163 results about "Temperature error" patented technology

The invention discloses a belt type roasting machine operation control method and system. The method comprises the steps that roasting machine operation control parameters including the material level, the fan rotating speed and the air bellow temperature target value are set; collecting the blanking amount, the machine speed, the material level and the temperature measurement values of the roasting section air bellow and the soaking section air bellow in real time; calculating a speed target value based on the blanking amount change rate and the material level error, and dynamically adjusting the speed of the trolley; and a fuzzy control strategy or a regular control strategy is selected according to the blanking fluctuation state, the historical control mode and the fan-speed matching degree. In the fuzzy control mode, slope characteristics are extracted through temperature curve fitting, fuzzy decision is carried out in combination with temperature errors, and the fan rotating speed adjustment amount is output; and in the rule control mode, the fan rotating speed adjustment amount is determined according to a predefined rule table. And finally, the fan target rotating speed is updated according to the fan rotating speed adjustment amount, and the rotating speeds of the main induced draft fan and the backheating fan are adjusted according to the fan target rotating speed. The stability of thermal parameters of the belt type roasting machine can be improved.

The invention discloses a dynamic digital compensation method for the metering error of wide-temperature-interval electric energy meter equipment, and the method comprises the steps: collecting the metering error data of the equipment at different temperatures through a temperature sensing module, so as to construct a historical temperature-error relation library; training an adaptive compensation model based on a historical temperature-error relation library to establish a nonlinear mapping relation between the temperature and the error; in the real-time operation process of the equipment, the current equipment temperature is collected through a temperature sensing module, and the current equipment temperature and the real-time load rate are input into the self-adaptive compensation model to obtain error correction; and the metering result is dynamically adjusted in real time according to the current equipment temperature and the error correction amount so as to output a compensated accurate metering value. According to the method, a temperature sensor does not need to be newly added, dynamic error correction is realized only by utilizing the existing temperature sensing capability of equipment, the metering precision and stability in a wide-temperature environment can be improved, the comprehensive cost is reduced, and the high-precision metering requirements in special environments such as extremely cold and high temperature environments are met.

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 provides a real-time calibration method and system for an inertial measurement unit, and a terminal, and the method comprises the steps: carrying out the first correction of an acceleration measurement value and an angular velocity measurement value which are output by a to-be-calibrated inertial measurement unit and are obtained in real time based on a temperature error compensation data table, and carrying out the second correction through employing a multi-sensor fusion filtering algorithm; on one hand, a temperature variable is introduced to carry out a multi-temperature zero offset test and a multi-temperature multi-axis rotation excitation test, a temperature error compensation data table is established, and the influence of temperature on the performance of the to-be-calibrated inertial measurement unit is fully considered; on the other hand, a multi-sensor fusion filtering algorithm is adopted, interference of vibration noise can be suppressed, the attitude calculation precision of the to-be-calibrated inertial measurement unit is improved, and therefore the calibration precision of the to-be-calibrated inertial measurement unit is guaranteed; the technical problems that an existing inertial measurement unit calibration method is low in calibration precision and poor in real-time performance are solved.

The invention discloses a fuzzy neural network PID photovoltaic series welding temperature control method based on improved PSO optimization. The method comprises the steps that a target photovoltaic series welding equipment heating transfer function model is acquired; setting an initial PID parameter; adjusting a PID increment parameter of the PID control module in real time according to the temperature error, the temperature error change rate and a preset fuzzy rule base; the neural network is combined with fuzzy control, and parameters and rules of fuzzy control are automatically modified through training data; according to the photovoltaic series welding temperature condition, the fitness function of the PSO algorithm is improved, the adjustment mode of the inertia weight is improved, and the improved PSO algorithm is used for optimizing the initial PID parameters of fuzzy neural network PID photovoltaic series welding temperature control. Self-adaptive precise control and robust control of the welding temperature control system are achieved, the temperature fluctuation phenomenon in the photovoltaic series welding process is effectively improved, and the robustness and control reliability of the system are enhanced.

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 a data center air conditioning equipment control method and system. Comprising the steps of obtaining a first environment temperature and a second environment temperature of a target space where the data center air conditioning equipment is located at a first sampling moment and a second sampling moment, and determining a temperature error and an error change rate of the target space at the first sampling moment by combining an expected environment temperature, the temperature error and the error change rate serve as target input variables to be matched with a preset fuzzy rule base, a target output fuzzy set is obtained, defuzzification processing is conducted on the target output fuzzy set, and a corresponding target output variable is obtained; and a control signal is determined according to the temperature error, the error change rate and the target output variable, and equipment operation parameters of the data center air conditioning equipment are adjusted through the control signal. The technical problem that the effect of controlling the equipment operation parameters of the data center air conditioning equipment through the control signals generated through the fixed PID parameters is poor is solved.

