224 results about "Temperature correction" patented technology

The invention discloses a temperature correction method and system for a hot press, and particularly relates to the technical field of hot press temperature control, and the method comprises the steps: obtaining and preprocessing multi-dimensional operation data, including a temperature time sequence, pressure setting and material attributes; constructing a coupling model based on the multilayer neural network, and predicting temperature distribution of different process stages; performing sensor drift compensation, analyzing temperature deviation characteristics, judging whether sensor drift or material thermal diffusion abnormity exists or not, and generating a local distortion mark; determining a compensation mode according to the distortion mark, and starting a local compensation mode or a global balance control mode if the distortion is recognized as over-limit distortion; and comparing with the output of the coupling model, verifying the temperature correction effect, and if the deviation is reduced and the distortion mark is converged, outputting a stable temperature correction result. The problems of temperature distortion and sensor drift are effectively solved, and the long-term precision and stability of the hot press under complex working conditions are improved.

The invention relates to the technical field of temperature monitoring, and discloses a temperature rise monitoring method and system for high-voltage totally-closed vacuum environment-friendly GIS equipment, and the method comprises the steps: collecting temperature data through a temperature sensor, and constructing a node feature matrix and an adjacent matrix according to the spatial position relation of an SF6 gas chamber layer, a high-voltage conductor layer and a housing sealing layer; carrying out intra-layer graph convolution operation and inter-layer graph convolution operation to obtain a temperature space distribution feature vector, and carrying out time sequence fusion to obtain a temperature dynamic change time sequence feature vector; partitioning the monitoring area according to the temperature spatial distribution feature vector and the temperature dynamic change time sequence feature vector to obtain adaptive control parameters of each partition; and the adaptive control parameters are input into a multi-level compensation controller for temperature compensation coefficient calculation, and temperature correction parameters of each level are obtained, so that the integrity and accuracy of temperature field distribution feature extraction are improved, and accurate evaluation and graded early warning of temperature rise risks of different levels are realized.

The invention provides an outer wall leakage point positioning detection method and system based on infrared thermal imaging, and relates to the technical field of computer vision, and the method comprises the steps: firstly collecting a multi-period infrared thermal imaging data set of a target building outer wall, covering a surface temperature distribution matrix at different environment temperatures, and then carrying out the dynamic temperature correction processing, the method comprises the following steps of: forming a standardized temperature distribution set for eliminating the influence of environment temperature fluctuation, extracting a thermal characteristic parameter set containing the characteristics of temperature gradient distribution and the like from the standardized temperature distribution set, calling a pre-trained thermal anomaly detection model to carry out leakage risk probability mapping on the thermal characteristic parameter set, and generating a leakage point probability distribution diagram; and finally, performing region segmentation processing according to the leakage point probability distribution diagram and a preset dynamic judgment threshold value, outputting a leakage point positioning coordinate set and a corresponding leakage strength grade identifier, and realizing accurate positioning and strength grade identification of the leakage points of the outer wall.

The invention discloses a supercharged hot press temperature correction method and system, and relates to the technical field of data encryption, and the method comprises the steps: collecting temperature data and pressure data of the surface of a hot pressboard in a hot press through a high-precision sensor, carrying out the preprocessing, and carrying out the correction of the temperature of the hot pressboard based on the preprocessed temperature and pressure data; the method comprises the following steps: establishing a coupling relation model between temperature and pressure, determining an area needing to be corrected, performing local heating or local cooling adjustment on the area needing to be corrected, monitoring the influence of pressure change on temperature in real time in the area correction process, and dynamically adjusting the heating power. A complete and efficient supercharged hot press temperature correction method is formed through high-precision data acquisition, temperature-pressure coupling modeling, accurate correction area recognition and dynamic power adjustment, all the steps supplement one another, accurate control over hot press plate temperature distribution is jointly achieved, the temperature control precision, the response speed and the energy efficiency are remarkably improved, and the method is suitable for large-scale popularization and application. And a reliable technical guarantee is provided for improving the processing quality of the hot press.

