984 results about "Heat balance" patented technology

The invention provides an intelligent scheduling and control method and device for an integrated energy system. According to the method, power, gas and heat resource operation data are acquired, multi-scale layered modeling is performed according to a time scale and a space scale, and a power resource state space model, a gas resource flow continuity model, a heat resource heat balance model and a multi-energy coupling characteristic constraint model are established; carrying out feature extraction and dimension reduction representation by adopting a deep auto-encoder network; cooperative training of multiple groups of cognitive models is carried out through a split hierarchical federal learning framework, and a global intelligent model is obtained; constructing a neural architecture search network with a hybrid bionic learning rule, setting a hierarchical scheduling target, and generating a hierarchical intelligent scheduling strategy; and a fault-tolerant control mechanism is constructed, and error detection and correction of operation deviation are realized. According to the invention, multi-time scale collaboration, collaborative learning under multi-device group privacy protection and high-reliability fault-tolerant control are realized, and the operation efficiency and reliability of the integrated energy system are remarkably improved.

The invention relates to the technical field of photovoltaic power generation, and discloses a BAPV-based roof photovoltaic intelligent monitoring system and a dynamic tuning method and device. The method comprises the following steps: scanning a preset BAPV assembly through three-dimensional laser, constructing a surface point cloud model, and establishing a three-dimensional coordinate system comprising BAPV assembly installation base points; acquiring a real-time environment parameter set corresponding to the BAPV component; calculating an optimal working angle of the BAPV component according to the real-time environment parameter set based on an improved particle swarm algorithm; simulating an all-weather shadow movement track according to the optimal working angle based on a Monte Carlo method, and generating a component shielding influence weight matrix; establishing a heat balance equation according to the component shielding influence weight matrix so as to calculate a spacing optimization parameter of the BAPV component; a control instruction is generated according to the spacing optimization parameters, and dynamic tuning of the BAPV assembly is completed according to the control instruction; the control instruction comprises a support rotation angle compensation amount, an inverter parameter adjustment amount and an abnormal component isolation instruction. And the pain points of modeling errors, static optimization limitation, thermal runaway risks and the like are solved.

The invention relates to the technical field of reaction kettle temperature control, and discloses a fine chemical engineering reaction kettle temperature intelligent control method based on self-adaptive search, which comprises the following steps: S1, data acquisition: acquiring operation data of a reaction kettle, including temperature in the kettle, jacket inlet and outlet temperature, fluid flow and valve opening signals; s2, heat balance calculation: establishing a heat balance equation based on the collected data, and calculating reaction heat release and an equivalent heat transfer coefficient; s3, updating the model; s4, predictive control solution is carried out; s5, performing adaptive search; s6, carrying out security constraint; s7, stage identification; and S8, performing control execution. The reaction heat release amount and the equivalent heat transfer coefficient are calculated in real time through linkage of a heat balance calculation module and a model updating module, online parameter identification is achieved through a recursive least square algorithm, a heat model can be dynamically corrected along with working condition changes, it is ensured that a prediction model is consistent with the actual reaction process, and the prediction efficiency is improved. And the temperature prediction precision and the reliability of control response are obviously 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 discloses an axial flux motor temperature prediction method based on equivalent thermal circuit method calculation, and the method comprises the following steps: 1, motor thermal circuit unit division: decomposing a motor into a stator unit, a rotor unit, an air gap unit and a housing unit, and constructing an equivalent thermal network through a node-branch method; 2, calculating a multi-physics coupling heat source; 3, thermal resistance parameter dynamic calculation and CFD coupling optimization: calculating conduction thermal resistance, convection thermal resistance and contact thermal resistance; and 4, parameter self-calibration based on machine learning: constructing a PINN model according to a physical law and known physical parameters, introducing a Bayesian optimization algorithm on the basis of the PINN model, adjusting and optimizing the parameters of the PINN model by using Bayesian optimization, designing a reinforcement learning algorithm, and carrying out self-calibration on the parameters of the PINN model. Enabling the reinforcement learning algorithm to dynamically adjust parameters according to the real-time operation data of the system and the prediction result of the PINN model; 5, constructing and solving a heat balance equation; and step 6, visualizing and verifying the temperature field.

