4422 results about "Heat flow" 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 discloses an aircraft surface flow field intelligent reconstruction method and system based on multi-source data fusion, and belongs to the technical field of flow field intelligent prediction. Acquiring multi-source sensor data on the surface of the aircraft, and constructing a multi-source data set; a flow field reconstruction model based on Transform is constructed; a multi-source data set is adopted to train a flow field reconstruction model; and outputting an aircraft surface flow field reconstruction result based on the trained flow field reconstruction model, and visually displaying the aircraft surface flow field reconstruction result. Based on the strong nonlinear mapping capability of the deep learning model, through training of a large amount of sensor data, high-order correlation characteristics among pressure, heat flow and friction resistance stress can be automatically extracted, through fusion of sparse discrete data, a continuous physical field of the whole surface of the aircraft can be effectively reconstructed, and the method is suitable for the aircraft. The limitation of a traditional analytical model in dealing with a strong nonlinear problem is broken through, and the precision and reliability of aircraft flow field prediction are improved.

The invention discloses a temperature control system and method for a hot runner of an injection molding machine mold, and the method comprises the steps that the temperature control system collects the temperature data of each region of the hot runner in real time through a temperature sensor, and carries out the adjustment according to the data feedback; a built-in self-adaptive algorithm automatically adjusts a temperature control strategy according to different injection molding materials and production requirements, such as temperature upper limit, temperature lower limit and heating and cooling opportunities, and the production efficiency is optimized; when the system recognizes temperature fluctuation, a heating mode or a cooling mode is automatically switched, and the cooling system is dynamically adjusted for temperature balance; a plurality of temperature sensors are arranged in a key area of the mold for regional monitoring, and temperature control output is adjusted in real time; meanwhile, an embedded learning algorithm gradually optimizes a temperature control strategy according to historical production data, adjusts control parameters, and improves the production precision and efficiency. According to the temperature control system and the temperature control method for the mold hot runner of the injection molding machine, the problems of low temperature control precision, poor energy efficiency and slow response in the prior art are solved, and efficient and intelligent temperature control capability is provided.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

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 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 relates to the technical field of active testing of circuit breakers, discloses an active testing method and system for a circuit breaker, and is used for solving the problem that an existing active testing method is difficult to realize self-adaptive adjustment of a threshold value. Time-frequency analysis is carried out on the contact speed signal to extract time domain and frequency domain features, and heat flow analysis of the thermopile array is combined to obtain a heat engine coupling feature vector; a thermo-electro-mechanical coupling dynamic graph with the sensors and the components as nodes and the reciprocal of thermal conductance as the edge weight is constructed, the structure is updated in real time, and node drift is predicted through a graph convolutional network; fusing the environment derating and the predicted drift amount to adaptively adjust a threshold value; extracting a thermoelectric coupling component of a contact speed fast change component and a heat flow refraction angle change rate, and generating a reversed polarity pulse compensation signal to suppress interference; time synchronization, closed-loop feedback of data and threshold adjustment results are realized through secondary alignment of IEEE1588 and the cloud, graph model node weight and threshold rules are dynamically updated, synchronization with equipment health degree is ensured, and accurate early warning and protection are realized.

The invention discloses a cold plate-immersion liquid cooling cooperative heat dissipation method based on steam zone coupling modeling, and relates to the technical field of cooperative heat dissipation. Comprising the following steps of S1, collecting collaborative heat dissipation monitoring data of each key position in real time, and performing data preprocessing; s2, the comprehensive risk of the steam area is judged, and a risk cooling adjustment instruction is issued according to the comprehensive risk judgment result; s3, receiving a risk cooling adjustment instruction, carrying out collaborative heat dissipation, evaluating the collaborative heat dissipation capability, adjusting the rotating speed of a circulating pump and the opening degree of a valve, and requesting condensation backflow adjustment; s4, judging the adjusting quantity of condensation reflux, executing reflux adjustment and performing safety monitoring; and S5, continuously monitoring the data of each link, and carrying out anomaly detection on the state of each link to realize anomaly regulation and control. The problems that in an existing single-phase cold plate or two-phase immersion liquid cooling mode, steam accumulation is prone to occurring in a high-heat-flow scene, so that the pressure intensity is increased, the boiling point is increased, and the heat exchange efficiency is reduced, and then the operation reliability of equipment is affected are solved.