The invention discloses a heat pump environment temperature self-adaptive regulation and control system oriented to peak-valley electricity price difference, and relates to the technical field of environment temperature regulation and control, and the system comprises a disturbance recognition module, a sampling scheduling module, a temperature correction module, a multi-source checking module, a regulation and control inhibition module and a self-optimization feedback module. And the change rate feature, the frequency spectrum mutation feature and the temperature measurement probe self-heating feature of the continuous external environment temperature sequence are extracted, a sampling risk index is generated, and a rapid oscillation mark is formed. Through adaptive sampling, probe self-heating compensation, multi-source consistency checking and feedback optimization mechanisms, dynamic response of the heat pump system to environment changes is achieved, data accuracy and control decision reliability are improved, and stability, energy saving performance and comfort control capacity under complex working conditions are remarkably enhanced.

The invention belongs to the technical field of refrigeration control, and discloses a refrigeration system optimization method and device based on error correction, and the method comprises the steps: obtaining a target required cooling capacity and a current environment parameter, inputting an optimization model, and obtaining an optimal control parameter and prediction power; constructing a performance curve; the performance curve comprises a temperature refrigeration curve, a temperature correction curve and a load correction curve; inputting the optimal control parameters into the performance curve to obtain actual power; subtracting the actual power from the predicted power to obtain a power error value; judging whether the absolute value of the power error value is smaller than a preset error threshold; if yes, the refrigerating system is made to operate according to the optimal control parameters; and if not, the cooling water inlet temperature in the optimal control parameters is adjusted according to the power error value. According to the method and the device, the error of the optimal control parameter output by the optimization model can be corrected, and the refrigerating system can be ensured to operate at the optimal power energy consumption while the target required cooling capacity is met.

The invention relates to the field of water resource monitoring and early warning, in particular to an intelligent water consumption monitoring and early warning method based on the Internet of Things. The method comprises the steps of obtaining water flow data and temperature data, and obtaining a water flow predicted value through a dynamic weighted sliding window prediction algorithm; calculating a water flow deviation value based on the water flow data and the water flow predicted value; calculating a temperature correction coefficient based on the temperature data, and calculating a comprehensive error value; and calculating a risk assessment value based on the comprehensive error value in combination with the temperature correction coefficient, and assessing an abnormal risk. The method solves the problems that a prediction algorithm adopted by a traditional water consumption monitoring mode is too simple, lacks dynamic adaptability to water flow fluctuation and is difficult to effectively cope with sudden water flow changes; the influence of external environment factors on the water flow is neglected, so that the prediction error is large; an adopted fixed threshold cannot adapt to different environment changes, and abnormal risks cannot be accurately detected in real time.

The invention provides a power grid load prediction improvement method and device based on an AI intelligent algorithm. The method comprises the following steps: S1, constructing an AI intelligent algorithm library for load prediction; s2, performing industry clustering on the power grid load, and dividing the power grid load into different industry classifications; s3, according to the industry classification, obtaining historical load data of each industry, selecting an algorithm of the AI intelligent algorithm library to carry out load prediction, and obtaining sub-industry load prediction data; s4, constructing a temperature correction model of each industry classification; and S5, based on the sub-industry load prediction data and the temperature correction model of each industry, correcting the sub-industry load prediction data in real time through an artificial intelligence algorithm model in combination with predicted meteorological data. The problem that the power grid load prediction precision is reduced in a large-scale new energy grid-connected scene can be solved.

The invention discloses an infrared calibration temperature measurement method based on a multi-component insulating gas multispectral imaging device, belongs to the technical field of electric power safety detection, and solves the problem of how to improve the temperature measurement precision of electric power equipment. The non-uniformity correction calibrates the response and bias of each pixel to the same numerical value, the temperature correction eliminates the influence of the lens temperature and the movement temperature on the received electric signal, the shading shutter correction ensures the accuracy and consistency of the shutter or the shading system, the radiation calibration is adopted to convert the measured blackbody voltage value into the temperature value, and the temperature value is converted into the temperature value. The real temperature of the surface of the detected electrical equipment is calculated by combining the temperature value after radiometric calibration conversion, the influence of the atmospheric environment on temperature measurement is eliminated, and the temperature measurement function of the electrical equipment based on an infrared multispectral imaging detector for insulating gas leakage in a complex environment can be realized. And a foundation is laid for further forming portable power multifunctional monitoring.

