41374 results about "Temperature control" patented technology

The invention relates to the technical field of battery temperature control early warning, in particular to an energy storage battery temperature control early warning method and system. The method comprises the following steps: acquiring an internal structure diagram of the energy storage battery; performing internal space layout analysis and inter-unit physical connection analysis on the internal structure diagram of the energy storage battery to construct a three-dimensional battery topological structure model; acquiring real-time temperature monitoring parameters of the energy storage battery; dynamic temperature distribution visual rendering is carried out on the three-dimensional battery topological structure model according to real-time temperature monitoring parameters of the energy storage battery, so that thermal state portraits of a plurality of unit areas are constructed; performing multi-period battery operation simulation on the thermal state portraits of the plurality of unit areas, and performing sliding time window temperature change situation prediction to obtain a temperature change prediction situation of each area; and carrying out continuous abnormal temperature rise trend detection on the temperature change prediction situation of each area so as to generate an abnormal temperature rise trend characteristic. According to the invention, safe and efficient pool temperature control early warning is realized.

The present application relates to the field of wire laying control technology, and discloses a composite material automatic wire laying forming optimization method, system, medium and wire laying machine. The method comprises: inputting dynamic tension control data into a fuzzy neural network calculation engine to obtain a dynamic compensation model for the retraction and release speed; based on the dynamic compensation model for the retraction and release speed, using a reinforcement learning engine to calculate the shearing sequence of multiple bundles and generate an intelligent shearing instruction set; constructing a re-delivery trajectory mapping relationship based on the intelligent shearing instruction set, and forming a re-delivery path matrix after iterative calculation by a digital twin engine; establishing a temperature field distribution prediction model based on the re-delivery path matrix, and constructing a temperature field dynamic control sequence after finite element analysis and calculation; substituting the temperature field dynamic control sequence into a multi-objective constraint equation, and outputting a laying strategy data packet after deep reinforcement learning iterative optimization. The present application realizes the precise coordination of multiple process parameters such as tension control, speed compensation, shear control, and temperature control.

The invention provides an energy-saving temperature control optimization method and system based on a central air-conditioning simulation platform, and relates to the field of central air-conditioning simulation platforms, and the method comprises the steps: collecting the operation parameters of a central air-conditioning system in real time through an Internet of Things sensor network, constructing a multi-dimensional dynamic data set in combination with historical data and outdoor meteorological data, and carrying out the calculation of the multi-dimensional dynamic data set; a physical model and machine learning hybrid driven simulation engine is adopted, a dynamic thermodynamic model of the central air-conditioning system is established, and a multi-objective optimization function of a simulation platform model is defined according to user comfort requirements, energy consumption cost constraints and environmental policy indexes; and adopting a hybrid optimization strategy of fusion of reinforcement learning and a genetic algorithm, iteratively optimizing control parameters in the simulation platform model, deploying a digital twin system according to the energy-saving strategy set, predicting potential faults through a virtual sensor, correcting the parameters of the simulation platform model, and realizing closed-loop control and continuous optimization. The method is used for overcoming the defect that a closed-loop feedback mechanism is lacked in the prior art.

The invention provides an intelligent toy injection molding process optimization method which comprises the following steps: aiming at a key temperature control area, calculating an optimized cooling time value and a cooling water temperature set value through a correlation model of thermodynamic attribute parameters of toy materials, cooling time and cooling water temperature, and issuing the cooling time value and the cooling water temperature set value to an injection molding machine control system, meanwhile, according to the temperature fluctuation amplitude of the key area, the forming pressure value is finely adjusted, so that the temperature fluctuation of the key area is reduced; in the injection molding process, temperature data of multiple positions on the surface of the mold are collected in real time and transmitted to the central processing unit, the central processing unit conducts filtering and denoising on the collected temperature data and then judges whether the temperature data exceed the optimized temperature control range or not, if yes, an alarm mechanism is triggered, and meanwhile operation parameters of the injection molding machine are automatically adjusted. And the time for deviating from the temperature control range is shortened to the minimum.