The invention 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 provides a sensorless motor stator temperature protection method, device and equipment, and relates to the technical field of motor control, and the protection method comprises the steps: obtaining the current voltage, current and rotating speed of a motor when the motor in a motor control system is in a running state, determining a corresponding temperature rise coefficient and a heat balance temperature according to the current voltage, the current current and the current rotating speed; obtaining a current estimated temperature according to the current voltage, the current current and the current rotating speed; determining a current predicted temperature according to the current estimated temperature, the heat balance temperature, the last estimated temperature and the corresponding temperature rise coefficient; and comparing the current predicted temperature with a preset protection threshold value, and performing temperature protection control on the motor according to a comparison result. A temperature sensor does not need to be installed in the motor, so that the installation difficulty and cost are reduced, the reliability and durability of the system are improved, and the risk that the sensor breaks down or is damaged is avoided.

The invention relates to the technical field of intelligent building heat load prediction and heat balance regulation and control, and discloses an intelligent building heat balance dynamic regulation and control method and system based on load prediction, and the method comprises the steps: constructing a time-frequency causal double-flow analysis network, mutual enhancement of the time-frequency characteristics and the causal relationship is realized; designing a hierarchical causal discovery algorithm, and mining a multilevel causal structure; developing a causal enhanced time-frequency representation learning method, and fusing time-frequency and causal information; establishing an intervention decision framework based on anti-fact analysis, and evaluating an intervention effect; an abnormal mode self-evolution recognition system is realized, and new abnormal modes are continuously learned; an interpretable abnormity diagnosis mechanism is developed, and a clear diagnosis report is provided; according to the method, the thermal load prediction accuracy is improved, the abnormal early warning capability is enhanced, the intervention efficiency is improved, the system interpretability is enhanced, and the optimization of the energy utilization efficiency is realized.

The invention discloses a roof radiant cooling and independent fresh air dehumidification system mixed operation comprehensive control method, and belongs to the technical field of building environment control and heating ventilation air conditioning. The method comprises the steps that the radiant cooling capacity and the dehumidification capacity of a surface air cooler are calculated through a heat balance equation, and an optimization objective that a top plate radiation system bears 70% sensible heat load and a fresh air system bears 90% humidity load is set; an anti-condensation strategy is triggered by combining dew point temperature monitoring, a control variable is adjusted by taking minimization of energy consumption as a target in a rolling time domain, and it is ensured that the indoor temperature ranges from 23 DEG C to 26 DEG C, the humidity ranges from 40% to 60%, the black ball temperature difference is smaller than or equal to 2 DEG C, and the condensation risk is smaller than or equal to 6%. The method is suitable for energy-saving temperature and humidity regulation and control of large public buildings, and efficient cooperative processing of sensible heat and latent heat loads is achieved.

The invention discloses an excavator heat dissipation control method and system based on environment temperature and operation working conditions. The excavator heat dissipation control method comprises the steps that S1, the operation working conditions of an excavator are divided into five working conditions including the super-heavy load working condition, the heavy load working condition, the medium load working condition, the light load working condition and the super-light load working condition; s2, the external environment temperature is divided into 10 gears; s3, according to the environment temperature and the operation working condition, the heat dissipation requirement is divided into 10 gears; s4, the rotating speed of the cooling fan is adjusted according to the cooling requirement gear, so that the cooling requirement is accurately matched with the rotating speed of the cooling fan; and S5, whether the temperature of the working medium in the excavator is larger than a high-temperature threshold value or not is judged, if yes, heat dissipation is conducted according to the corresponding heat dissipation fan rotating speed obtained through the heat balance test, and if not, heat dissipation is conducted according to the actual heat dissipation requirement gear standard. The problem of heat dissipation redundancy caused by single parameter control is solved, and dynamic matching of the rotating speed of the fan and the composite heat dissipation requirement is achieved. And the energy consumption under the low-load working condition and the cold environment is reduced, and the risk of insufficient heat dissipation under the high-temperature heavy-load working condition is avoided.

