3711results about "Temperatue control" patented technology

The invention relates to the technical field of self-adaptive control, and discloses a self-adaptive temperature control method and system for an automobile heater, and the method comprises the steps: calculating the real-time temperature deviation and temperature change rate of an actuator according to multi-dimensional temperature data; thermal inertia dynamic analysis is carried out on the historical heating power and temperature response relation through a preset thermal inertia compensation function, and a thermal inertia index of the actuator is obtained; the real-time temperature deviation, the temperature change rate and the thermal inertia index are jointly input into a preset fuzzy PID controller, and a preliminary power adjustment instruction of an actuator is output; analyzing the temperature change trend of the actuator in the time period, and performing prospective correction on the initial power adjustment instruction based on the temperature change trend; and controlling an actuator to execute heating operation according to the temperature control instruction, collecting real-time feedback temperature after the heating operation is executed, and performing joint online correction on parameters of the thermal inertia compensation function and a prediction coefficient of the time sequence model according to the real-time feedback temperature. According to the invention, the accuracy of self-adaptive temperature control of the heater can be improved.

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 technical field of process optimization, and discloses a hot work die steel heat treatment process optimization method and system.The method comprises the steps that hot work die steel samples are collected under multiple sets of different process conditions, and a performance basic data set is obtained; constructing a multi-target coordination optimization model based on the performance basic data set; performing phase change detection on the hot work die steel sample to obtain phase change monitoring data; performing prediction in combination with the phase change monitoring data to obtain a performance prediction result; and solving an optimal process parameter combination based on the performance prediction result and the multi-target coordinated optimization model, and realizing simultaneous optimization and coordinated balance of a plurality of performance indexes in the heat treatment process of the hot work die steel by making full use of associated information among different performance indexes.

The invention discloses an equipment temperature adjusting method fusing a long short-term memory network, and particularly relates to the technical field of temperature control, which comprises the following steps: determining the deployment position of a sensor through thermal simulation, collecting multi-source heterogeneous data, dynamically adjusting the sampling frequency in combination with the temperature and the load current change rate, and adjusting the temperature of the sensor; after data preprocessing, an attention mechanism enhanced LSTM prediction model is constructed, a time sequence sample data set is divided according to equipment thermal response characteristics, training is carried out, and an optimal model is obtained through early stop mechanism optimization; predictive feedback double-closed-loop regulation and control is achieved based on the optimal model, outer loop PI control is combined with an integral separation mechanism to generate a basic control quantity, an inner loop outputs a correction quantity through fuzzification, reasoning and defuzzification, an actuator is driven after superposition, and safety linkage is triggered synchronously; constructing an incremental data buffer pool to screen effective samples, and adaptively updating model parameters by adopting a layered fine tuning strategy; the temperature regulation and control precision and the long-term self-adaptive capability are obviously improved, and the over-temperature risk of equipment is reduced.

The invention discloses an agricultural product cold chain carriage temperature control method based on space equalization, and relates to the technical field of intelligent cold chain logistics, and the method comprises the steps: collecting carriage three-dimensional point cloud data and agricultural product electronic tag information, building a carriage loading three-dimensional model, carrying out the space grid division, and generating a partition topological feature vector; collecting temperature, humidity and carbon dioxide concentration data, calculating average temperature and average gas concentration observation values, and generating a breathing heat estimation value in combination with the partition topological feature vector; inputting the breathing heat estimation value into a dynamic prediction model, generating a subarea cold load curve and a priority weight by combining the subarea temperature deviation, and outputting a subarea cold load sequence; and according to the partition cold load sequence, generating a local execution proposal, constructing a global optimization problem taking the space temperature balance degree as an optimization target, and generating a global control plan. According to the method, global temperature equalization and energy consumption collaborative optimization are realized through network reasoning and dynamic optimization of the meta-reinforcement learning strategy.