The invention relates to a high-strength complex-phase hot-rolled wire rod for a 2500MPa-grade bridge cable and a manufacturing method of the high-strength complex-phase hot-rolled wire rod, after the high-carbon component of Nb-V-Mo is rolled and spun into a wire rod, the wire rod is subjected to online molten salt tail end quenching toughening treatment, so that the wire rod passes through front-section molten salt and is cooled at a cooling speed of greater than or equal to 38 DEG C / s, a part of austenite structure is transformed into quenched martensite, and a part of austenite structure is transformed into quenched martensite; the method comprises the following steps of: heating to a sorbite phase region temperature through a rear-section molten salt, controlling unconverted austenite to be converted into sorbite, performing isothermal tempering, controlling precipitation and growth of carbides, and finally performing slow cooling through a roller way to prepare a hot-rolled wire rod of which a microscopic structure comprises a complex-phase structure consisting of tempered martensite and tempered sorbite, wherein the tensile strength of the hot-rolled wire rod is 1710-1750MPa; the production method has the advantages that the material cost is controlled, the production efficiency is improved, and the production method is suitable for 2500MPa bridge cable production and is beneficial to reducing the risk of wire breakage in downstream cold drawing and subsequent processing processes.

The invention relates to the technical field of temperature control, and discloses a temperature error compensation method and system for a multi-heating-section coffee maker, and the method comprises the steps: synchronously collecting the real-time temperature value of each heating section, and calculating a temperature error index; constructing a thermal coupling interference model based on the physical distance between adjacent sections and the heat conduction characteristic of the medium; generating a dynamic decoupling compensation parameter according to the model and the error index (including constructing a symmetric interference matrix, calculating a coupling interference component, applying negative feedback and identifying a main interference component); a decoupling parameter is converted into a power adjustment instruction through a multivariable control algorithm (superposition of basic compensation and decoupling compensation, amplitude limiting and phase compensation); and heating output is updated according to the power instruction, and iterative execution is performed based on the error index change trend until the temperatures of all sections reach steady-state balance. The method can effectively model and compensate thermal coupling interference between sections, improves the efficiency of temperature error compensation, and achieves the quick and stable cooperative temperature control of multiple sections.

The invention relates to the technical field of industrial automation control, and discloses a high-precision and quick-response industrial thermostat temperature regulation system which comprises a temperature acquisition module, a fluctuation analysis module, a dynamic calibration module, a gradient optimization module, a threshold management module and a regulation execution module. The temperature acquisition module acquires real-time temperature and environment thermal inertia parameters, and sets a temperature adjustment interval; the fluctuation analysis module divides temperature nodes and generates fluctuation feature vectors; the dynamic calibration module extracts a temperature deviation index and establishes an adjustment compensation rule; the gradient optimization module identifies a temperature change grade and calculates a fluctuation density difference value; the threshold value management module deduces an optimal adjustment threshold value and generates a threshold value deviation sequence; and the adjustment execution module is integrated to form a temperature adjustment execution scheme. The system realizes deep analysis and dynamic compensation of temperature fluctuation through cooperation of multiple modules, improves the adjustment precision and the response speed, and is suitable for high-precision temperature control industrial scenes such as chemical engineering and mechanical manufacturing.

The invention relates to the technical field of industrial control systems, in particular to a PET extruder multi-zone intelligent temperature regulation and control system, which comprises a temperature field parameter acquisition module for acquiring the input power, the real-time temperature value, the temperature change rate value and the temperature difference value between adjacent temperature zones of an extruder to obtain a temperature zone associated state set; and summarizing and mapping the temperature zone association state set, and establishing temperature field response characteristics. According to the method, through correlation analysis of the temperature states of the multiple areas, independent adjustment of a single area is upgraded to dynamic optimization based on the thermodynamic coupling relation, and the coordination of temperature adjustment of the multiple areas is improved. Dynamic parameters required by temperature regulation and control can be calculated in real time in combination with the heat transfer rate, the temperature response delay time and the temperature response gain coefficient of the temperature interval instead of depending on a fixed set value, different operation working conditions are adapted, and the regulation and control flexibility is improved.

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

The invention relates to the technical field of temperature regulation and control, in particular to a liquid cooling control method and system of a battery control device, in the liquid cooling control method and system, through real-time collection and area screening of temperature and power data, accurate recognition of a high-temperature area is achieved, a clear cooling requirement partition is provided, and the cooling requirement of a battery is met. A dynamic adjustment strategy of pressure and flow parameters of the liquid cooling pump is optimized through a genetic algorithm, the cooling response speed and control precision are improved while energy consumption and cooling efficiency are effectively balanced, the pump speed and the valve opening degree are adjusted in real time, temperature changes are rapidly responded through automatic control, gradual implementation of a cooling target is ensured, and the cooling efficiency is improved. The hysteresis in the heat management process is reduced, the temperature control effect is continuously evaluated through a fuzzy control algorithm, the cooling intensity is dynamically adjusted according to the monitoring result, efficient cooling is ensured, meanwhile, equalization of temperature distribution is achieved, and a systematic heat management framework is established through long-term data monitoring and continuous optimization of cooling operation. And efficient and stable operation of temperature management is realized.

