92 results about "Temperature error" patented technology

The invention is suitable for the technical field of intelligent control, and discloses a water cooling control method, system and device and a medium. Based on the preprocessed data, constructing a thermal load trend prediction model based on LSTM to obtain a cold load prediction value; based on the cold load prediction value, a PID adjusting signal is generated in combination with the temperature error value; based on the PID adjusting signal, a water pump target frequency instruction is obtained in combination with the cooling load predicted value; based on the water pump target frequency instruction, a valve target opening instruction is obtained in combination with the actually-measured water flow; based on the valve target opening instruction, the fault alarm and emergency instruction is generated, the preset emergency measures are executed, the PID control parameters are updated, the performance evaluation report and the feedback information are obtained, and the response speed, the operation stability and the autonomous decision-making capacity of the water cooling system under the dynamic load and abnormal working conditions are improved.

The invention relates to the technical field of MEMS sensors, and discloses a temperature drift real-time compensation and correction method and system of an MEMS gyroscope. The method comprises the following steps: acquiring an original output signal and synchronous temperature time sequence data of the MEMS gyroscope under a preset temperature gradient, dividing a dynamic temperature change interval, extracting zero-bias stability and scale factor nonlinearity parameters, and constructing a temperature-error mapping table; checking output signals of multiple gyroscopes through array layout, and screening effective sensor nodes; and a multi-sensor fusion compensation coefficient matrix is generated by combining error calibration test weighted fusion parameters. A corresponding coefficient matrix is loaded according to a real-time temperature query mapping table, and a parameter weight is analyzed and updated by using a sliding time window residual error; when the temperature changes suddenly, an adaptive filtering optimization coefficient matrix is triggered, and finally optimization parameters are written into an embedded storage unit of the PCB integrated chip to complete mass production calibration. The method adapts to a dynamic temperature change scene, enhances the anti-interference capability, and adapts to a mass production process.

The invention relates to the field of oil field heating furnace control, and discloses an oil field heating furnace intelligent digital implementation method and control method.The control method comprises the following steps that S1, a temperature sensor is used for monitoring the temperature of an oil field heating furnace in real time; s2, calculating a temperature error between the upper limit and the lower limit of the real-time temperature and the set temperature according to the monitoring data of the temperature sensor; s3, a self-adaptive PID control algorithm is applied, and heating power is calculated based on the temperature error; and S4, dynamically adjusting the heating power to control the temperature of the oil field heating furnace. The precision and stability of temperature control can be improved, the oil field heating furnace can control the target temperature more accurately, and the production efficiency is improved. Meanwhile, the self-adaptive PID control algorithm can automatically adjust parameters according to actual working conditions and environment changes, the adaptability and robustness of the system are improved, and the requirements for manual intervention and adjustment are reduced. In addition, the stable and efficient heating process can be achieved by dynamically adjusting the heating power, and energy and cost are saved.

The invention discloses an automatic temperature compensation system and method for an ultrasonic transducer, and the method comprises the steps: carrying out the timely collection of the temperature through a temperature detection module, and carrying out the temperature error compensation of a pressure measurement result based on an environment temperature parameter; according to error characteristics of the digital temperature sensor, a characteristic threshold value is obtained based on a temperature compensation algorithm of an RBP neural network with nonlinear fitting capability and generalization capability, and then nonlinear error compensation in a temperature measuring range is completed by using the characteristic threshold value. The transition time of ultrasonic waves in a pipeline under any temperature and zero pressure serves as a training target value of an artificial neural network, drifting of the transition time at the zero pressure position is compared after training, the receiving waveform of the temperature change to the frequency mutation of the ultrasonic transducer under the zero pressure is calculated, the zero pressure position is locked, and the temperature change of the ultrasonic transducer is calculated. The frequency with the strongest signal is found out, the optimal working frequency of the ultrasonic transducer at the temperature is obtained, and temperature compensation of ultrasonic transit time is automatically completed through a temperature compensation module; according to the invention, the temperature compensation performance is reliable, the phenomenon of pressure drift caused by zero pressure ultrasonic transit time drift can be effectively avoided, and the final measurement error is effectively reduced.