The invention provides a lithium ion battery core temperature prediction method based on a finite element model, and the method comprises the following steps: 1, designing an electrochemical test experiment, and constructing a one-dimensional electrochemical model containing a lithium ion battery electrochemical heat production mechanism; 2, designing a lithium ion battery temperature test experiment, obtaining electrochemical parameters, heat transfer characteristic parameters, internal thermophysical parameters and environmental parameters of the battery under different working conditions, and obtaining a temperature change curve of the center position and the surface of the battery; and step 3, based on the heat balance equation, establishing a three-dimensional heat transfer model having the same geometric characteristics as the battery used in the experiment. According to the experimental result in the step 2, the three-dimensional heat transfer model is subjected to non-uniform region division, each region corresponds to one one-dimensional electrochemical model, and the heat production rate per unit volume is calculated by the one-dimensional electrochemical model in the step 1; introducing the heat production rate of each area into a three-dimensional heat transfer model to calculate the temperature distribution of the battery, and designing an experiment to correct a one-dimensional electrochemical model; 4, modifying the operation conditions and heat dissipation conditions of the battery, and calculating and analyzing the temperature difference delta T between the center position and the surface position of the battery under different operation conditions and heat dissipation conditions by using the three-dimensional heat transfer model in the step 3; and 5, measuring the surface temperature of the battery, and calculating the temperature of the center of the battery according to the working condition of the battery in the step 4 and the delta T corresponding to the environment temperature, thereby realizing monitoring of the temperature of the center position of the battery. According to the method, a high-precision algorithm model is constructed and verified by utilizing data accumulated in an earlier-stage experiment, the central point temperature which is difficult to directly measure in the battery is predicted only through real-time and easily-acquired battery surface temperature information, operation condition parameters and heat dissipation conditions, key thermal state information is provided for a battery management system, and the battery management efficiency is improved. The method is used for real-time safety monitoring and thermal management optimization.

The invention discloses a hybrid model driving-based space-time consistency regulation and control method for a central heating system, which comprises the following steps of: performing hydraulic equilibrium analysis on the central heating system, and performing hydraulic analysis on a space structure of a heating pipe network by using a graph theory method based on an energy conservation law, simulating the hydraulic working condition of the official website by using a basic loop analysis method; based on an energy conservation and mass conservation heat balance equation, a heat source and a heat user are indirectly connected through heat exchanger transition, a dynamic physical model of each subsystem is established based on a lumped heat capacity method, a refined model of the heat supply system is established, and the thermal dynamic characteristics of the system are researched and analyzed; based on a Pearson's correlation function, considering thermal inertia of equipment such as a pipe network of the central heating system and a building fence structure, and determining a regulation and control period and time of the regulation and control model; according to the method, by controlling the opening degree of the regulating valve of the heat exchange station, the suitability degree of the room temperature of a heat user is guaranteed.

The invention belongs to the technical field of crude oil electric heating furnaces, and relates to a crude oil electric heating furnace control system and a crude oil electric heating furnace. Temperature feature vectors of multiple independent heating sections are collected, a dynamic weight matrix used for representing the thermal inertia unbalance degree is generated, and temperature control compensation gains are generated through real-time analysis in combination with crude oil viscosity-temperature data; performing adaptive adjustment by combining corresponding element values of the dynamic weight matrix to output a segmented power regulation instruction, preferentially calling redundant power of the main and auxiliary coils for cooperative heating, starting adjacent segment compensation heating when the main and auxiliary power is insufficient, and setting heat balance constraint and deviation monitoring termination conditions at the same time; local over-coking is avoided while the power resource utilization rate of the crude oil electric heating furnace is remarkably improved, the viscosity is rapidly converged to a steady-state range through closed-loop feedback of viscosity data after heating and iterative optimization of a regulation instruction, and the stability of long-term operation of the system and the achievement speed of a control target are remarkably improved.