The invention provides a PI control method and device for laser soldering based on observation compensation, a controller and a program product, and the method comprises the steps: building a laser soldering thermodynamic model containing a thermal disturbance term based on a lumped parameter method, and constructing a state-space equation; designing a state observer based on the state-space equation, and estimating a state variable of the state-space equation and external disturbance acting on the state variable in real time; calculating a feedforward control quantity according to a target temperature curve and the thermodynamic model, calculating a compensation control quantity according to a disturbance value estimated by an observer, and calculating a PI control quantity according to the deviation between the output temperature and the target temperature to obtain a total control quantity; and in each sampling period, the total control quantity is dynamically adjusted according to the deviation between the current welding spot temperature and the target temperature, so that the temperature error tends to zero. According to the method, the disturbance observation technology and the feedforward-PI control are combined, and high-precision and high-robustness control over the welding temperature is achieved.

The invention provides a temperature control method of a power battery, electronic equipment and a storage medium, and the method comprises the steps: determining a temperature error value and an error change rate value of the power battery based on a temperature value of the power battery and a set temperature value; based on the temperature error value and the error change rate value of the power battery, determining an error expansion and contraction factor and a PID expansion and contraction factor; inputting the error scaling factor and the PID scaling factor into a fuzzy controller to determine a PID target correction coefficient; and inputting the PID target correction coefficient into a PID controller to obtain a target temperature value output by the PID controller, so that the power battery temperature control execution system adjusts the temperature of the power battery.

The invention provides a boiler wall temperature prediction method and system based on deep learning. The method comprises the steps of obtaining characteristic parameters related to boiler wall temperature and prediction parameters during boiler operation; dividing the feature parameters and the prediction parameters into a training set, a verification set and a test set; constructing a boiler wall temperature prediction model; the boiler wall temperature prediction model comprises an empirical mode decomposition module, a deep learning module and an error correction module, the empirical mode decomposition module is used for decomposing prediction parameters into a plurality of component sequences, the deep learning module is used for predicting the boiler wall temperature according to the component sequences, and the error correction module is used for correcting the predicted boiler wall temperature; using the training set to train the boiler wall temperature prediction model, and adjusting the boiler wall temperature prediction model through the verification set; and evaluating the boiler wall temperature prediction model by using the test set, and if an evaluation result meets a preset standard, deploying the boiler wall temperature prediction model into an operation monitoring system of the boiler to predict the boiler wall temperature, thereby realizing accurate prediction of the boiler wall temperature.

The invention discloses a compensation thermal resistance regulation and control method applied to relay thermal network modeling, and belongs to the technical field of thermal modeling in an electromagnetic and thermal coupling system. The method is used for solving the problems that a traditional thermal network model is inaccurate in local temperature field prediction and difficult in hot spot recognition in relay thermal analysis. Comprising the steps of S1, establishing a thermal network model of a relay structure; s2, a compensation thermal resistance unit is inserted, and a T-type network is established; s3, solving a two-dimensional Poisson equation to obtain an average temperature; s4, comparing the average temperature with the node temperature in the thermal resistance network; iteratively adjusting the compensation thermal resistance unit until the temperature error of the compensation thermal resistance unit and the compensation thermal resistance unit is within an acceptable range; and S5, the calibrated model is operated, and the steady-state temperature is output. The introduction of the compensation thermal resistance is mathematically equivalent to the addition of a reverse heat flux regulator, so that the node temperature can be approximate to the two-dimensional integral average temperature, the distortion of the thermal network in a local two-dimensional region is effectively corrected, and the reflection capability of the model to local hot spots and temperature gradients is remarkably improved.

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 temperature control method of an infrared polarized light therapeutic instrument, and relates to the technical field of medical instruments and intelligent control. Temperature errors and related historical time sequence data are processed in real time through a pre-trained thermal load dynamic identification model; the state characterization quantity reflecting the heat exchange efficiency between the current probe and the external environment can be accurately output; the characterization quantity is not an abstract signal, but contains parameters with definite physical significance, such as an equivalent thermal time constant, contact thermal resistance or an effective heat exchange coefficient, so that the control system can deeply perceive the state of the control system and does not depend on delayed temperature deviation to react; therefore, when the treatment probe moves on the surface of a human body, goes through working conditions which cause step-type change of the thermal load from suspension to close contact, or slides under different pressures and the like, the controller can identify the dynamic change trend nearly in real time.