The invention discloses heat supply equipment based on computing power and a control method, and belongs to the technical field of heat supply control. The method comprises the following steps: acquiring heat supply data, and performing anomaly detection on the heat supply data; when the heat supply data is not abnormal, the distribution condition of the hot water in the heat supply pipe network is analyzed, and a flow analysis result and a pressure analysis result are obtained; optimizing the operation parameters of the heat supply network, and calculating the heat recovery efficiency of the heat supply network; constructing and training an autoregressive integral moving average model, inputting current power utilization related data and heat recovery efficiency, and outputting a thermal load demand prediction value; influence weights of the indoor temperature and the outdoor temperature on the thermal load demand are determined, a temperature difference is calculated, a temperature correction coefficient is calculated according to the temperature difference, and a thermal load demand prediction value is adjusted by using the temperature correction coefficient; setting a power corresponding relation, and adjusting the power of the electric boiler by stages; the operation time and the stop time of the electric boiler are calculated according to the operation state data of the electric boiler, and the electric boiler is set according to the operation time and the stop time obtained through calculation.

Provided is a temperature measurement device for, in a situation where the temperature of a silicon wafer which is a measurement target is indirectly measured, removing, from actually measured radiance, the effects of radiance coming from a chamber member, and calculating the amount of change in the temperature of the measurement target. The temperature measurement device comprises: a chamber for accommodating a measurement target object; a heating unit; a chamber window at a position in the chamber opposite from the measurement target object; a temperature measurement unit for measuring the temperature of the measurement target object and the chamber window; and a computation unit for calculating the temperature of the measurement target object from detected values of the temperature measurement unit. The computation unit is provided with: a conversion unit for generating, from actually measured temperatures calculated from the detected values of the temperature measurement unit, conversion data pertaining to the amount of change in the temperature of the measurement target object corresponding to the amount of change in the temperature of the chamber window; a condition acquisition unit for acquiring a condition under which the measurement target object is heated; a detected value acquisition unit for acquiring a detected value of the temperature measurement unit; and a temperature correction unit for estimating the temperature of the measurement target object by using the conversion data to correct an actually measured temperature calculated from the detected value of the temperature measurement unit.

The invention discloses an XBT-T5 observation data deviation analysis and temperature correction method, and relates to the technical field of ocean observation, and the method comprises the steps: obtaining the original temperature observation data of a target sea area based on an XBT-T5 front-end temperature sensor, calculating the depth, generating a temperature-depth profile, and constructing a temperature-depth database in combination with historical depth observation archive data; the method comprises the following steps: synchronously acquiring temperature and depth data by using a CTD temperature-salinity-depth instrument, and carrying out association pairing with a temperature-depth database to generate an XBT-T5 observation data deviation field under the same spatial-temporal scale; based on generation of an XBT-T5 observation data deviation field under the same spatial-temporal scale, designing a dual-channel adaptive encoder, and constructing a temperature-depth collaborative correction model; and according to the temperature-depth collaborative correction model, coupling the temperature-depth database and generating an XBT-T5 observation data deviation field under the same spatial-temporal scale, thereby realizing XBT-T5 observation data deviation analysis and temperature correction. The method improves the quality and application value of observation data.

The invention discloses a load prediction method based on weather forecast correction and a temperature accumulation index, and relates to the technical field of load prediction, and the method comprises the steps: S1, obtaining a first forecast total error of historical weather forecast; s2, calculating a current forecast error rate based on current weather information and the first forecast total error, and performing primary correction on weather forecast data according to the error rate; s3, calculating a temperature accumulation index according to the influence of the temperature accumulation effect on the load; s4, building a temperature correction model based on the temperature accumulation index, and carrying out the secondary correction of the meteorological prediction data; s5, constructing a BP neural network prediction model, and carrying out load prediction according to the secondarily corrected meteorological prediction data; the problem of low load prediction accuracy caused by lack of accurate prediction of future weather conditions in the prior art is solved, and the accuracy and stability of load prediction are remarkably improved.