The invention relates to the technical field of building energy conservation, in particular to an edge computing cooperative communication method for multiple heat pumps and a photovoltaic system, which comprises an edge server, a cloud server, multiple heat pumps, a variable frequency pump and an indoor and outdoor heat supply device, and is characterized in that the edge server realizes time synchronization of equipment through an OPC UA over TCSN protocol, a multi-level energy topology network is established, and the multi-level energy topology network is connected with the cloud server; in combination with physical energy flow and information flow, based on a building heat balance equation, an edge server controls a heat pump to work at an energy-saving operation point according to indoor and outdoor temperatures and user requirements, and the flow of a variable frequency pump is adjusted. In addition, multi-mode state sensing is achieved through the distributed sensor network, a layered self-adaptive control strategy is executed, photo-thermal collaborative optimization and heat pump group collaborative control are achieved, the system collaborative control precision is remarkably improved through the method, the time synchronization error is reduced by three orders of magnitude, and the system response speed reaches the millisecond level and is 10 times faster than that of a traditional system.

The invention belongs to the technical field of intelligent heat supply, and provides a green power consumption heat storage and release matching control method and system based on a water heat storage boiler, and the method comprises the steps: firstly obtaining a heat load prediction sequence and an electric power spot market price prediction sequence of a heat supply system; secondly, regarding the heat supply network as a graph structure composed of nodes and pipelines, and establishing a pipe network dynamic model for describing the hydraulic and thermal characteristics of the heat supply pipe network; and finally, with the purpose of minimizing the comprehensive operation cost of the heat supply system in the whole scheduling period, and with the whole network heat balance, heat source operation, centralized heat storage device operation, heat supply network safety and user comfort as constraint conditions, solving to obtain a source network load storage cooperative control strategy. The purpose of integrated collaborative optimization of the heat source, the energy storage, the pipe network and the load is achieved, a scheduling strategy with better economical efficiency can be generated, and the problems that the absorption capacity is insufficient, and the overall operation economical efficiency of the system is not high are solved.

The invention relates to the technical field of orchard meteorological disaster prevention and reduction frost prevention, and provides a surface layer disturbance temperature inversion frost prevention method. According to the method, the frost rate of the orchard can be effectively reduced and the frost loss can be reduced through the processes of constructing the orchard air temperature prediction model, determining the frost disaster threshold value, installing fan pipe tower equipment in the orchard, collecting temperature data in real time based on a sensor network of an Internet of Things monitoring system and optimizing fan parameters through the heat balance model.

The invention provides an integrated energy system operation optimization method considering a source-load fusion scene, and relates to the technical field of energy optimization, and the method comprises the steps: constructing a typical output scene based on historical renewable energy output data; fusing the typical output scene with the electric-thermal load data in the corresponding time period to generate a typical scene sequence representing source-load correlation; taking the comprehensive operation cost as a target, establishing a scheduling optimization model for simultaneously constraining the electricity-heat balance, the equipment output and the energy storage state, and embedding the typical scene sequence into the scheduling optimization model; solving the optimization model to obtain a multi-period optimal scheduling strategy; and controlling energy supply and storage equipment in the integrated energy system according to the scheduling strategy. According to the method, the optimal energy supply scheme of the comprehensive energy system capable of effectively avoiding the uncertainty of the source load is generated for a typical source load fusion scene, the economic benefit of the system is effectively improved on the basis of ensuring energy supply safety, and multi-target balance of economy and reliability is realized.