The invention provides a multi-sensor-based welding temperature feedback control method and related equipment, and the method comprises the steps: carrying out the preprocessing of multi-dimensional temperature data collected in a welding region, and obtaining a multi-dimensional temperature feature vector; performing weighted fusion on the multi-dimensional temperature feature vectors to obtain an effective temperature feedback result of the welding area; based on the effective temperature feedback result, the environment temperature data and the welding speed, a target temperature curve is generated through a preset fuzzy rule; and iterative learning is carried out according to the target temperature curve and the effective temperature feedback result, temperature errors of all sampling moments are determined, and a welding output instruction is updated according to the temperature errors. Through the implementation of the scheme, fusion and weighting processing are performed on the multi-dimensional temperature data, and the effective temperature feedback result of the welding area can be generated, so that precise iterative adjustment of welding heat source output is realized, and the accuracy of heat source power regulation and control is effectively improved.

The invention discloses a control method, a control device, equipment and a medium of a semiconductor temperature control system, and the control method comprises the steps: firstly, collecting the working temperature of a to-be-detected object through a temperature detection module, and obtaining an error absolute value between the working temperature and a target temperature; when the error absolute value is larger than a preset temperature error threshold value, the output of the first proportional control unit, the output of the integral control unit and the output of the differential control unit are subjected to superposition processing and determined as coarse adjustment output control quantity; and when the error absolute value is smaller than or equal to a preset temperature error threshold value, at least determining the output of the integral control unit corresponding to the first moment as a fine adjustment output control quantity, and finally, according to the coarse adjustment output control quantity or the fine adjustment output control quantity, a semiconductor refrigeration module is driven to carry out temperature regulation and control. By means of the method, after the error absolute value enters the tiny preset temperature error threshold value, the fine adjustment algorithm is switched, and ultrahigh-precision constant temperature keeping is completed through optimized integral control and output amplitude limiting.

The application discloses a kind of multi-wavelength area array CCD pyrometer's calibration and noise analysis method, constructs temperature measurement calibration model, obtains the parameter that each channel R of CCD camera, G, B needs calibration;Solving the unknown parameter of calibration model, analysis calibration error;Construct noise analysis model, find out the unknown parameter of each channel R of CCD camera in noise analysis model, G, B;Quantitative analysis is carried out to the noise of each channel R of CCD camera, G, B by noise analysis model.The influence caused by each channel R of CCD camera, G, B noise is evaluated.The calibration model of pyrometer in the application is an innovative model, the error of each channel of pyrometer is very small when calibration is carried out under this model;The noise analysis method in the application can quantitatively analyze the noise of pyrometer, the gray value fluctuation caused by each noise can be solved by the method, and the temperature error caused by each noise can be analyzed.

The embodiment of the invention relates to a temperature compensation method and device and a readable storage medium, and the method comprises the steps: primary compensation: employing polynomial fitting to build a baseline model based on the original output values of a plurality of groups of MEMS pressure sensors and the surface temperature value of a lithium ion battery, and obtaining the primary compensation output values of the MEMS pressure sensors; dynamic compensation: pre-establishing a database for acquiring a relationship between an internal temperature value of the lithium ion battery and a temperature dynamic compensation coefficient of the MEMS pressure sensor, and calculating a dynamic compensation output value of the MEMS pressure sensor based on the primary compensation output value and the temperature dynamic compensation coefficient; feedback calibration: periodically acquiring the deviation between the measured value and the predicted value of the voltage polarization amplitude of the lithium ion battery, and automatically and reversely correcting the baseline model; according to the invention, the temperature error of the MEMS pressure sensor is dynamically compensated by constructing a multi-stage compensation system and voltage polarization amplitude characteristics.