The invention relates to the technical field of industrial process intelligent monitoring, and provides a digital twinning-based gas pressure regulation self-regulation intelligent monitoring system, which comprises a data acquisition unit, a digital twinning unit and an execution and feedback unit. The data acquisition unit acquires operation data of the gas pressure regulating equipment in real time, and the operation data are preprocessed and then transmitted to the digital twinning unit. The digital twinning unit constructs a physical mechanism sub-model based on the geometric topology and heat flow coupling characteristics of the gas pressure regulating equipment, and loads a data driving sub-model to form a mixed digital twinning model; and in combination with real-time data mapping and a disturbance-safety boundary condition set, executing predictive iterative simulation to generate a plurality of groups of voltage regulation schemes, and screening an optimal scheme. And the execution and feedback unit converts the scheme into a standardized control instruction to drive pressure regulating equipment and return operation data to realize closed-loop optimization, so that real-time monitoring, high-precision prediction and self-adaptive regulation and control of the gas pressure regulating process are realized under complex working conditions, and the safety, the stability and the energy utilization efficiency are improved.

The invention relates to the technical field of intermediate frequency furnace sintering temperature control, and discloses a sintering temperature control system of an intermediate frequency furnace. The system comprises a multi-source data acquisition module which is used for acquiring multi-dimensional thermodynamic data, covering temperature distribution, sintering power and heat flow track data in a sintering process in real time; and the temperature field analysis module is used for carrying out dynamic compensation correction processing on the multi-dimensional thermodynamic data, inputting the multi-dimensional thermodynamic data into a sintering analysis processing layer for characteristic modeling, and generating a sintering temperature regulation and control instruction. The sintering analysis processing layer comprises a data preprocessing module and a thermodynamic modeling module, the data preprocessing module performs operation such as temperature interval division and abnormal value elimination on original data, and the thermodynamic modeling module is obtained based on historical data cooperative training. According to the system, through multi-dimensional data acquisition and analysis processing, the sintering temperature can be accurately regulated and controlled, the quality of sintered products and the production efficiency are effectively improved, and the system has good universality and adaptability.

The invention relates to the technical field of temperature control, in particular to a mass concrete water cooling water temperature control method and system. The method comprises the following steps: collecting concrete key parameters through a multi-source sensor, constructing a microenvironment model based on information geometry, and generating a thermosensitive characteristic spectrum; forming a distributed thermodynamic model by utilizing a mutual information routing algorithm and heat-fluid-solid coupling analysis, and calculating an optimal cooling strategy; water flow path and flow optimization is realized in combination with fractional order particle swarm optimization; a pump set and a valve are adjusted through fuzzy self-adaptive control; and a potential instability region is identified through the spectrum energy gradient, and risk early warning is triggered. The precision and reliability of mass concrete cooling temperature control are remarkably improved, and intelligent, efficient and safe temperature control adjustment in the whole process is achieved.

The invention provides a digital twinning application-oriented electrical equipment electromagnetic heat flow coupling rapid calculation method, and belongs to the technical field of electrical digital data processing.The method comprises the steps that firstly, a three-dimensional model of electrical equipment is acquired and preprocessed, and a full-order electromagnetic heat flow coupling calculation model is established and verified through a temperature rise test; generating an experimental point matrix by using a Latin hypercube sampling method, and constructing a current temperature power density relational data set; performing regional division on the power density field by applying a K-means clustering algorithm, and constructing an electromagnetic response surface model through a radial basis function; establishing a heat flow field order reduction model based on an intrinsic orthogonal decomposition technology, and extracting a dominant mode primary function; bidirectional coupling of an electromagnetic field and a heat flow field reduced-order model is achieved, an improved Lagrange multiplier method and a fixed point iteration method are adopted for processing the nonlinear coupling problem, finally, a software development kit supporting an open platform communication unified architecture protocol is packaged, and the electromagnetic heat flow coupling rapid calculation capacity needed by digital twinning application is achieved.

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 single-frame infrared thermal imaging building outer wall hollowing detection method and system based on heat flow evaluation. The method comprises the following steps: acquiring a single-frame infrared thermal image and a visible light image which are synchronously acquired; generating an infrared thermal imaging sequence based on the single-frame infrared thermal image and the Green function of the heat conduction control equation; performing time-space frequency domain transformation and column harmonic function inversion on the infrared thermal imaging sequence, and inversely transforming back to a time-space domain to generate a virtual heat flow image sequence; sequentially carrying out binarization processing and discrimination function enhancement processing on the single-frame virtual heat flow image to obtain an outer wall enhanced binarization image; identifying an interferent from the visible light image by adopting a target detection network; and carrying out registration and mapping on an identification result in the visible light image and the infrared thermal image, and removing interferents in the outer wall enhanced binarization image to obtain a pure outer wall binarization image. The method has the advantages of high environmental adaptability, high recognition precision and the like, and is suitable for safety detection and maintenance of building exterior walls.