A heat balance optimal satellite sun orientation control method comprises the following steps: firstly, determining sun orientation target parameters according to a sun vector direction calculated by an orbit, using preset sun orientation target parameters when regular preset parameters are set, and then calculating a sun orientation target attitude angle and angular velocity by using a formula provided by the method, and finally, the sun orientation of the satellite to the target attitude angle and angular velocity is realized according to the measurement of the terahertz gyroscope and the plane control of the jet phase.

The invention discloses a pump station unit state comprehensive evaluation method, and belongs to the technical field of pump station unit detection. The method comprises the following steps: acquiring multi-source monitoring data and generating a standardized monitoring data set; time-varying mutual information between indexes is calculated, a dynamic threshold value is determined in combination with current working condition parameters and a water level difference correction term, and a dynamic association network is constructed; performing physical mechanism characteristic decoupling on the data, including stripping a vibration signal working condition drift component based on a reference curve to obtain a vibration residual error, and calculating an equivalent standard working condition temperature based on a heat balance principle; respectively calculating a first weight based on data statistics and a second weight based on network topology, and adaptively generating a comprehensive coupling weight according to a consistency coefficient of the first weight and the second weight; and finally, judging a health state level by using a cloud model. Through deep fusion of a physical mechanism and data driving, the problems that fault features are difficult to extract and the model robustness is poor under variable working conditions are solved, and accurate evaluation of the unit state is achieved.

The invention relates to the technical field of ground source heat pumps, and discloses a ground source heat pump buried pipe zoning layout and cold and heat balance control method which comprises the following steps that the current three-dimensional ground temperature field state of the area where a ground source heat pump buried pipe is located is obtained; predicting a future state sequence of the ground temperature field under different control strategies in a future prediction time domain; solving to obtain an optimal control sequence based on a multi-objective optimization function which aims at minimizing the comprehensive operation cost of the system in the prediction time domain; the multi-objective optimization function at least comprises an energy consumption item representing system short-term operation energy consumption and a balance item representing a ground temperature long-term balance state; and executing the first control action in the optimal control sequence. The prediction model constructed by the invention can combine a physical rule with a data residual continuously learned from actual operation, and ensures that prediction information on which a control decision depends always keeps high fidelity in long-term operation of the system.

The invention relates to the technical field of heat supply unit peak regulation capacity optimization, in particular to a heat supply unit heat storage peak regulation strategy construction method and device and a storage medium, and the method comprises the steps: carrying out the hourly prediction of a day-ahead electrical load and a day-ahead thermal load through a target BO-ResNet-AM neural network prediction model, obtaining a day-ahead hourly electric load predicted value and a day-ahead hourly thermal load predicted value; based on a power supply balance constraint, a heat supply balance constraint, a unit ramp rate constraint and a target function, taking pipe network heat storage / release, actual power supply power and actual heat supply as decision variables, and constructing an initial source network load storage collaborative interaction mode optimization scheduling model; and converging the initial source network load storage collaborative interaction mode optimization scheduling model to a globally optimal solution through an adaptive weight learning factor particle swarm optimization algorithm. By accurately predicting the electric heating load and quantifying the heat storage capacity of the pipe network, peak clipping and valley filling of the electric load and space-time translation of the thermal load are achieved, and the deep adjustment and peak capacity of the unit is improved.

The control device comprises a control module, an ice melting power supply module, a boundary switch, a short circuit switch and an ice melting switch, the boundary switch, the short circuit switch, the ice melting switch and a protection switch are arranged on a high-voltage cable, and the control module sequentially drives the boundary switch, the short circuit switch, the ice melting switch and the protection switch to execute state switching through action instructions. The conduction control of the ice melting loop is realized; the control module integrates a finite element algorithm function, collects current, voltage and temperature distribution parameters in an ice melting loop in real time, and dynamically corrects ice melting current parameters through three-dimensional electromagnetic-thermal coupling field simulation; setting a parametric modeling unit, and calculating an optimal voltage regulation gear based on a heat balance equation and a Joule heat effect to realize adaptive voltage regulation; the demarcation switch, the short circuit switch and the ice melting switch are arranged, the effect of cable short circuit heating ice melting is achieved by sequentially controlling the on-off states of all the switches, finite element real-time simulation and parameterization voltage regulation decision are combined, and the cable ice melting efficiency, reliability and safety are remarkably improved.