The invention relates to the technical field of light emitting devices, and discloses a control method for a silicon light integrated multi-wavelength light emitting device, and the method comprises the steps: carrying out the grating coupling processing and polarization state separation processing of a plurality of wavelength channels of the silicon light integrated multi-wavelength light emitting device, and obtaining an initial optical characteristic data set; performing temperature response characteristic analysis to obtain a temperature field characteristic parameter set; performing spectral characteristic analysis on the plurality of wavelength channels to obtain wavelength channel characteristic vectors; a wavelength drift coefficient matrix and a refractive index change coefficient matrix are calculated, and a multi-wavelength linkage control data model is generated; according to the method, a hierarchical control structure comprising a quick response layer, a temperature compensation layer and a polarization optimization layer is constructed, multi-wavelength cooperative control operation is executed, and a steady-state control parameter set is output, so that the wavelength stability control precision and the temperature control precision are improved, the adaptive capacity to disturbance of different time scales is enhanced, and the stability of the system is improved. And stable operation under complex working conditions is ensured.

The invention relates to the technical field of processing temperature control, and discloses a temperature control method and system for a hot processing process and a storage medium. The method comprises the following steps: collecting hot working whole process temperature data through multiple sensors, calculating a temperature change rate, an extreme point and a uniformity index, and obtaining key characteristic parameters; establishing a quantitative relation matrix of the process parameters and the temperature field by using an orthogonal test; calculating an optimal process parameter combination based on the matrix by using a rolling time domain optimization algorithm to generate a control instruction; and performing execution opportunity and duration prediction and correction on the instruction to form a precise target control instruction. The temperature control precision and stability in the hot working process of the large alloy steel component are improved, so that the product quality is improved, the energy consumption is reduced, and the production period is shortened.

The invention discloses an electrical cabinet condensation defense method and system based on environmental parameter monitoring. The method comprises the following steps: acquiring temperature and humidity information of multiple points in an electrical cabinet and outside the cabinet in real time; calculating a dew point temperature and a condensation risk index in the cabinet; predicting the lowest temperature and humidity change rate in the cabinet in the next time period in the control period; based on the minimum temperature and humidity change rate prediction value in the cabinet and the current condensation risk index, whether the electrical cabinet meets the condensation risk trend criterion is judged, if yes, the electrical cabinet enters a condensation risk suppression linkage control mode, and if not, the electrical cabinet enters a condensation risk defense self-adaptive mode; and in the condensation risk suppression linkage control process, when the current condensation risk index of the electrical cabinet is lower than a condensation risk index threshold value, entering a condensation risk defense self-adaptive mode, and otherwise, entering a next control period. Data acquisition is comprehensive and accurate, the dew point temperature can be accurately calculated, the control strategy is intelligent and flexible, equipment can operate according to needs, condensation is effectively prevented, and the energy-saving effect is remarkable.

The invention discloses a data center machine room AI energy-saving control method and system, a digital twin model of a machine room operation state is constructed through a holographic perception and heterogeneous data fusion technology, centimeter-level monitoring of an equipment state and environmental parameters is realized, and the system integrates a laser radar array, an acoustic sensor and a gas sensor network. The time-space alignment of multi-modal data is completed by combining edge computing nodes, holographic mapping including thermodynamic characteristics, vibration characteristics and gas leakage risks is formed, historical temperature control strategy characteristics are extracted by adopting a variational auto-encoder based on a dynamic strategy generation mechanism of generative artificial intelligence, and a load trend is predicted by combining a long-short-term memory network. Constructing a self-adaptive strategy pool; the multi-agent reinforcement learning framework enables temperature control, equipment scheduling and power grid response to form game optimization, the strategy robustness in a complex scene is improved, and the system innovatively fuses power grid real-time electricity price and carbon transaction data so as to establish a multi-target decision system.