The invention discloses a thermal management control method and device for a new energy automobile battery, and relates to the field of battery thermal management control, the device comprises an entropy change module, a fault module, a decision module, a phase change module and a scheduling module, entropy change intensity and nuclear heat flow field analysis is carried out on collected current and voltage signals to obtain an aging thermal topology, and the aging thermal topology is subjected to thermal management control. The method comprises the following steps: constructing an anisotropic diffusion equation based on aging thermal topology in combination with a fault diffusion tensor, discretizing a sub-strategy set for a safety margin field, constructing a cooling Nash game, analyzing through a payment matrix and a replicated dynamic equation, screening a stable strategy, mapping, and constructing an implicit phase change criterion model for the surface temperature of a battery to obtain a phase change cumulant; the phase change cumulant latent heat is analyzed and then cooperatively arbitrated with the cooling membership degree to obtain arbitration cooling capacity, the water pump flow is obtained through limiting operation based on the arbitration cooling capacity and the temperature deviation, then cubic root mapping is conducted on the water pump flow and the arbitration cooling capacity to obtain the fan rotating speed, and accurate control over battery thermal management is achieved.

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 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.

The invention relates to the technical field of pipeline detection, in particular to an infrared thermal imaging full-dimensional monitoring method for corrosion of a pipeline under a thermal insulation layer, which comprises the following steps of: acquiring temperature distribution under the thermal insulation layer and screening measuring points with consistent directions, extracting a boundary continuous region to calculate thermal probability, identifying abnormal measuring points and extracting time sequence characteristics, and predicting and marking response delay measuring points based on a model. And generating a CUI risk region division result. According to the method, a temperature difference direction consistency identification mechanism is constructed through space sequence subdivision and heat flow direction trend judgment of pipeline surface temperature distribution data, a measurement point set with clear space heat conduction characteristics is obtained through continuous screening, and a gradient change rate local extreme value is further taken as an identification basis; the method comprises the following steps: constructing a thermal anomaly probability evaluation parameter by combining spatial density and change intensity to realize preliminary identification of an abnormal point, then introducing a time sequence temperature parameter to construct a multi-dimensional dynamic feature set, and completing multi-step temperature prediction through normalized combination calculation after model training.

The invention relates to the technical field of battery heat dissipation, in particular to a hydrogen fuel cell high-uniformity radiator and a high-uniformity heat dissipation method.The hydrogen fuel cell high-uniformity radiator comprises a mounting frame and a heat dissipation box fixed to the side wall of the mounting frame, a heat dissipation cavity is formed between the heat dissipation box and the mounting frame, and a fan is fixed to the end, away from the mounting frame, of the heat dissipation box; the multiple heat dissipation fins are fixed to the mounting frame and distributed at equal intervals, and heat dissipation structures used for disturbing flowing of airflow are arranged on the heat dissipation fins; the air guide mechanism is arranged in the heat dissipation box, a first air guide plate is connected to the air guide mechanism, a follow-up pressurization mechanism is further arranged in the heat dissipation box, a second air guide plate is connected to the follow-up pressurization mechanism, and by controlling the first air guide plate and the second air guide plate to execute deflection action, pressurization airflow can be conveyed to an edge weak air area, so that the pressurization effect is improved; therefore, heat flow escaping from the central area can be smoothly discharged from the edge area.

The invention discloses a server temperature control method and system based on deep learning, and belongs to the technical field of server temperature control, and the method comprises the steps: firstly, synchronously collecting server hardware temperature, business load and environment parameters, capturing a heat conduction relation through combining a thermal imaging technology, and constructing a dynamic relation network through time-space fusion processing; a heat flow prediction model is constructed based on the network, model parameters are dynamically corrected in combination with thermal response characteristic attenuation coefficients generated by service load characteristic analysis, and temperature distribution changes are predicted; generating a candidate control strategy set, screening an optimal strategy through composite scene simulation, and generating a control instruction; and comparing the actual temperature after the control instruction is executed with the model prediction temperature in real time, switching to a safety control mode when the deviation exceeds a threshold value, and extracting an incremental sample to update model parameters after the deviation is recovered, thereby realizing accurate temperature control.