The utility model discloses a three temperature error code appearance with case and three temperature error code appearance, three temperature error code appearance with case includes shell and liquid leakage sensor, the shell includes bottom plate and bearing, and a plurality of bearing fixed settings are in bottom plate, are used for bearing electrical element, and liquid leakage sensor sets up in bottom plate, and the detection end of liquid leakage sensor forms the measurement interval with the upper surface of bottom plate, and the measurement interval is less than the height of bearing. Three temperature error code appearance includes three temperature error code appearance with case and electrical element, and the electrical element sets up in bearing. Compared with prior art, the utility model provides three temperature error code appearance with case through setting up bearing electrical element, and the height of electrical element is lifted, avoids the contact of electrical element and water in the initial stage of water leakage, sets up liquid leakage sensor and discovers water leakage failure in time, and electrical element is powered off protection rapidly, and the damage of electrical element and the loss of data are avoided to the maximum.

This invention discloses an intelligent temperature control system and method for heavy-duty truck disc brakes, relating to the field of heavy-duty truck braking systems. The control system comprises a brake disc, a micro-vortex tube array, a dual-channel rotary sealing module, a MEMS temperature-wind speed sensing network, a high-speed pressure-flow proportional valve group, and a vehicle domain controller. The MEMS sensing network collects real-time data on the brake disc friction ring temperature and convective wind speed. The domain controller predicts the temperature rise trajectory using a thermo-mechanical coupling model. When the temperature exceeds a threshold, cold-end and hot-end coordinated cooling is initiated. A pulsed airflow from the cold end sweeps tangentially across the friction surface via an air knife to strip away the hot layer, while a micro-airflow from the hot end is injected into the backplate air guide groove to eliminate thermal stress gradients. The flow rates of the two airflows are decoupled and distributed online by the proportional valve based on temperature error. This invention requires no modification to the brake caliper structure, is compatible with ABS / EBS protocols, suppresses heat fade, extends lining life, and improves braking safety margin.

The invention discloses a hot air comb double-area constant temperature control system based on temperature induction, and relates to the technical field of temperature regulation and control, and the system comprises a temperature monitoring module which is used for collecting the real-time temperature data of a hot air comb in real time; the control core module comprises an area identification unit and a temperature control unit; the area identification unit is used for distributing area characteristic labels for different heating areas of the hot air comb; the temperature control unit is used for receiving the real-time temperature data and calculating a control signal for adjusting the power of the heater; and the driving execution module is used for adjusting the power of the heating element in the corresponding area through an independent power channel according to the received control signal. The method has the advantages that the problem of non-uniform heat distribution caused by a physical structure of the hot air comb is effectively solved by setting double-area independent constant-temperature control and introducing a multi-state intelligent judgment mechanism based on the size of a temperature error signal, a change trend and an area characteristic label; and the temperature control precision and stability of the tip sensitive area are obviously improved.

The invention relates to the technical field of medical instruments, in particular to a cavity pressure and temperature cooperative control method, a cavity pressure and temperature cooperative control system and perfusion equipment. The control module increases the suction flow of the suction device according to the temperature error so as to reduce the actual temperature in the operation cavity; and the control module increases the perfusion flow of the perfusion device based on the pressure change amount in the operation cavity caused by the increase of the suction flow so as to compensate the pressure in the operation cavity.

This invention provides a method for full-temperature error self-calibration of intelligent fusion terminals based on digital twin transfer, belonging to the field of intelligent fusion terminal power metering technology. It includes: selecting sample terminals for multi-condition data acquisition across the entire temperature range; establishing a common error baseline model for the population using Gaussian process regression; extracting individual deviation features at room temperature and individual deviation labels for the full temperature range from the sample terminals; training a transfer mapping network from room temperature deviation to full temperature deviation based on XGBoost; performing a single-point self-test at room temperature on the terminal to be shipped and extracting room temperature deviation features; inputting the room temperature deviation features into the transfer mapping network to predict individual deviations at the full temperature range; algebraically superimposing the population baseline and individual deviations to reconstruct the full-temperature compensation coefficient table and burning it to the terminal; and completing self-calibration by interpolating the table based on real-time temperature during terminal operation. This invention, through the fusion of population commonality separation and individual deviation transfer mapping, can reconstruct the full-temperature compensation curve of the terminal based on single-point data at room temperature.