The invention relates to the technical field of flexible circuit board production, in particular to a process optimization method and system for a flexible circuit board production line. The method comprises the following steps: acquiring characteristic data of a flexible circuit board material; executing a circuit board thermocuring action according to the material characteristic data of the flexible circuit board, performing thermal stress intensity evaluation, and generating stress hot spot distribution data; performing real-time curing temperature control feedback adjustment according to the stress hotspot distribution data to obtain circuit board curing effect evaluation data; detecting a real-time surface wettability index of the to-be-processed flexible circuit board in front of the laminating station; and fitting process parameter compensation is carried out based on the circuit board curing effect evaluation data and the real-time surface wettability index so as to realize curing-fitting process optimization of the flexible circuit board production line. According to the invention, intelligent optimization of the curing-laminating process of the flexible circuit board production line is realized, and the quality problems of uneven stress and overlarge deformation in the thermocuring-laminating process are effectively solved.

The invention provides a power plant heat tracing system intelligent optimization method based on environment temperature fluctuation, and relates to the technical field of temperature control of a power plant heat tracing system, and the method comprises the following steps: S1, data collection and preprocessing: deploying a sensor array, collecting an operation data signal # imgabs0 # of a power plant heat tracing pipeline, carrying out the preprocessing of the operation data signal # imgabs1 #, and storing the preprocessed operation data signal # imgabs0 #; outputting a standardized feature vector; s2, model establishment and parameter optimization: constructing a physical-data dual-drive heat transfer model, and inputting standardized feature vector optimization initial parameters; compared with the prior art, the method has the following beneficial effects: firstly, control parameters can be automatically adjusted according to factors such as thermal load change, external environment temperature fluctuation and equipment aging; and secondly, the temperature trend in the future short time can be predicted by constructing a heat transfer dynamic model, the control strategy is adjusted in advance, the temperature is prevented from being out of control, heat dissipation can be increased in advance or heat source input can be adjusted in advance, and safe and efficient operation of the system is effectively guaranteed.

The invention discloses an electric ship battery pack temperature control method, and relates to the technical field of ship battery pack temperature control, and the method comprises the following steps: arranging a plurality of temperature sensors in a battery pack, monitoring the temperature data of each single battery in real time, and transmitting the temperature information of each single battery to a central processing unit in real time; through multi-sensor arrangement, heat conduction model calculation and intelligent cooling system scheduling, accurate temperature monitoring and dynamic adjustment of the electric ship battery pack are realized, real-time abnormal detection is ensured, and thermal runaway is prevented. The intelligent cooling system accurately adjusts cooling force according to temperature changes, and safety accidents are avoided. Meanwhile, a cooling strategy is optimized, energy consumption is reduced, system efficiency is improved, battery life is prolonged, sailing mileage is increased, maintenance cost is reduced, and long-term stable and efficient operation of the battery pack is ensured.

The invention relates to the technical field of EPP (foamed polypropylene) production and manufacturing, and discloses an EPP foaming process parameter optimization method which comprises the following steps: monitoring temperature field and pressure changes in real time, and judging whether a thermodynamic state deviates from a preset window or not; during deviation, constructing a multi-physics field coupling model to evaluate a bubble growth dynamic unbalance risk, and identifying micro-pore non-uniform distribution characteristics through multi-source sensing data fusion and frequency domain analysis; and judging whether the technological parameters are globally coordinated and regulated based on risks and characteristics, analyzing the heat transfer and heat radiation influence of the temperature control unit, quantifying the parameter regulation sensitivity and determining the regulation priority. The system comprises a thermodynamic monitoring module, a dynamic coupling analysis module and the like. According to the invention, real-time monitoring, accurate analysis and intelligent regulation and control of the EPP foaming process are realized, the process stability and the product quality are improved, and the method is suitable for the field of EPP production and manufacturing.

The invention relates to the field of electromagnetic induction heating, and discloses a global temperature control method for an electromagnetic induction heating system, which comprises the following steps of: acquiring a two-dimensional temperature distribution diagram of a heating area at a plurality of key moments through a multi-point infrared temperature acquisition and induction heating coil synchronous excitation mechanism; performing multi-dimensional region segmentation on the global temperature scene data set, and identifying a temperature abnormal region and a thermal diffusion path feature based on a boundary thermal gradient change rate and an energy transfer path analysis algorithm; a distributed power regulation and control method and a historical thermal field evolution rule are introduced based on the regional thermal response feature map; thermal field feedback information is collected in real time in the temperature control process, and the current global thermal field state is judged in combination with a thermal distribution stability judgment criterion; and based on the updated control parameter configuration table, in combination with the thermal performance parameters of the material and the geometric information of the workpiece, generating an operation instruction set of the heating process, and executing intelligent regulation and control. The induction heating device has the advantage of improving the induction heating quality.