The present application belongs to the technical field of material processing, and relates to a mold-free mirror image filament laying method and a mold-free mirror image filament laying system. The method lays a filament ribbon in a mirror image symmetry, without a mold, thereby improving production flexibility and efficiency. The method acquires the temperature and pressure of the filament ribbon in real time, calculates the output power of a heater and the modification value of a filament laying end motion mechanism path by using temperature and pressure differences, and optimizes controller parameters through reinforcement learning, so as to realize stable control of the temperature and pressure. The system comprises a hardware part and a control system. The hardware part includes pressure and heat source components. The control system adjusts through real-time feedback to ensure the quality of filament laying. The present application solves the problem that the temperature and pressure are difficult to accurately control in the process of mold-free mirror image filament laying, and improves the performance of composite products.

The invention relates to the technical field of intelligent control, and discloses a self-adaptive temperature curve control system for high-temperature alloy vacuum casting, which comprises a sensing module, a control module and a control module, and is characterized in that the sensing module acquires multi-point temperature information and preprocesses the information to obtain temperature distribution in a furnace; the acquisition module obtains vacuum environment parameters. The simulation module establishes a three-dimensional dynamic coupling model based on heat conduction, radiation, convection and phase change heat effect, and obtains a real-time temperature evolution prediction result. The generation module obtains a target temperature curve of the corresponding stage. The prediction control module collects a real-time temperature evolution prediction result and a target temperature curve, deviation calculation and trend analysis are carried out, and a heating power and cooling flow control instruction is generated. And collecting product feedback errors and carrying out self-learning correction on prediction model parameters to obtain an optimized control output result. The control and optimization of the high-temperature alloy vacuum casting temperature field are realized, and the structure uniformity of castings and the quality stability of finished products are improved.

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 relates to the technical field of non-electrical variable control or regulation systems, and discloses a temperature rising blanket temperature closed-loop control method and system based on human body position recognition feedback, and the method comprises the steps: calculating a form compactness coefficient representing a heat dissipation boundary based on pressure data, and calling a mapping function to convert the form compactness coefficient into an equivalent thermal impedance estimated value; introducing the estimated value and dynamically constraining the forward channel gain of the temperature closed-loop controller according to a negative correlation strategy; according to the method, a real-time mapping mechanism of the contact topological characteristics and the control gain is constructed, so that the problem of model mismatch caused by body position change of the controlled object is solved; when the high-impedance contact state is detected, energy input is automatically reduced, the local heat accumulation effect is restrained, and the convergence and safety of the thermodynamic control process under the variable boundary condition are ensured.

The invention relates to the field of mold cooling optimization, and discloses an automobile mold cooling optimization system and method based on reinforcement learning, and the method comprises the steps: collecting the real-time temperature and flow data of each cooling loop, carrying out the preprocessing and abnormity filtering of the data, and constructing a multi-dimensional basic cooling state database through combining historical operation records and environmental parameters; performing spatial mapping and statistical analysis on the temperature and flow data in the basic database, identifying a high-temperature region with heat concentration and a part with remarkable temperature gradient, and forming a local heat feature model; establishing an independent control sub-model, and optimizing cooling water flow and temperature regulation parameters of each loop by adopting a simulation and reinforcement learning combined method; a local adjustment strategy and an overall cooling target are fused, and main loop parameters are optimized through a global control algorithm; in the mold cooling process, temperature and flow fluctuation are continuously monitored, and real-time data are input into an optimization system. The method has the advantage that the cooling precision and efficiency are improved.

The invention discloses a PID temperature control system and method for a semiconductor etching machine, and relates to the field of temperature control, and the system comprises a coupling relation construction module, a temperature sensing confidence module, a decoupling compensation module, a coupling relation dynamic updating module, and a transient temperature change control module. According to the invention, by constructing the coupling relation matrix and the inverse matrix thereof, decoupling control of multi-area temperature control is realized, cross interference is effectively suppressed, and the temperature control precision is improved. And a multi-point temperature measurement fusion and anti-interference algorithm is introduced, so that the temperature measurement accuracy and the system robustness are enhanced. A response residual vector is associated with a control vector, and a coupling matrix is dynamically optimized, so that the system has self-learning and model self-adaption capabilities and adapts to working condition changes. And a transient temperature change quick response mechanism is set, so that the control priority can be improved and the PID parameters can be adjusted when the temperature changes suddenly, the response speed and the control stability of the system to abnormal temperature change are remarkably improved, and the thermal uniformity and the process consistency in the etching process are ensured.