The present invention relates to the field of water resource monitoring and early warning, and particularly to an intelligent water use monitoring and early warning method based on the Internet of Things. The content includes: obtaining water flow data and temperature data, and obtaining a water flow prediction value through a dynamic weighted sliding window prediction algorithm; calculating a water flow deviation value based on the water flow data and the water flow prediction value; calculating a temperature correction coefficient based on the temperature data, and calculating a comprehensive error value; calculating a risk assessment value based on the comprehensive error value and combining the temperature correction coefficient to evaluate the abnormal risk. It solves the problems that the prediction algorithm adopted by the traditional water use monitoring method is too simple, lacks dynamic adaptability to water flow fluctuations, and is difficult to effectively respond to sudden water flow changes; ignores the influence of external environmental factors on water flow, resulting in large prediction errors; the fixed threshold adopted cannot adapt to different environmental changes and cannot detect abnormal risks in real time and accurately.

The invention discloses an infrared temperature measurement method, a program product and equipment. The method comprises the following steps: acquiring an infrared image acquired from a monitoring scene; calculating an actual distance between a target in the infrared image and an image acquisition device, and calculating an initial temperature of the target; obtaining a temperature correction model, wherein the temperature correction model comprises a temperature compensation model and / or a target background radiation correction model; and correcting the initial temperature based on the temperature correction model and the actual distance to obtain the actual temperature of the target.

The invention discloses a low-temperature correction method for an SF6 density relay, relates to a low-temperature correction technology for a circuit breaker density relay, and aims to solve the problem of measurement misalignment caused by remarkable limitation of an existing correction method for the SF6 density relay. The method comprises the following steps: installing a density relay in a sealing test device, and filling SF6 gas to a standard pressure; placing the sealing test device in a low-temperature environment, selecting at least five temperature points, standing for 1 hour, and recording an indicating value P standard of a standard densimeter and a measured value P1 of a density relay to be corrected; calculating an error value delta P of each temperature point; performing function fitting on the error value delta P and the corresponding temperature T by adopting a quadratic polynomial function, and solving a correction error delta P1; calculating the value P correction of the corrected density relay; and low-temperature correction of the density relay is completed. The beneficial effect is that the monitoring precision in the extremely cold environment is significantly improved.

The invention discloses a multi-meteorological factor mode forecast temperature correction method based on deep learning, and relates to the technical field of meteorological data processing, and the method comprises the steps: collecting multi-meteorological factor data and observation temperature field data, and outputting a meteorological chart structure; inputting the meteorological chart structure into a graph convolutional network for deep feature extraction, and outputting a multi-meteorological factor feature tensor; performing global and local space-time characteristic analysis on the multi-meteorological-factor characteristic tensor through a dynamic gating fusion network, and outputting a fusion characteristic tensor; inputting the fusion feature tensor into a full-connection neural network for nonlinear transformation and dimension mapping to form a temperature correction model of deep learning; performing different model parameter disturbances on the temperature correction model to generate an accuracy index; inputting into a quality detection model for training, and judging the quality of each temperature correction model. According to the invention, through dual-mechanism cooperation of meteorological chart structure construction and dynamic gating fusion, deep feature extraction and adaptive weight fusion of multiple meteorological factors are realized.