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

The invention relates to the technical field of computers, in particular to a temperature control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an estimated temperature of a heat dissipation part based on a pre-established physical model, and obtaining an actual temperature of the heat dissipation part based on the estimated temperature and the actual temperature of the heat dissipation part; judging whether parameters of a pre-established physical model meet preset updating conditions or not; if the parameters of the physical model meet preset updating conditions, the parameters of the pre-established physical model are updated, and based on the updated parameters, regulation and control parameters of a proportional integral differential controller are determined according to a preset objective function, so that the proportional integral differential controller controls the operating temperature of the server based on the regulation and control parameters. Therefore, the problems that in PID regulation and control of the server fan, parameter setting depends on artificial experience, efficiency is low, subjectivity is high, and power consumption, noise and heat dissipation performance cannot be effectively balanced in the prior art are solved, and effective control over the temperature, the power consumption and the noise of the server is achieved.

The invention relates to the technical field of cable production automation control, and provides a crosslinked cable production control method based on an improved PID (Proportion Integration Differentiation) control algorithm, which comprises the step of constructing an optimal reference model by establishing a cooperative control framework of temperature, pressure and traction speed and taking the temperature of a vulcanization pipe as a main control variable and the pressure and the traction speed of an extruder as slave control variables. A main controller tracks a temperature set value in real time, PID parameters are dynamically set according to technological parameters such as the thickness deviation of an insulating layer and the crosslinking degree of a material, and precise control is achieved through a three-ring cooperative coupling improved PID controller. A temperature control ring enables the steady-state error of the actual temperature and the set value to be converged to zero. The pressure and speed control loop converges the fluctuation amplitude to a process allowable range. The temperature stability, the pressure uniformity and the traction synchronism of crosslinked cable production can be improved, the process fluctuation and the defect rate are reduced, and the product quality and the production efficiency are improved.

The invention discloses a temperature control management method for an electric oven, and relates to the technical field of intelligent household appliance control, and the method comprises the steps: carrying out the offset correction of a pre-stored mode mapping table based on a calibration matrix, loading a target temperature interval and a three-dimensional temperature field partition parameter according to a cooking mode selected by a user, and triggering a dynamic learning mark; according to the dynamic learning mark, the furnace chamber temperature and the environment temperature change rate are collected in real time, the power compensation amount is calculated through a thermal inertia compensation model, and a partition power control matrix is generated in combination with the three-dimensional temperature field partition parameters; and distributing the power compensation amount and the partition power control matrix to the heating pipe according to a preset topology, dynamically adjusting power output, and implementing temperature early warning and no-load identification based on an acoustic emission spectrum entropy value. The temperature gradient change rate is calculated through the Fourier heat conduction law, the three-dimensional temperature field partition parameters are dynamically generated, and accurate control over the temperature field in the complex three-dimensional space is ensured so as to cope with environment changes and user demand changes.

The invention discloses an indoor temperature real-time regulation and control method of a heat distribution pipeline and a control system of the indoor temperature real-time regulation and control method, relates to the technical field of dynamic control of a heat distribution pipe network, and solves the problems of hydraulic oscillation and temperature control hysteresis caused by the fact that local valve regulation neglects whole-network coupling and a first-order linear model is difficult to describe multi-order thermal inertia and large heat capacity in the prior art. According to the scheme, on the basis of pipe network distributed PDE / lumped parameter hybrid modeling and in combination with extended Kalman filtering and unscented Kalman filtering on-line identification, a feedforward decoupling compensation item is generated through spectral decomposition, a self-adaptive multi-model predictive control and iterative learning compensation closed-loop structure is constructed, a control instruction is issued according to a pump-first and valve-second serialization strategy, and a self-adaptive multi-model predictive control and iterative learning compensation closed-loop structure is constructed. Meanwhile, the model weight and the prediction time domain are dynamically adjusted; according to the method, the global balance capability and the temperature tracking precision of heat distribution pipeline regulation and control are remarkably improved.