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 relates to the technical field of building environment temperature control, and discloses a temperature control equipment intelligent adjusting method and system based on machine learning, and the method comprises the steps: building a space thermal field sensing network, obtaining multi-dimensional temperature field data, and generating a temperature gradient distribution matrix; and the positions of cold and hot spots are calibrated by combining infrared temperature measurement data, an airflow path is predicted, and air supply parameters are optimized. Meanwhile, building heat capacity characteristics are analyzed, and a thermal response dynamic model is constructed. And the air supply direction is adjusted for the local supercooling area. And based on the temperature change rate and the air supply parameters, the equipment start-stop time is optimized. Through real-time temperature sampling, continuous updating of temperature gradient distribution, cyclic execution of cold and hot spot calibration, airflow prediction and air supply optimization, accurate control of space temperature is realized. According to the invention, the accuracy and energy efficiency of building space temperature adjustment can be obviously improved, and an innovative solution is provided for an intelligent temperature control system.

The invention discloses a multi-device temperature control cooperative adjustment method and system, and relates to the technical field of intelligent control, and the method comprises the steps: S1, calculating a matching value with a case in a historical experience database through collecting multi-dimensional variable data of a current temperature control scene, including temperature and humidity device states and user demands, and employing a cosine similarity method, obtaining a similar historical case set; s2, according to the case with the highest matching value in the similar historical case set, extracting an equipment cooperation configuration parameter as an initial reference, fusing equipment power distribution, a cooperation time sequence, a parameter threshold range and a historical load mode, and determining a preliminary parameter adjustment basis; according to the multi-device temperature control cooperative adjustment method and system, the real-time decision-making efficiency and the energy efficiency optimization level of a temperature control strategy are remarkably improved, the method and system adapt to a complex dynamic environment, and accurate cooperative control is achieved.

The invention relates to the technical field of non-electrical variable control, and discloses an industrial water chiller temperature intelligent adjusting system, which comprises a refrigeration circulation loop and a control unit, the control unit calculates a steady state control component based on the water outlet temperature deviation, performs differential processing on the refrigerant pressure to extract the gradient, and outputs the gradient. Generating a transient compensation component when the gradient exceeds a dynamic noise threshold; according to the method, the problem of thermal lag is solved by utilizing the pressure wave transmission speed advantage, aggressive response is prevented from triggering low-pressure shutdown through a safety margin constraint mechanism, the pressure safety margin is calculated in real time, a gain coefficient is determined according to a nonlinear model, and a final driving instruction is generated. And the dynamic balance of the control response speed and the system physical security boundary is realized.

The invention relates to the technical field of temperature control of high-precision industrial heating equipment, in particular to an anti-interference precise temperature control method and system for heating an upper die, and the method comprises the steps: starting a multi-region heating array, heating the upper die to a target temperature according to a preset temperature rise curve, and building a uniform thermal field; before the high-pressure medium is introduced, heat load change caused by the high-pressure medium is predicted based on medium process parameters; in the medium introduction process, dynamic anti-interference compensation control is executed, a feedforward power compensation instruction based on a thermal load and a feedback power fine tuning instruction based on temperature deviation are generated respectively, and the feedforward power compensation instruction and the feedback power fine tuning instruction are weighted and fused into a composite power driving signal for adjusting a heating array; when the temperature fluctuation converges to a stable threshold value, the feedforward compensation weight is gradually reduced, smooth switching to steady-state control is achieved, transient thermal shock caused by a high-pressure medium is effectively restrained through feedforward and feedback cooperative compensation and dynamic weight adjustment, the temperature fluctuation is reduced, and the temperature control precision and stability are improved.