The invention discloses a server heat dissipation module control optimization method and system based on analogue simulation, and relates to the technical field of multi-physics field coupling modeling, and the method comprises the steps: constructing a multi-physics field simulation twin space, carrying out the heat flow simulation to obtain a heat dissipation simulation data set, collecting the real-time operation parameters of a server, mapping the real-time operation parameters to the space, and carrying out the heat dissipation simulation data set; the heat dissipation simulation data set is combined to deduce and obtain the heat dissipation temperature change trend, heat dissipation requirements are analyzed and determined according to the trend, a feedback data set is obtained through multi-target control and parameter adjustment, the space is corrected through the feedback data set, and a strategy is made to optimize heat dissipation module control. The technical problems that existing server heat dissipation control lacks twinborn simulation, accurate mapping and dynamic data processing support of the server heat flow state are difficult, complex changes of heat flow cannot be adapted, and consequently the heat dissipation regulation and control precision is insufficient are solved, accurate pre-judgment and dynamic regulation and control of the heat dissipation trend of the server are achieved, and the service life of the server is prolonged. And the control accuracy and adaptability of the heat dissipation module of the server are improved.

The invention discloses a reservoir-shaft integrated prediction method for geothermal exploitation, which belongs to the technical field of geothermal exploitation, and comprises the following steps: S1, constructing a cross-scale reservoir model, S2, establishing a reservoir-shaft coupling model, S3, establishing a heat-fluid-solid coupling control equation, S4, solving the coupling control equation, S5, simulating multiphase flow in a shaft, and S6, learning and optimizing a machine. S7, dynamically updating prediction; by constructing a cross-scale reservoir model and a wellbore-reservoir coupling model, accurate mapping from micro pores to macroscopic thermal storage and dynamic coupling of a reservoir and a wellbore are realized, and numerical solution and multiphase flow accurate simulation of a thermal-fluid-solid multi-field coupling control equation are combined. Rock heterogeneity, multi-physical field interaction and complex flow characteristics in the shaft are comprehensively considered, the prediction accuracy and comprehensiveness are greatly improved, and the defects that in a traditional method, reservoir and shaft analysis is split, and the model precision is limited are overcome.

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 belongs to the field of production control, and particularly discloses a control method of a thick-wall optical product precision injection molding hot runner system, which comprises the following steps of: acquiring mold geometric data of local thickness distribution in a mold-containing cavity along a melt flowing direction, calculating theoretical cooling time constants of each region by combining material thermophysical parameters, and calculating the cooling time constant of each region; establishing a thickness-cooling rate mapping relation model; predicting the time when the melt reaches each area and the effective cooling time according to an injection time sequence; solving a temperature compensation value of a heating area corresponding to the hot runner by taking the minimum final temperature variance when the key area is ejected as a target; and finally, dynamically applying a compensation value according to a time sequence before the melt arrives, and withdrawing / adjusting after region filling is completed or a pressure maintaining stage is entered. The invention can balance the temperature field of the mold cavity, reduce the refractive index gradient and shrinkage defect, improve the optical performance and yield of the product, and is suitable for precise injection molding of the thick-wall optical product.

The invention relates to a multi-dimensional high-resolution turbine blade heat-flow coupling field synchronous measurement method and system, and the method comprises the steps: obtaining a target spot image of known space distribution in a measurement space, and building a three-dimensional space mapping function; carrying out particle matching on the velocity field measurement original image based on a three-dimensional space mapping function, and reconstructing a three-dimensional particle trajectory by adopting a self-adaptive grid algorithm combined with machine learning to obtain a high-resolution three-dimensional velocity vector field; acquiring a temperature field measurement original image, performing three-dimensional space registration according to a three-dimensional space mapping function, further calculating voxel-level temperature distribution, and inverting a three-dimensional temperature field; and carrying out coupling analysis on the three-dimensional velocity vector field and the three-dimensional temperature field, and outputting a three-dimensional heat-flow coupling cloud picture. According to the invention, multi-dimensional and high-precision synchronous measurement of the temperature field and the velocity field in the complex flow field of the turbine blade is realized, the spatial resolution and dynamic response capabilities are remarkably improved, and a reliable experimental basis is provided for analysis and optimization of the cooling performance of the blade.