The invention discloses an intelligent control system for liquid PTC heater production, and relates to the technical field of heater production, and the system comprises a state sensing module which collects the mold temperature, the target curing temperature, a slurry injection trigger signal, the slurry initial temperature and other parameters in real time; the predictive thermal compensation module calculates feed-forward compensation power based on the target curing temperature and the slurry initial temperature to resist thermal shock; the self-adaptive PID feedback control module dynamically judges the operation stage of the system according to the temperature error and the mold temperature change rate, and calls corresponding gain configuration to generate feedback power; the power output execution module superposes the feed-forward compensation power and the feedback power to generate total target power and drive the heating assembly, through the synergistic effect of feed-forward compensation and self-adaptive PID control, the temperature stability and the product quality consistency are remarkably improved, meanwhile, the system response speed and the energy consumption efficiency are optimized, and the system reliability is improved. The method has the characteristics of clear logic and easy implementation, and is suitable for various production conditions and environment requirements.

The invention provides a temperature control method and system based on flexible production line spraying and drying, and the method comprises the steps: training a lightweight LSTM network through obtaining the in-furnace temperature, the target drying temperature, the workpiece type and the heating power at the next moment under different working conditions; the temperature in the furnace and the target drying temperature are obtained in real time, the temperature error and the error change rate are calculated, according to a double-threshold switching rule, one of the trained lightweight LSTM network or PID is called, heating power is output, and the temperature is controlled; when the trained lightweight LSTM network and the PID need to be switched, judging whether a difference value between the heating power output by the lightweight LSTM network and the heating power output by the PID is greater than a preset value or not; if yes, the total transition time is calculated according to the difference value, the thermal characteristics of the workpiece and the total mass of the workpiece, then a nonlinear transition curve is defined, and transition of the heating power is conducted according to the total transition time and the nonlinear transition curve.

The present application relates to the technical field of temperature control, and discloses a roller kiln temperature monitoring system and method. The method comprises the following steps: dividing temperature sensing data of a temperature sensing optical fiber and measured temperature data of a temperature sensing module into a training set and a test set according to time sequence of generation; segmenting the temperature sensing optical fiber, constructing a fiber heat conduction model, and setting a bias value for the fiber heat conduction model corresponding to each segment of the temperature sensing optical fiber; calculating error values between the temperature sensing data of each segment of the temperature sensing optical fiber and the measured temperature data of the temperature sensing module according to the fiber heat conduction model and the set bias value, and obtaining temperature error values; re-determining the bias value through a machine learning optimization algorithm; and outputting the temperature sensing data, coordinate information corresponding to the temperature sensing data and generation time according to the fiber heat conduction model and the optimized bias value. In this embodiment, a fiber heat conduction model is constructed through distributed optical fiber sensing detection technology, so as to obtain temperature field data of each position of a roller kiln lining.

The application discloses a design method of a fiber sensor for realizing strain and temperature decoupling, wherein a first period of a Bragg fiber grating and a second period determined by the sum of the length of the Bragg fiber grating and the length of the fixed interval are taken as the output of the design; if the temperature error and the strain error derived by using the spectral first characteristic peak central wavelength and the spectral second characteristic peak central wavelength of the fiber sensor are less than the given temperature measurement allowable error and the strain measurement allowable error, the values of the first period corresponding to the spectral first characteristic peak wavelength and the second period corresponding to the spectral second characteristic peak wavelength are taken as the output. The design method provided by the application can obtain the processing parameters of the fiber sensor which can satisfy the given strain and temperature allowable error, thereby improving the precision of the fiber sensor. Other embodiments of the application provide a measuring device using the obtained fiber sensor and a measuring method based on the measuring device.