The invention discloses a furnace body temperature control system, which belongs to the technical field of industrial automation control, and comprises the steps of monitoring and collecting multi-dimensional data of a physical furnace body in real time, performing preprocessing, generating a state vector, setting a working condition judgment method, classifying various working conditions, outputting working condition labels and characteristic parameters, and establishing a health degree evaluation model; the state of the actuator is monitored in real time, and frequent maintenance and short service life caused by overuse of equipment are prevented; constructing a furnace body virtual model, setting a real-time prediction method, and simulating furnace body temperature distribution so as to predict a future temperature trend, judge whether to start a rehearsal mode, output an optimal scheme, and realize advanced intervention of prediction and decision making; a working condition identification and temperature prediction result is read, a decision engine method is set, and a dynamic control instruction is generated and executed; and comparing data of the physical furnace body with data of the digital twinborn body, setting a self-evolution method, and carrying out online calibration and correction on the virtual model.

A concrete mortar mixing and stirring system belongs to the technical field of concrete production equipment. Aiming at the problems that an existing stirring system is difficult to accurately judge the mixing uniformity of concrete mortar and the quality is easily influenced due to excessive stirring or insufficient stirring, the system comprises a stirring tank, a vibration signal acquisition unit, a torque monitoring unit and a control unit, stirring blades in a stirring tank are driven by a motor, a vibration signal acquisition unit captures a tank body vibration signal, a torque monitoring unit detects the torque change of the motor, and a control unit decomposes the tank body vibration signal into a frequency domain signal and extracts a preset aggregate collision vibration frequency band energy value to generate a vibration energy sequence; and analyzing the torque change fluctuation intensity to generate a torque variation coefficient sequence, calculating a correlation coefficient sequence of the two, generating an adaptive shutdown threshold by a sliding time window, and cutting off a motor power supply when the correlation coefficient sequence is continuously lower than the threshold for a preset number of times. The device is mainly used for automatic stirring control of concrete mortar, and precise starting and stopping of the stirring process are achieved.

The invention relates to the field of construction temperature regulation and control, in particular to an intelligent temperature control method and device for fan foundation construction in an alpine region. The method comprises the following steps: collecting real-time concrete temperature monitoring parameters based on a distributed temperature sensor, carrying out time sequence temperature discrete trend analysis and spatial temperature fluctuation distribution evolution, and constructing a temperature fluctuation distribution evolution diagram; concrete surface environment parameters are extracted, heat exchange simulation processing is carried out on the temperature fluctuation distribution evolution diagram, multivariate coupling correlation analysis is carried out, and a temperature-environment quantitative relation model is constructed; and obtaining historical meteorological logs and meteorological environment data of the construction area, carrying out similar meteorological condition matching calculation, carrying out short-term meteorological trend prediction, and generating short-term meteorological trend prediction features. According to the dynamic temperature regulation and control requirements, safe construction of the fan foundation concrete in the high and cold environment is guaranteed, and the construction quality is improved.

The invention relates to the technical field of spinning machines, in particular to a spinning machine precision control method suitable for a high-temperature working condition, and the method comprises the following steps: collecting multi-source information; establishing a mapping relation between the thermal error and the temperature field to obtain a thermal error prediction model, training and correcting the thermal error prediction model, and outputting a real-time thermal error prediction value; generating a comprehensive position compensation instruction and performing position compensation; the pressure feedback value collected in real time is compared with a corresponding preset threshold value, if the pressure feedback value collected in real time is larger than or equal to the corresponding preset threshold value, the comprehensive position compensation instruction is converted into a force control instruction, and if the actual axial pressure feedback value or the actual radial pressure feedback value is smaller than the corresponding preset threshold value in the force control process, the comprehensive position compensation instruction is converted into the force control instruction. If yes, returning to the position compensation mode. According to the method provided by the invention, comprehensive compensation and active inhibition of thermally induced errors can be realized, and the forming precision of high-temperature spinning and the surface smoothness of a workpiece are remarkably improved.