The application discloses a kind of in-service air conditioner performance detection device and method.The device is composed of wind receiving chamber, exhaust chamber, return air chamber, differential pressure gauge, two mixers, heating wire and humidifier, return air temperature and humidity probe and return air motor.The device uses electric heating wire heat balance air conditioner refrigeration capacity, through heating and humidification method, air conditioner blows out the air to the detection required temperature and humidity state, and is connected to the return air opening of air conditioner, circulates and operates to reach stable state and has continuous condensate, uses electric energy meter to collect the electric energy of heating wire 1h, and synchronously collects the condensate amount generated by air conditioner 1h, according to the data collected, the performance of in-service air conditioner can be calculated, without disassembling air conditioner, avoid damage to in-service air conditioner.

The invention relates to the technical field of cold-chain logistics transportation and storage temperature control, in particular to an air compressor vehicle-mounted refrigeration and refrigeration house collaborative temperature control system based on AI scheduling, which comprises a multi-dimensional state sensing module used for collecting real-time temperature field data, environmental meteorological parameters, compressor operation states and goods category information in a refrigerator car and a refrigeration house, and sending the real-time temperature field data to a server; a structured multi-dimensional state vector is output; and the thermodynamic evolution prediction module is used for setting a prediction time domain with a finite length based on the multi-dimensional state vector, and calling and constructing a mathematical model of a heat balance relationship between the refrigerating capacity generated by the operation frequency of the compressor and the environment and the cargo heat load. According to the method, the comprehensive cost function fusing the energy consumption, the cargo quality loss and the equipment wear is constructed, and the hidden quality attenuation is converted into the dominant economic cost by using the Arrhenius model, so that the global operation benefit maximization of the system on the premise of ensuring the cargo safety is realized.

The invention relates to the technical field of ground source heat pump operation control, in particular to an optimal adjustment method of a ground source heat pump system, which comprises the following steps: S1, collecting underground soil temperature and system heat load of the ground source heat pump system; s2, calculating a soil heat balance index based on the underground soil temperature; s3, according to the soil heat balance index and the system heat load, the optimized operation mode of the ground source heat pump system is judged; and S4, according to the optimized operation mode judged in the S3, the operation parameters of the ground source heat pump system are adjusted, and a corresponding execution mechanism is driven. According to the method, the operation mode is judged by introducing the soil heat balance index and combining the system heat load, meanwhile, the flow of the circulating water pump, the frequency of the compressor and the opening degree of the heat exchange valve are subjected to interval adjustment, and unification of energy efficiency optimization and long-term balance of the soil heat environment is achieved.

The embodiment of the invention provides a gas-liquid phase change carbon dioxide energy comprehensive utilization system suitable for a data center and a control method thereof, and the system comprises an energy storage subsystem which comprises a gaseous carbon dioxide management unit, an energy storage assembly, a liquid storage unit and an energy release assembly which are sequentially connected in a closed loop manner; the energy release assembly comprises an evaporator; a heat exchange medium inlet of the data center is connected with a heat exchange medium outlet of the evaporator, and a heat exchange medium outlet of the data center is connected with a heat exchange medium inlet of the evaporator; the heat balance assembly comprises a high-temperature transmission pipeline and a low-temperature transmission pipeline; the heat balance assembly is used for supplementing a high-temperature heat exchange medium to a heat exchange medium inlet of the evaporator through the high-temperature transmission pipeline or supplementing a low-temperature heat exchange medium to a heat exchange medium inlet of the data center through the low-temperature transmission pipeline under the operation working condition of the system when the heat dissipating capacity of the data center is inconsistent with the heat supply capacity needed by the evaporator. The embodiment of the invention can realize comprehensive utilization of energy and reduce the investment and operation cost of the system.