The application provides a semiconductor equipment disturbance prediction and control method, system, device and medium, the method comprising: first, presetting the mapping rule between the process instruction and the disturbance event, analyzing the process instruction in the process recipe during the operation of the semiconductor equipment; screening the disturbance instruction based on the look-ahead window mechanism, converting the disturbance instruction into the disturbance event, and generating the corresponding disturbance prediction curve; generating a plurality of feedforward compensation components based on the disturbance prediction curve, superimposing the feedforward compensation components, obtaining the comprehensive feedforward compensation control quantity, mapping each comprehensive feedforward compensation control quantity to the prediction time axis, and obtaining the feedforward compensation curve; calculating the temperature error based on the current temperature value and the target temperature of the temperature control system, and obtaining the feedback control quantity combined with the PID algorithm; superimposing the comprehensive feedforward compensation control quantity and the feedback control quantity to obtain the final control output quantity, and sending the final control output quantity to the temperature control system to drive the heating or cooling device.

The present disclosure relates to a motor stator temperature measurement method and device and a vehicle, comprising: obtaining a motor rotor speed and a motor phase current; determining a first temperature and an impedance of the motor stator according to the speed and the phase current, wherein the first temperature and the impedance of the motor stator are calibration values; calculating a temperature error caused by heat loss of the motor stator as a temperature correction value through the first temperature and the impedance of the motor stator; determining a second temperature according to the temperature correction value and motor stator temperature sensor measurement data, and taking the second temperature as an actual temperature of the motor stator. In this way, the measurement data obtained by the temperature sensor of the motor stator can be corrected through the measurement of the motor speed and the phase current, so that the actual temperature obtained can more accurately reflect the temperature of the driving motor, avoiding the problem of inaccurate measurement of the motor stator temperature caused by the motor speed and the position of the temperature sensor.

The embodiment of the invention provides an air conditioner temperature correction method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: acquiring state information at a current moment, wherein the state information comprises an initial environment temperature collected by a temperature sensor and a screen-on state of a display screen; determining a corresponding temperature compensation value according to the state information; according to the initial environment temperature and the temperature compensation value, the corrected environment temperature at the current moment is obtained; and the air conditioner operates according to the corrected environment temperature. The indoor initial environment temperature is collected through a temperature sensor of the air conditioner, state information such as the bright screen state of a display screen is obtained, a temperature compensation value corresponding to the current moment is determined according to the state information, and the initial environment temperature is corrected based on the temperature compensation value; by means of the mode, the temperature error caused by heating of the temperature sensor is reduced, and therefore the accuracy of environment temperature detection is guaranteed.

The invention discloses a temperature control method and device based on a wild horse optimized BP neural network PID, and a storage medium. The temperature control method and device are suitable for the precise temperature control requirement of a biological liquefaction device for livestock died of illness. The method comprises the following steps: establishing a system mathematical model in which an inertia link and a delay link are connected in series; optimizing the initial weight and the threshold value of the BP neural network by adopting a wild horse optimization algorithm, and evaluating the effect by taking the temperature error, the adjustment time and the overshoot as indexes; pID parameters are dynamically adjusted through the optimized BP neural network, data interaction is achieved in combination with the OPC technology, and integral anti-saturation processing is carried out; and the control device outputs a 0-10V signal to drive the execution mechanism to form closed-loop control. The device comprises a Siemens S7-200 Smart PLC, a PT100 sensor, a silicon controlled voltage regulator and the like, and the storage medium stores a computer program for realizing the method. According to the invention, the problems of large overshoot of the traditional PID and easy local optimum of the BP neural network are solved, and the temperature control precision and robustness of a large-time-lag nonlinear system are improved.