The invention relates to the technical field of data processing, in particular to a cold-chain logistics whole-course tracking system and method. Obtaining a fluctuation point according to the discrete characteristic of the temperature time sequence, and obtaining a noise point according to the amplitude characteristic of the fluctuation point and the data difference characteristic of the fluctuation point and the adjacent data point; taking a vacancy moment and a moment of a noise point in the temperature time sequence as a target moment; taking the time period from the target moment to the historical nearest fluctuation point as a first time period, and taking the time period from the target moment to the future nearest fluctuation point as a second time period; when the temperature change trends of the first time period and the second time period are opposite, the correction degree is obtained according to the length features and the data difference features of the first time period and the second time period; and obtaining a correction temperature according to the data change characteristics and the correction degree of the moments before and after the target moment. A correction temperature time sequence is obtained according to all correction temperatures; monitoring is carried out according to the temperature correction time sequence, and the accuracy of temperature correction and temperature monitoring is improved.

The invention provides a power grid photovoltaic output short-term prediction method and system fused with a meteorological time sequence, and relates to the technical field of photovoltaic power, and the method comprises the steps: reading multi-source meteorological observation data of a target region; performing cloud field motion estimation, and establishing a cloud motion vector field; activating a temperature corrector, reading environment temperature and photovoltaic module temperature, constructing a temperature-module efficiency dynamic model by utilizing a temperature reading result and wind speed and wind direction data of a weather station, and establishing a power upper limit correction factor; after an illumination disturbance signal is established by using the cloud motion vector field, a short-time scale dynamic output prediction curve is generated; and performing power grid operation constraint mapping adjustment, and outputting a calibration prediction result. According to the method and the device, the technical problem of low photovoltaic output short-term prediction precision caused by instability and unpredictability due to the fact that photovoltaic power generation is easily influenced by weather changes in the prior art is solved, and the photovoltaic output prediction precision is improved and the power grid dispatching and operation are optimized by fusing the meteorological time sequence.

The invention relates to the field of household appliances, and provides an air conditioner intelligent control method and device.The method comprises the steps that based on a refrigeration mode, whether the set temperature of an air conditioner is larger than a first temperature threshold value or not, whether the humidity is larger than a first humidity threshold value or not, whether the air volume exceeds a first air volume threshold value or not and whether sunlight exceeds a first sunlight threshold value or not are judged; judging whether the sunshine corresponding time is daytime or not so as to determine a corresponding first temperature correction value; based on the heating mode, judging whether the set temperature of the air conditioner is smaller than a second temperature threshold value or not, judging whether the humidity is smaller than a second humidity threshold value or not, judging whether the sunlight exceeds a second sunlight threshold value or not and judging whether the time corresponding to the sunlight is daytime or not so as to determine a corresponding first temperature correction value; and correcting the set temperature of the air conditioner by using the first temperature correction value. The defect that the comfort is poor due to the fact that automatic control cannot adapt to different environments is overcome, the temperature of the air conditioner is automatically adjusted, and the comfort is improved.

The invention relates to the field of detection of temperature measuring devices, in particular to a temperature calibration method and system for a temperature measuring device, and the method is executed in an automatic system, and comprises the following steps: fixing a temperature measuring device to be calibrated and a reference temperature device on a heat conduction substrate in a coplanar manner; the temperature of the cavity is adjusted to a preset calibration point through a temperature control system, and heat balance dynamic judgment is executed; at least two bias currents with different amplitudes are applied to a to-be-calibrated temperature measuring device, corresponding original voltage signals are collected, a zero-power theoretical resistance value for eliminating the influence of the self-heating effect is calculated based on the original voltage signals, a corresponding reference temperature T is adopted as a data pair, parameter fitting is conducted on the resistance-temperature relation model, and the temperature measuring device is calibrated. A temperature correction calculation formula is established, a synthesis uncertainty evaluation model is established, each uncertainty source is analyzed and synthesized, and the synthesis uncertainty is calculated and output. According to the method, the risk of calibration failure caused by thermal stress or environmental interference is reduced.

