic characteristics of rocks in the roadway area, simulating simulation data of surrounding rocks in the roadway area under the multi-physics field action by the numerical model; acquiring real-time monitoring data of various types of sensors arranged in a risk monitoring area of surrounding rock deformation corresponding to the simulation data; denoising, filtering and abnormal value processing are carried out on the real-time monitoring data, and then multi-source data fusion is carried out to calibrate the numerical model; and predicting the deformation trend of the surrounding rock based on the calibrated target numerical model and the real-time monitoring data. Therefore, by means of geological modeling, numerical model simulation, sensor arrangement optimization, numerical model optimization and surrounding rock deformation trend prediction, roadway surrounding rock monitoring precision is improved, and safe operation of a roadway is guaranteed.

The invention discloses a poultry behavior abnormity real-time monitoring system based on multi-modal image fusion, particularly relates to the technical field of intelligent breeding behavior recognition, and is used for solving the problem of poor behavior monitoring accuracy under feather shielding. The method comprises the following steps: firstly, through combined perception of a visible light image and an infrared image, extracting a claw track interruption point and an anus temperature gradient direction, and realizing analysis of a motion state of a sheltered area; then, in combination with the heat conduction delay characteristic and the group movement direction, the flexion and extension angle of the covered leg joint is inverted, and a complete gait sequence is generated; thirdly, multi-source features such as gaits, temperature differences and body postures are fused, and a dynamic deviation model of the individuals relative to the mass center of the group is constructed; and finally, generating a stress behavior threshold curve according to the ground temperature and the ammonia gas concentration, outputting an abnormal behavior type and confidence, and realizing intelligent distinguishing of mechanical obstacles and adaptive behaviors.

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 relates to the technical field of automobile cup holder temperature control methods, and discloses an automobile cup holder temperature regulation control method based on a microcontroller. According to the method, real-time temperature data and environment parameters of a target container are collected, and an initial temperature parameter set containing a container surface temperature distribution curve and an environment heat exchange coefficient sequence is generated; then, establishing a first adjusting model containing a mapping relation between surface temperature change and refrigeration power according to the container surface temperature distribution curve, and establishing a second adjusting model containing environment heat interference and a heating power compensation rule according to the environment heat exchange coefficient sequence; during cup stand temperature control, based on real-time temperature difference fluctuation and container material heat conduction characteristic data, a target model is activated to generate a dynamic power instruction, finally, the instruction is input into a semiconductor temperature control unit of the cup stand, and the current gradient of a refrigeration sheet or the voltage distribution of a heating film is adjusted. The temperature of the automobile cup holder can be accurately and intelligently adjusted, and the user experience and the comfort level of an automobile cabin are improved.

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 deep resource fluidized mining disturbance effect evaluation model under a multi-field coupling effect, and the method specifically comprises the following steps: constructing a multi-field coupling parameter system: collecting geologic body basic parameters, covering rock mass mechanical parameters, thermal physical parameters, fluid parameters and chemical parameters in deep three-high, high ground stress, high ground temperature and high karst water pressure environments, and establishing a multi-field coupling parameter system; the method comprises the following steps: establishing a dynamic parameter database, realizing real-time updating of parameters along with a mining process, establishing a heat-flow-force-chemical full-coupling mathematical model, introducing the influence of a rock plastic damage correction term quantification temperature on heat conduction efficiency, associating a dynamic mapping relation between mineral reaction and rock physical property parameters, and establishing a dynamic parameter database. Simplification errors of a traditional model on multi-field effects are thoroughly eliminated, chained interaction of temperature, fluid, stress and chemical processes in a deep three-high environment is accurately described, a model prediction result better fits an actual mining working condition, and prediction deviation is greatly reduced.