The invention relates to the technical field of lithium battery energy storage and temperature control, in particular to an electronic radiator intelligent temperature control system based on a lithium battery energy storage cabinet. The system comprises an edge temperature sensing module, a cloud thermal management strategy module, a cloud clustering analysis module, a thermal field topological optimization module, a multi-source thermal feature fusion module, a dynamic temperature control strategy generation module and a grading strategy issuing execution module. An edge temperature sensing module collects real-time temperature data of multiple monitoring points and an edge side preliminary temperature control scene judgment result; the cloud heat management strategy module receives battery pack topology connection data; the cloud clustering analysis module carries out fuzzy clustering on the data to obtain a temperature state and scene discrimination clustering center; the thermal field topological optimization module optimizes a temperature state clustering center in combination with topological data; the multi-source thermal feature fusion module fuses the two clustering centers to form multi-source fusion feature representation; the dynamic temperature control strategy generation module determines a temperature control strategy identifier accordingly, and the grading strategy issuing execution module matches and distributes a gradient temperature control strategy to a heat dissipation actuator.

The invention discloses an artificial intelligence-based refining process efficiency optimization and real-time temperature control method and system, and the method achieves the efficient optimization and precise temperature control of a refining process through the innovation of four steps: 1, breaking through the limitation of traditional single-point monitoring, and deploying a multi-modal sensing array and a feed port near infrared spectrum sensor according to three-dimensional coverage; process-raw material two-dimensional data are collected in real time and associated, and the problem of data islands is solved; 2, innovatively constructing a'process-raw material 'two-dimensional feature vector, predicting a finished product rate by adopting an XGBoost model, and judging a dynamic power adjustment demand in combination with a threshold value to replace a traditional experience decision; thirdly, on the basis of the value output by the DQN model, an optimal dynamic temperature curve is calculated in a staged mode, and then the problem of fixed curve stiffness is solved through a generated precise power instruction; and fourthly, a three-level aging standard reaching mechanism is created for the first time, and an effect closed loop is formed corresponding to a differentiated scheme of model strengthening, local compensation and cross-furnace repairing.

The invention provides a multi-temperature-zone temperature control system optimization method based on a gradient algorithm and segmented control, and the method comprises the steps: building a temperature control prediction model of each temperature zone through the gradient algorithm based on the thermal response characteristics of multiple temperature zones, determining a heat transfer path based on the predicted temperature data determined by the temperature control prediction model, and carrying out the optimization of the multi-temperature-zone temperature control system based on the thermal response characteristics of the multiple temperature zones. A temperature control process is divided into a plurality of stages, a corresponding stage temperature control strategy is established based on temperature control characteristics of each stage, optimal system precision is ensured through optimization and segmented control strategies based on a gradient algorithm, the stage temperature control strategies are optimized based on temperature difference between real-time temperature data and predicted temperature data, and the optimal system precision is ensured. The system can feed back and adjust the control parameters in real time, collect the actual temperature data at the end of each stage of the multiple temperature zones, optimize the heat transfer path based on the actual temperature data, and improve the energy efficiency of the whole temperature control system by optimizing the heat transfer path.

The invention relates to the technical field of chip test engineering control, in particular to an active temperature control method and system for a chip aging tester, and the method comprises the steps: analyzing a test process according to test task parameters, and evaluating the expected thermal load change rate of a test chip, so as to dynamically generate a chip target junction temperature control curve; based on the chip target junction temperature control curve, the actual chip junction temperature and the current actual furnace temperature, the theoretical furnace temperature is obtained through a junction temperature closed-loop control algorithm, the furnace temperature compensation amount is calculated through a feedforward compensation algorithm in combination with the test state parameters, and the ideal furnace temperature is obtained according to the theoretical furnace temperature and the furnace temperature compensation amount; the actual temperature control quantity is obtained according to the basic temperature adjusting quantity and the temperature control compensation quantity, a preset chip target junction temperature control curve can be tracked more accurately, transient and steady state errors caused by test program switching and environment fluctuation can be more effectively restrained, and control over the chip junction temperature with higher precision and faster response is achieved.