The invention discloses a flexible inclinometer temperature correction method for monitoring the deflection of a concrete panel, and relates to the field of structural health monitoring, and the method comprises the following steps: S1, collecting the environmental data of the concrete panel, and constructing a structural state feature vector in combination with preset material parameters; s2, establishing a thermal drift correction model, and calculating a thermal drift response value; s3, stripping the original deflection data based on the response value to obtain a real deflection value; s4, calculating a deflection simulation value through finite element simulation, and comparing the deflection simulation value with a true value to obtain a drift prediction consistency residual error; s5, based on the spatial distance between the structural state feature vector and the historical feature vector, reconstructing a deflection correction value by adopting a semantic weighted interpolation algorithm; and S6, dynamically monitoring residual change according to the time window, and updating the thermal drift correction mode. Through multi-source sensing fusion, physical simulation feedback and tensor interpolation reconstruction, the accuracy, stability and robustness of thermal drift correction are effectively improved.

The invention relates to the technical field of security and protection management of big data, and particularly discloses an electric power engineering field security and protection management system and method based on big data. Temperature data of electric power equipment is collected in real time through an infrared thermal imaging instrument, and temperature prediction is performed by using a Gaussian process regression model in combination with environmental data; in consideration of the influence of an air attenuation coefficient on infrared thermal imaging data, the invention provides a correction method based on temperature deviation analysis, high-deviation equipment temperature data is accurately corrected by calculating the air attenuation coefficient and a temperature correction factor, and further, the temperature of the equipment is accurately corrected based on the corrected temperature data. Temperature abnormity of the equipment is identified by using a temperature fluctuation rate analysis technology, and real-time early warning and accurate positioning of equipment faults are realized.

The invention provides a heat pump device based on power consumption and a control method and linkage system thereof, and the control method comprises the steps that an indoor set temperature, a temperature correction value and a temperature upper limit value of a user temperature comfort interval are obtained, and the temperature correction value is determined by an outdoor environment reference temperature; in the space heating operation mode and under the condition that no hot water heating requirement exists, the storage electric quantity of the energy storage unit and the on-grid power supplied to the power grid by the power generation and energy storage device are obtained; and when the stored electric quantity is larger than or equal to the first preset electric quantity and the on-grid power is larger than or equal to the first preset power, the indoor set temperature is updated according to the temperature correction value and the temperature upper limit value. The invention provides a control mode in a space heating operation mode and under the condition that no hot water heating requirement exists, and the space heating operation state can be adjusted to consume electric power; the indoor set temperature can be updated based on the temperature upper limit value and the temperature correction value determined by the outdoor environment reference temperature, the flexibility is high, the power consumption is improved, and the user comfort is guaranteed.

The invention provides a precision compensation method and device for a real-time clock of an electric energy meter. The method comprises the following steps: acquiring the current environment temperature of a to-be-measured electric energy meter; when it is determined that the current environment temperature exceeds a preset normal temperature interval, on the basis of a plurality of preset temperature correction points and compensation coefficients corresponding to the preset temperature correction points, real-time clock correction is carried out on the to-be-measured electric energy meter at the preset temperature correction points in sequence according to the temperature from low to high; wherein the compensation coefficient is obtained by performing polynomial fitting on the original temperature value reading of the sensor corresponding to the preset temperature correction point and a reference temperature value. According to the invention, error transmission during precision compensation is avoided, and the real-time clock precision of the electric energy meter is improved.

The invention provides a spraying temperature control method and system, and the method comprises the steps: obtaining an inlet flue gas temperature and an outlet flue gas temperature after a temperature control instruction is received; smoothing the inlet flue gas temperature and the outlet flue gas temperature to obtain an inlet flue gas temperature correction value and an outlet flue gas temperature correction value; calculating a first deviation between the inlet flue gas temperature correction value and a set temperature, and obtaining an advance of a target water flow based on the first deviation; calculating a second deviation between the outlet flue gas temperature correction value and a set temperature, obtaining a compensation amount of a target water flow based on the second deviation, and summing the initial amount and the compensation amount to obtain the target water flow; the actual water flow of the current process section is obtained, and a first difference value between the actual water flow and the target water flow is calculated; and adjusting the opening degree of the current process section waterway valve based on the first difference value. The change of the required water flow is predicted through the change of the inlet temperature, and the corresponding response speed is increased.