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 application provides a temperature sensor calibration method, device, computing equipment and storage medium. The temperature sensor is arranged in a chip. The temperature sensor calibration method comprises the following steps: arranging the chip in multiple working modes respectively; acquiring an external reference temperature, a power consumption value of the chip and a temperature measurement value of the temperature sensor in each working mode; calculating a temperature error between the temperature measurement value of the temperature sensor and the external reference temperature; performing fitting processing on the temperature error and the power consumption value, and obtaining a fitting curve; and calibrating the temperature sensor according to the fitting curve. Through the calibration method, the influence of the power consumption of the chip on the calibration accuracy of the temperature sensor can be eliminated, and accurate calibration results can be obtained.

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.

The invention relates to a battery pack temperature monitor, and belongs to the field of battery temperature monitoring, the battery pack temperature monitor comprises a mounting shell, the mounting shell is clamped on a battery pack cover plate of a battery pack assembly, one end, close to a battery cell of the battery pack assembly, of the mounting shell is detachably connected with a fixing shell, and the fixing shell is provided with an elastic piece; the side, deviating from the fixing shell, of the elastic piece is in contact with the inner wall of the mounting shell, a heat conduction shell is arranged in the fixing shell, a temperature sensor is arranged in the heat conduction shell, and the side, deviating from the fixing shell, of the heat conduction shell is in contact with the battery cell. The elastic piece enables the heat conduction shell to make contact with the battery cell of the battery pack assembly, after the heat conduction shell is heated, the temperature sensor can monitor the temperature of the battery cell in real time, the temperature response time is saved, the temperature error is reduced, and higher guarantee is provided for driving safety.

The present application belongs to the technical field of textile dyeing, and discloses a cloth dyeing and finishing temperature synchronous adjusting mechanical device, which comprises a dyeing pool, a dyeing groove is arranged in the middle of the dyeing pool, an air inlet pipe is fixedly connected to one side of the dyeing pool, and an air outlet pipe is fixedly connected to the other side of the dyeing pool. Through the cooperation of the heat expansion temperature sensing bag, capillary pipes, sleeves, plug rods, valve cores and sliding groove boxes, the temperature sensing liquid is driven to expand and contract with heat or cold by using the temperature change of the dyeing liquid itself, the plug rod drives the valve core to move linearly through the pressure transmission of the capillary pipes, the opening degree of the valve core is proportional to the temperature deviation, the lower the temperature is, the more the valve core rises, and the greater the flow of the heating medium is, the closer the temperature is to the set value, the smaller the opening degree of the valve core is, the proportional regulation of the heating power and the temperature error is realized, the temperature control precision is improved without the electric control system, the problem that the electronic components are prone to failure in a high temperature and high humidity environment is effectively avoided, the response lag of the electric control regulation is eliminated, and the dyeing uniformity is improved.

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 relates to a solder paste temperature adaptive fractional order PID control method for a grounding working condition, and the method comprises the steps: obtaining a real-time measurement value of a solder paste temperature in a welding process, setting a target temperature, and calculating a temperature error; a self-adaptive fractional order PID controller is constructed; inputting the temperature error into the adaptive fractional order PID controller to obtain an output signal at the current moment t; and the temperature of the soldering paste is controlled by taking the output signal at the current moment t as the adjusting quantity of the heating power. According to the method, the temperature control precision is obviously improved, the root-mean-square error and the maximum absolute error of the actual temperature and the target temperature are obviously reduced, and the engineering application value and the popularization potential of the control method in actual welding production are embodied.

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 present application relates to the field of data processing, and more particularly to a kind of injection mold temperature control method and system, method includes: same model different batches of injection mold surface is based on area uniform division region, obtain the historical temperature sequence and real-time temperature sequence of each region.Historical temperature sequence is preset sliding window, calculate temperature fluctuation degree, determine the temperature sensitivity of each region.Calculate the similarity degree of real-time temperature sequence and historical production stage temperature sequence, select the most similar degree as the most matching production stage, and calculate the comprehensive temperature error.According to temperature sensitivity and comprehensive temperature error, the temperature control signal of PID control center is corrected, and the comprehensive temperature control signal is obtained and accurate temperature control is realized.The present application realizes accurate and stable temperature control by calculating temperature sensitivity and dynamically adjusting temperature control strategy, reduces manual intervention, improves production efficiency and product quality.

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.