The invention relates to the technical field of intelligent control, in particular to an intelligent control system and method for a machining center clamp. The system comprises an acquisition processing unit, an evaluation control unit and a signal conditioning unit. The evaluation control unit calculates membership functions of normalized clamping force, displacement and temperature data in different intervals, then evaluates whether the working state of the center clamp is normal or not, sets clamping force, displacement and temperature thresholds when the working state is abnormal, calculates clamping force, displacement and temperature errors in combination with the normalized clamping force, displacement and temperature data, and finally evaluates whether the working state of the center clamp is normal or not. Then historical data is obtained from the database, clamping force, displacement and temperature control coefficients are respectively calculated in combination with clamping force, displacement and temperature errors, the abnormality of the working state of the clamp can be found in time by calculating a membership function and comprehensively evaluating the working state, and the situation that the machining precision of the clamp is affected due to the fact that the abnormal working state is not found in time is avoided.

The invention discloses a full-temperature-range dynamic temperature monitoring method and equipment based on a combined sensor, and relates to the field of temperature monitoring. Comprising the following steps that S1, two side holes are reserved in a side plate of a heating furnace to be subjected to temperature measurement in a penetrating mode, and two five-point thermocouples are inserted into the two side holes in a penetrating mode correspondingly; s2, a top plate of the heating furnace penetrates through the two top holes, the two infrared thermometers penetrate through the two top holes correspondingly, and the two infrared thermometers detect the temperature of the rotating table; s3, the lower computer collects temperature change data of all monitoring points; s4, a temperature standard value is set, and if the temperature of each monitoring point position is within a first temperature error standard, the state is normal; s5, a temperature error value is set, if the temperature error value is larger than the actual error value, the state is normal, and if the temperature error value is smaller than the actual error value, an alarm is given; and S6, if the state in the step S4 and the state in the step S5 are normal, the temperature in the heating furnace meets the production requirement, and therefore the problem that temperature change data of the same position at different time cannot be reflected in real time is solved.

The utility model relates to a temperature measuring structure of a vacuum furnace. The flange is arranged on a furnace body; the pressing nuts are uniformly mounted on the flange; the pressing pad is matched with each pressing nut for use; the sealing ring is sleeved on each pressing nut and pressing pad assembly; the temperature measuring thermocouple wires penetrate through the centers of the pressing nuts and the pressing pads; the temperature measuring flange seat is connected to the furnace body; the fixing piece is used for firmly connecting the flange with the temperature measuring flange seat; the temperature measuring frame is placed in the furnace body; the flange is provided with nine temperature measuring thermocouple wires, eight of the nine temperature measuring thermocouple wires are respectively distributed at eight vertex positions of the temperature measuring frame to form symmetrical distribution, and one of the temperature measuring thermocouple wires is located at the center in the temperature measuring frame. The technical problem that in the prior art, when an old-fashioned temperature measuring structure is used for coping with a complex thermal environment in a furnace body, the heating condition of all areas of a workpiece in the heat treatment process cannot be accurately measured, and the measured temperature error is large is solved.

Methods and systems for controlling vertical glass distribution are provided. A traversing pyrometer periodically measures a parison actual temperature after the parisons exit a blank mold. The thermal camera takes a thermal image of each glass container after the glass container exits the blow mold. A vertical glass signature extraction module extracts a vertical glass distribution signature. A parison temperature estimator determines a parison estimated temperature for each vertical glass distribution signature obtained based on the vertical glass distribution signature, a most recently measured parison actual temperature and a parison stretch time. A parison temperature summer compares the parison estimated temperature to a parison set point temperature to determine a parison temperature error. A parison temperature control controls a blank mold contact time based on the parison temperature error.