The invention relates to the technical field of lime kiln control, and discloses a lime kiln partition intelligent temperature control system and a storage medium, and the system comprises a data collection unit which is used for collecting state data of each region of a lime kiln; the working condition recognition unit recognizes working conditions based on the state data; the temperature control unit is provided with a PID (Proportion Integration Differentiation) control strategy and a prediction control strategy, and the opening degrees of the fuel regulating valves and the air regulating valves in different areas in the lime kiln are calculated according to the corresponding control strategies selected on the basis of working conditions; the discharging control unit is provided with a balance control strategy, the balance control strategy obtains the current discharging speed through the current productivity of the lime kiln and the material level height in the lime kiln, and the execution unit correspondingly controls the lime kiln according to the control quantity. The method effectively solves the problems of difficulty in multi-area coordination, poor working condition adaptability, high energy consumption and the like in a traditional control mode, and has the remarkable advantages of improving the temperature control precision, ensuring the production stability and reducing the energy consumption.

The invention relates to the field of control, in particular to a zone control method and system for a temperature field of a copper material heat treatment furnace. In the off-line stage, a strategy library containing various high-efficiency affine control laws is calculated in advance by solving a multi-parameter planning problem, the furnace temperature state space is divided into a plurality of explicit control subareas according to the coupling strength of all temperature areas in the furnace, and a set of alternative control laws are assigned for each subarea; during on-line operation, the partition to which the current furnace temperature belongs is determined according to the current furnace temperature, the partition with the minimum performance cost is quickly selected from the alternative control laws of the partition through short-time domain prediction to serve as the current optimal law, and when the predicted furnace temperature enters the boundary of the partition, the optimal control laws of the current partition and the adjacent partition are weighted and mixed; otherwise, directly adopting the current optimal law to generate a control instruction and applying the control instruction to the heater.

The invention provides an intelligent traditional Chinese medicine processing fire control method and system based on multi-modal sensing, and the method comprises the steps: collecting multi-modal sensing data in the previous traditional Chinese medicine processing process, carrying out the preprocessing, and then extracting multi-dimensional features; using a machine learning technology to identify different fire stages corresponding to the multi-dimensional features of each time point, fitting the multi-dimensional features in each fire stage through a regression algorithm, and constructing a dynamic fire curve template; collecting multi-modal sensing data in the current traditional Chinese medicine processing process in real time, and extracting real-time multi-dimensional features; the real-time multi-dimensional features are compared with the dynamic fire curve template, and feature deviation is calculated; meanwhile, the quality score of the real-time multi-dimensional features is calculated; on the basis of the characteristic deviation and the quality score, a control instruction is generated in real time through a preset control algorithm to intelligently regulate and control the processing fire degree; according to the invention, closed-loop, intelligent and robust decision-making and regulation of traditional Chinese medicine processing fire can be realized.

The invention discloses a die temperature field coordinated regulation and control method based on digital twinning, and relates to the technical field of die temperature control. The method comprises the following steps: constructing a mold temperature field digital twin model covering macroscopic, mesoscopic and microscopic scales; a distributed optical fiber temperature sensor is deployed to realize continuous temperature field sensing; physical-digital real-time synchronous mapping is established through ensemble Kalman filtering; performing model prediction control based on the digital twinborn body; three-dimensional visualization and multi-modal man-machine interaction of the temperature field are realized by adopting an augmented reality technology; and reinforcement learning is used to enable the digital twinborn body to have an autonomous optimization capability. Through deep fusion of a physical space and a digital space, precise sensing, real-time mapping and intelligent control of a mold temperature field are realized, and the temperature control precision and the self-adaptive capability of the system are remarkably improved.

The invention discloses a regulation and control system and method based on heat energy of an energy storage cabinet, and belongs to the technical field of intelligent heat management. Temperature data in the energy storage cabinet are collected, a temperature distribution matrix is constructed, and a thermal gradient vector and an overheating risk area are extracted based on a difference algorithm; further establishing a thermal power load mapping model, and dynamically generating an air circulation path optimization diagram; the opening angle of a flow deflector and the rotating speed of a fan are adjusted in combination with an optimized path, and self-adaptive regulation and control of a thermal field in the cabinet body are achieved; meanwhile, a machine learning model is trained by utilizing historical operation data, an optimal regulation and control strategy is output, and an execution layer is driven to realize collaborative response of a fan and a flow deflector; the method has the advantages of high regulation and control precision, high response speed, low energy consumption and the like, and is suitable for heat management requirements of various types of energy storage cabinets.