The invention discloses an enterprise lease-oriented equipment credit evaluation system and method, relates to the technical field of equipment data processing, and aims to synchronously quantify the running temperature, power consumption and heat dissipation state of equipment by forming an original thermal state data set Hraw and avoid one-sided judgment caused by traditional single-parameter monitoring. Based on a thermal state feature set Hset of a temperature stability index Tstb, a power consumption fluctuation spectrum index Pspc and a heat dissipation anomaly integral Qint, a three-dimensional feature space reflecting equipment operation stability and energy balance can be constructed, a thermal state feature template set Htpl is further formed through clustering, and dynamic reference establishment in different operation modes is achieved. And comparing the real-time feature vector with the thermal state feature template set Htpl to calculate a thermal balance index Hc, and generating an equipment credit score Sc in combination with a historical credit mean value score Sh, so that quantitative credit of enterprise equipment use behaviors can be realized.

The invention discloses a simulation analysis method and system based on an electromagnetic compatibility test, and relates to the field of electromagnetic compatibility testing, and the method comprises the steps: building a hardware three-dimensional simulation model for a hardware environment with electromagnetic compatibility to be tested, and obtaining hardware environment data; establishing a multi-device heat balance model, and dynamically adjusting temperature values and distances between the plurality of components and between the component groups; based on FDTD and MoM algorithms, the electromagnetic compatibility of the hardware environment data is analyzed; establishing an electromagnetic compatibility dynamic adjustment model, and dynamically optimizing the stability of to-be-tested electromagnetic compatibility hardware configuration and software analysis; and optimizing and adjusting the electromagnetic compatibility dynamic adjustment model in combination with actual design feedback. The method has the advantages that through multi-physics field coupling simulation and dynamic feedback optimization, collaborative design of hardware layout, heat balance and electromagnetic compatibility is achieved, the compliance rate of an electromagnetic compatibility test is remarkably improved, and the research and development cost is reduced.

The invention relates to the field of intelligent clothing power supply control, in particular to an intelligent clothing power supply control method and system based on temperature feedback. Real-time collected data in a multi-mode sensor are obtained, dynamic baseline calibration is conducted on the real-time collected data, then feature vectors are constructed, fusion calculation is conducted on the human body temperature according to a Pennes biological heat equation, calculation is conducted on the human body initial temperature based on a dynamic heat balance equation, and the system active regulation and control heat flux is obtained. Establishing an intelligent temperature prediction model; and inputting the characteristic data set and the system active regulation and control heat flux into a temperature intelligent prediction model for prediction, and carrying out temperature regulation and control on a power supply control system of the intelligent clothes according to a multi-step temperature prediction result. The precision and efficiency of temperature prediction are significantly improved, and accurate pre-judgment of multi-step temperature is realized.

The invention relates to the technical field of civil construction engineering, in particular to effective utilization of geothermal resources and improvement of an energy exchange system. According to the energy pile, dynamic regulation and control of stratum heat balance are achieved through the active heat management technology, and the influence of heat accumulation on sustainable utilization of geothermal resources is effectively prevented; a composite heat extraction structure is adopted, and the heat absorption efficiency of geothermal resources is remarkably improved; a high-thermal-conductivity energy pile comprises a fixed base body, and a water circulation assembly is embedded in the fixed base body. The water circulation assembly comprises a water pumping assembly, a circulation pipeline and a water conveying assembly which are communicated with one another; a heat absorption device is arranged on the outer side of the fixed base body and comprises a plurality of heat absorption columns which are vertically distributed; the heat absorption column is provided with a heat conduction head embedded into the fixed base body.