The invention discloses a gyroscope temperature error compensation method and device based on a gray nonlinear regression model, and the method comprises the steps: building a gyroscope zero offset temperature error model and a gyroscope scale factor temperature error model; integrating the gyroscope zero offset temperature error model and the gyroscope scale factor temperature error model to obtain a gyroscope temperature overall error model; according to the gyroscope temperature overall error model, obtaining a gyroscope error coefficient based on full temperature calibration so as to obtain a compensated initial output value of the gyroscope; constructing a first sequence fitting equation based on a gray nonlinear regression model for each axis initial output value of the initial output values of the gyroscope; and solving each parameter in the first sequence fitting equation, and substituting each solved parameter into the first sequence fitting equation to obtain a compensated target output value of each axis of the gyroscope. The gray nonlinear regression model solves the problems of insufficient adaptability to complex temperature change and limited compensation precision in the prior art, and realizes more accurate compensation for high-order term residual errors.

The invention relates to the technical field of temperature monitoring, and particularly provides a temperature estimation method, which comprises the following steps: acquiring running state data of a monitored object; the running state data serve as model input, the final temperature value of the monitored object is estimated according to a temperature estimation model, the temperature estimation model comprises a thermal resistance neural network model and a sensor neural network model, and the sensor neural network model is used for compensating temperature errors caused by the characteristics of a sensor; and correcting the output temperature of the thermal resistance neural network model to obtain a final temperature value of the monitored object. The invention further provides electronic equipment and a computer storage medium. According to the technical scheme, the problem that temperature estimation of the monitored object is inaccurate due to the hysteresis defect of sensor detection is solved, errors caused by the part of sensor detection can be compensated through the technical scheme, and therefore the temperature estimation accuracy of the monitored object is improved.

The utility model relates to the field of hydrothermal drying equipment, in particular to full-automatic hydrothermal circulation constant-temperature drying equipment which comprises a drying room, a control system and a heating system, the control system is used for a user to set data and control the heating system, and the heating system is used for controlling the temperature and the humidity in the drying room. The temperature and the humidity in the drying room can be accurately and uniformly controlled, so that the drying temperature error of + / -2 DEG C and the humidity error of + / -5 DEG C are reduced. And the influence of unstable temperature on the quality and color of a dried object is avoided. Water vapor is adopted for heat transfer, the efficiency is high, and the highest drying temperature is guaranteed. The heat can be quickly and uniformly transferred to the articles in cooperation with an automatic fan, so that the drying efficiency is improved, and the quality of the dried articles is improved.

The invention relates to the technical field of heat dissipation regulation and control, in particular to a server heat dissipation regulation and control method and device and a medium. The method comprises the following steps: acquiring a core temperature, an accumulative error and a task vector containing the characteristics of instruction composition, floating point density and the like; predicting an expected heat flux based on the model, calculating a thermal penalty factor positively correlated with an accumulative error, and generating a scheduling scheme by taking the heat flux accounting for penalty in a balanced manner and total execution time as targets; an integral step length inversely proportional to the temperature error change rate is set to calculate an accumulative error; predicting a temperature track through a first-order heat conduction model by using heat flux, and taking an initial slope as a differential item; and calculating a proportional gain associated with the expected heat flux and the accumulative error, and summing each control quantity to generate a heat dissipation control instruction. According to the scheme, local hot spots can be avoided, the control predictability is enhanced, and stable and coordinated temperature regulation is realized.

The application relates to the technical field of engineering machinery, in particular to an oil path anti-blocking control method, device and system and an asphalt station. The method comprises the following steps: acquiring a temperature error of material; determining a reference output frequency of an oil pump in a burner based on the temperature error; dynamically converting the reference output frequency to generate a dynamic output frequency; and controlling the output frequency of a frequency converter of the oil pump in the burner based on the dynamic output frequency. The method determines the reference output frequency of the oil pump in the burner based on the temperature error, thereby ensuring that the temperature of the material is controlled in a controllable and accurate range, the reference output frequency of the oil pump is dynamically converted, the rotating speed of the oil pump is changed with the frequency, pressure fluctuation is formed in the oil path of the burner, the effect of pressure pulse is achieved in the oil path, and automatic cleaning and anti-blocking of the oil path of the burner are realized.