The invention discloses a silicon rod surface resistance automatic detection and intelligent correction system and method. The system comprises a measurement execution module, a data processing module, a temperature correction module, an exception handling module and a result judgment module. The measurement execution module accurately positions and measures the temperature and the surface resistance of the silicon rod; the data processing module preliminarily corrects the data and identifies abnormity; the temperature correction module optimizes and corrects the measured value according to the temperature data and the influence curve; the exception handling module automatically retests the exception data; and the result judgment module gives final evaluation. The method sequentially comprises the steps of measurement preparation, data acquisition, primary processing, temperature correction, exception processing and result judgment and uploading. The problems that traditional measurement is greatly influenced by temperature, data deviation is prone to occurring and the automation degree is low are solved, the requirement of detection for the environment can be effectively lowered, energy waste is avoided, abnormal data are automatically recognized and processed, manual intervention is reduced, the detection accuracy and efficiency are improved, quality detection of the silicon rod in photovoltaic production is guaranteed, and the production efficiency is improved. And powerful technical support is provided for development of the photovoltaic industry.

The invention discloses an air conditioner heating temperature compensation method, device and equipment and a medium. The method comprises the steps that if the air conditioner enters a heating mode, the indoor environment temperature, the indoor air outlet temperature, the indoor set temperature and the current freeze-frame air sweeping position of an air deflector are obtained, and the initial heating compensation temperature is determined through a preset temperature compensation model according to the current freeze-frame air sweeping position of the air deflector, the preset temperature compensation model is constructed based on the corresponding relation between the freeze-frame air sweeping position of the air deflector and the operation angle of the air deflector; judging whether the running time of the air conditioner reaches a preset running time threshold value or not; and if yes, the initial heating compensation temperature is corrected through a preset compensation temperature correction model according to the indoor environment temperature, the indoor air outlet temperature and the indoor set temperature, and the target heating compensation temperature is determined. Through a dual temperature compensation mechanism, thermal stratification is effectively restrained, comfort is improved, and energy consumption is reduced.

The invention discloses a temperature correction method and device and a storage medium, and the method is applied to an infrared temperature measurement device, and the method comprises the steps: obtaining the temperature state data of the infrared temperature measurement device, and enabling the temperature state data to be obtained through the temperature difference values corresponding to a plurality of regional environments of the infrared temperature measurement device, the temperature difference value corresponding to the regional environment is the difference value between the real-time temperature of the regional environment and the zeroing temperature of the regional environment at the zeroing moment; based on the temperature state data and a correction reference factor, the reference temperature of the infrared temperature measurement equipment is corrected, and the correction reference factor comprises the current environment temperature sensitivity of the infrared temperature measurement equipment; the environment temperature sensitivity represents the change condition of temperature related data detected by the infrared temperature measurement equipment along with the temperature of the reference area environment of the infrared temperature measurement equipment; and calculating to obtain a temperature measurement value of the infrared temperature measurement equipment by using the corrected reference temperature. In this way, the temperature measurement precision of the equipment can be improved.

The invention relates to a gas pipeline safety protection problem, in particular to a gas pipeline leakage heat radiation prediction method based on terrain and temperature correction. The method comprises the following steps: acquiring pipeline design parameters and surrounding environment data, calculating a gas leakage flow rate Q according to the pipeline design parameters and the surrounding environment data, and calculating a heat release rate Q'according to the gas leakage flow rate Q; constructing a landform correction factor calculation model according to absorption, heat conduction and reflection characteristics of a surface material around the pipeline; importing the landform correction factor calculation model into the basic multi-point source model for iteration until convergence, and obtaining the total radiation intensity obtained by convergence; and correcting the total radiation intensity obtained by convergence based on the difference value between the actual temperature and the standard environment temperature to obtain the final total radiation intensity. The method can accurately predict the thermal radiation intensity distribution of the gas pipeline under the conditions of complex terrains and different environment temperatures, and further accurately assesses the damage range and the influence area of thermal radiation in a fire blast accident.