The invention discloses a temperature control method and system for Chinese food cooking based on multi-modal representation recognition, and relates to the technical field of temperature control for Chinese food cooking, and the method comprises the steps: carrying out the data collection through a sensor, and carrying out the preprocessing; analyzing the food state change, monitoring the food state change in real time, and performing multi-dimensional feature fusion; capturing texture dynamic characteristics, monitoring a cooking image, introducing a feedback variable, and controlling and adjusting the temperature; environment variables are monitored, and preference setting is carried out; analyzing the big data and user historical data; according to the method, comprehensive monitoring of multi-dimensional data such as temperature, humidity and color is realized through fusion processing of a multi-modal sensor, and accuracy and real-time performance of cooking data are ensured; by combining multiple technologies such as multi-modal sensor data fusion, big data analysis, time and space attenuation modeling and user preference setting, the food state is dynamically analyzed, the cooking stage is accurately judged, the temperature control strategy is optimized, and the extensive control problem of a traditional method is avoided.

The invention relates to the technical field of temperature control, in particular to an intelligent temperature control system for the whole cable production process. Comprising a cable parameter acquisition module, a production process modeling module, a temperature control decision module, an execution control module and a monitoring early warning module. According to the system, cable production parameters are collected, and a graph neural network and a symbolic regression algorithm are used for modeling production temperature distribution and a temperature-quality relation. And based on the model, an optimal temperature control strategy is generated by adopting reinforcement learning, and precise temperature control is realized through adaptive fuzzy control. Meanwhile, the system monitors temperature parameters in real time, early warning signals are sent out when abnormal detection, over-limit detection or equipment failure are detected in combination with sparse coding and variation inference, and the production stability and the product quality are ensured. According to the invention, through intelligent modeling, decision making, control and monitoring means, the temperature control precision and efficiency of the whole cable production process are comprehensively improved.

The invention discloses a constant-temperature and constant-humidity test box temperature control system based on a multistage PID algorithm and a control method thereof. The constant-temperature and constant-humidity test box temperature control system comprises an environmental parameter detection module, an in-box parameter detection module and a multistage PID controller, wherein the environmental parameter detection module is used for collecting temperature, humidity and air pressure data outside a test box in real time; the in-box parameter detection module is used for collecting multi-dimensional environmental parameters inside the test box; when the failure of any sensor is detected, starting a fault self-diagnosis module, replacing the data of the failure sensor with a data interpolation method of a side sensor, and recording the deviation compensation amount at the same time. A multi-stage PID control architecture is adopted, and feedforward compensation, parameter adaptive optimization and fault redundancy strategies are combined, so that high-precision and anti-interference control of the temperature and humidity of the test box is realized.

The invention relates to the technical field of kiln temperature control. The kiln temperature consistency control method comprises the steps that kiln internal environment information is input into a temperature change prediction model, temperature fluctuation trend information is obtained, kiln temperature control optimization parameters are generated according to the temperature fluctuation trend information, and the kiln temperature consistency is controlled according to the kiln temperature control optimization parameters. The current operation parameter is kept if the adjusted environment information conforms to a kiln temperature control target value, and the adjusted environment information is input into the temperature change prediction model again if the adjusted environment information does not conform to the kiln temperature control target value to generate a new kiln temperature control optimization parameter. And on the basis of the new kiln temperature control optimization parameter, the operation parameter in the kiln is adjusted again until the adjusted environment information accords with the kiln temperature control target value. The method has the effect of ensuring the consistency of the internal temperature of the kiln.

The invention relates to the technical field of roller cooling, and discloses a roller cooling temperature control method and system.The method comprises the steps that the length of a roller is obtained, and the roller is equally divided into N temperature monitoring areas according to the length of the roller; n pieces of detection temperature value data are obtained and preprocessed; inputting the detected temperature value data into a pre-trained state model for comparison, and obtaining a temperature prediction value; the optimal cooling water flow is calculated according to the temperature prediction value through an MPC controller; acquiring historical data of the roller, and inputting the historical data into the auto-encoder for reconstruction; inputting detection temperature value data collected in real time into the auto-encoder, and calculating a reconstruction error value; and determining a current cooling water flow control state based on the reconstruction error value, and compensating the cooling water flow to the MPC controller. The roller cooling efficiency is improved.

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.