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 discloses an S-shaped micro-channel heat dissipation device with a double-layer turbulent flow structure and a use method, belongs to the field of liquid cooling heat dissipation, and is suitable for heat dissipation of a high-heat-flux device or a heat conduction device. The device comprises a base, a cover plate, a micro-channel body, turbulent flow columns, a flow guide structure, O-shaped sealing rings and quick-screwing connectors, the micro-channel body is provided with S-shaped channels which are vertically symmetrical, the turbulent flow columns are evenly arranged in the centers of the channels, and the top ends of the turbulent flow columns are flush with the end face of the micro-channel body. The turbulent flow columns can be rectangular columns or water-drop-shaped columns which are arranged in a single row or multiple rows at equal intervals and are matched with the flow guide structure to achieve efficient flow division of cold and hot fluid and interlayer heat interaction. Fluid mixing is strengthened through the centrifugal force of the S-shaped channel, a heat boundary layer is destroyed by the turbulent flow columns, and the problems that a traditional straight channel is low in heat exchange efficiency and uneven in temperature distribution are solved. Deionized water or nanofluid is selected as cooling liquid, closed circulation is formed by entering and exiting of the cooling liquid through the quick-screwing connector, and the adaptive scene and the comprehensive performance of the device are further expanded through the multiple rows of turbulent flow columns or the water-drop-shaped turbulent flow columns.

The invention discloses a multi-dimensional data-based temperature prediction method and system for a power integrated module, particularly relates to the technical field of temperature measurement, and is used for solving the problems of temperature field distortion and unreliable measurement result caused by thermal disturbance introduced by a sensor in temperature monitoring of an existing power integrated module. Multi-dimensional temperature data are formed by acquiring measurement data of a plurality of temperature sensors, a virtual heat flow path is reconstructed based on temperature gradient distribution, deviation degree analysis is carried out on the virtual heat flow path and an inherent structure heat flow path of a module so as to judge thermal disturbance influence, and reference isothermal surface topological structure features are acquired when disturbance occurs. A real-time isothermal surface is constructed, a thermal disturbance space position and an influence range are identified by detecting a curvature distribution sudden change area, a local thermal conductivity correction field is established to perform thermal field reconstruction on multi-dimensional temperature data to generate correction temperature field data, and finally a temperature change trend is analyzed according to the correction temperature field data to predict a future temperature state.

The invention provides a deep energy reservoir multi-scale heat-fluid-solid coupling simulation method and system, and belongs to the field of deep energy reservoir numerical simulation. Acquiring spatial distribution characteristics and physical property parameters of different lithologic reservoir media under a micro-scale, and constructing a digital structure model of the reservoir media; a micro-observation action mechanism and a flow mechanism are embedded in the model to obtain a micro-observation numerical model; establishing a mapping relation by solving model structure parameters and physical property parameters of the microscopic numerical model under different thermal-fluid-solid coupling conditions; and on the basis of the mapping relationship, in combination with the macrogeological and engineering data of the target reservoir, establishing a macroscale heat-fluid-solid multi-field coupling control equation and solving, and outputting the multi-physics field response of the target reservoir under the given working condition. According to the method, fine simulation of physical property parameter dynamic transmission and a multi-field coupling evolution process from a micro view to a macro view is realized, and the accuracy and reliability of deep complex reservoir engineering behavior prediction are remarkably improved.

The invention discloses a data center power distribution cabinet energy-saving heat dissipation method based on heat flow optimization, and the method comprises the steps: arranging a multi-source sensing unit for collecting monitoring data, and constructing a heat flow map containing the relation between nodes and edges; establishing a self-evolution heat flow neural map model based on the heat flow map, and dynamically updating an edge weight to output a prediction result; determining a temperature difference and an air flow direction according to a prediction result, and setting a phase change memory air guide composite layer structure; the central controller receives the prediction and air flow state and generates a heat flow control instruction linkage control parameter; an energy bond scheduling mechanism is established, a credit account is set, and cross-cabinet cooling capacity borrowing and repayment operation is executed; and updating the model by using feedback and deviation data, and periodically executing retraining and parameter optimization. According to the invention, intelligent heat dissipation and energy-saving optimization of the data center power distribution cabinet are realized through self-evolution heat flow neural map modeling and a synergistic effect of the phase change memory air guide composite layer and an energy bond scheduling mechanism.