127 results about "Temperature correction" patented technology

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 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 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 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 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 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 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 present application relates to the technical field of heat supply balance management, in particular to a heat supply balance management method and system for end user heat supply. The method comprises the following steps: S1, a heat supply global data acquisition model is built, heat supply pipeline data is collected, and an end user list is obtained according to the heat supply pipeline data; outdoor temperature and historical heat supply temperature of each end user are synchronously obtained; independent temperature periods are divided according to the outdoor temperature value; the same heat supply scheme is adopted for classification and elimination of regulation and control interference; temperature differences of different users are compared under the same heat supply condition; exclusive heat loss coefficients of each household are quantitatively generated; heat loss differences caused by floors, orientations and wall heat preservation can be accurately distinguished; user target heat supply temperature is dynamically corrected according to the heat loss coefficient; the temperature correction range of users with large heat loss is increased, and the correction range of users with excellent heat preservation performance is reduced; the uneven heating and cooling problem caused by inconsistent heat dissipation of different houses is solved from the heat loss level of the user itself.

The application provides a temperature control method, device, storage medium and equipment. In the method, a single in-vehicle temperature sensor arranged at a central position in a vehicle obtains an in-vehicle temperature sampling value. According to a current vehicle speed, an outside temperature and an air conditioner cycle state, an air outlet temperature and an illumination intensity of a target temperature zone, a temperature correction value corresponding to the target temperature zone is determined. Then, the in-vehicle temperature sampling value is corrected based on the temperature correction value to obtain a head temperature of the target temperature zone, and the target temperature zone is controlled in temperature based on the head temperature. In this way, the cost of the in-vehicle temperature sensor is reduced, and the accuracy of temperature control of each temperature zone is improved.

The application relates to the correction technical field of a temperature sensor, and discloses a temperature sensor correction method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: obtaining temperature difference values of different preset temperature ranges through a plurality of preset time periods, a comprehensive temperature response model is constructed, a nonlinear characteristic is extracted by using a change value of adjacent temperature difference values, a relational function is fitted, a target temperature difference value of a current time point is dynamically obtained, and the intelligentization and real-time of temperature correction are realized.The application has the beneficial technical effects that the inconvenience of a traditional temperature sensor depending on factory correction is avoided, errors caused by temperature floating in actual application are reduced, and calibration time and cost are reduced.

The application discloses a pipeline temperature measurement temperature correction method, comprising the following steps: performing calibration experiments, obtaining first temperature measurement array data and second temperature measurement array data on the outer and inner surfaces of the pipeline respectively; constructing a thermal physical model of the pipeline to be measured, calculating a first temperature derivative, and obtaining an energy balance equation of the relationship between the inner and outer surfaces of the pipeline; substituting the first temperature measurement array data and the second temperature measurement array data into the energy balance equation to obtain a complete energy balance equation; performing verification experiments, obtaining third temperature measurement array data and fourth temperature array data on the outer and inner surfaces of the pipeline respectively; substituting the third temperature measurement array data into the complete energy balance equation, reconstructing the pipeline inner surface temperature array data and calculating a second temperature derivative; and comparing the reconstructed temperature array data with the fourth temperature array data to calculate errors. The application adopts a reverse heat conduction temperature correction method to correct the pipeline temperature measurement, so that the accuracy and stability of the measurement results are improved.

The invention discloses an air conditioner control method and device, an air conditioner and a storage medium, and relates to the technical field of air conditioners. The air conditioner control method comprises the steps that position information of the space where the air conditioner is located is obtained; when the position information of the space where the air conditioner is located meets the temperature correction condition, the temperature correction value of the air conditioner is determined; the target temperature is corrected according to the temperature correction value, and the corrected target temperature is obtained; and performing temperature control on the air conditioner according to the corrected target temperature. By means of the mode, when the position information of the space where the air conditioner is located meets the temperature correction condition, the temperature correction process is started based on the temperature correction value, the temperature of the air conditioner is controlled, and the problem that due to the fact that the air conditioner cannot know the layout of the space where the air conditioner is located, air conditioner control fails when the air conditioner mistakenly senses the high environment temperature is solved; accurate control over the air conditioner is guaranteed, the situation of large cooling capacity output is avoided, and the user experience is improved.

A temperature control device controls power supplied to a heater based on a temperature estimate value estimated over time so that a temperature control target to which heat propagates from the heater of the fixing unit reaches a preset target temperature. The temperature control device includes a temperature sensor, first and second storage circuits, a temperature difference detection circuit, and a target temperature correction circuit. The temperature sensor detects a temperature of the heater. The first storage circuit stores the temperature estimate value. The second storage circuit stores a sensor temperature. The temperature difference detection circuit calculates an actual temperature rise amount from a temperature difference between the temperature estimate value and the temperature of the heater from the respective storage circuits. The temperature correction circuit performs control such that a target temperature is lowered in accordance with the actual temperature rise amount.

A fast-response temperature and humidity sensor includes a humidity-sensitive material, a cylindrical frame disk, a temperature sensor, and an MCU with on-chip ROM. The frame disk has multiple deep-groove air channels evenly distributed around its perimeter. The frame disk has a socket for fixing the temperature sensor, which is electrically connected to the microcontroller. The temperature sensor measures the ambient temperature around the temperature and humidity sensor, and the MCU performs temperature correction on the humidity measurement value. The MCU's on-chip ROM stores a standard database containing multiple humidity-sensitive resistance (R)-humidity (H) curves of the fast-response temperature and humidity sensor at different temperatures (T). Based on the measured temperature value (T) and resistance value (R), the MCU looks up the corresponding humidity value (H) in the standard database.

This invention provides a method, apparatus, and system for multi-point temperature correction of an array induction logging tool. The method includes: acquiring measurement signals from the array induction logging tool during temperature changes, the measurement signals being detected by a preset number of temperature sensors; constructing a temperature coefficient matrix for each temperature sensor based on the measurement signal, resulting in a preset number of temperature coefficient matrices; calculating a temperature correction coefficient matrix based on each temperature coefficient matrix; acquiring actual measurement signals from the array induction logging tool downhole, and performing temperature correction on the measured signals based on the temperature correction coefficient matrix. The multi-point temperature correction method for an array induction logging tool provided by this invention can calculate the temperature correction coefficient matrix based on the actual measurement signals and correct the measured signals based on the temperature correction coefficient matrix, thus avoiding errors caused by formation temperature changes and improving the accuracy and reliability of the array induction logging tool.

The invention relates to a temperature correction method based on a full-connection neural network. The method comprises the following steps: constructing an EMFCNN temperature model based on the full-connection neural network; the EMFCNN temperature model is trained, and after training is completed, an EMFCNN 24h highest temperature model, an EMFCNN 24h lowest temperature model and an EMFCNN hourly temperature model are obtained; performing temperature correction based on the EMFCNN 24h highest temperature model, the EMFCNN 24h lowest temperature model and the EMFCNN hourly temperature model; according to the method, deep fusion of spatial features and meteorological elements is realized through station number Embedding coding and mode forecasting element splicing operation, the limitation of a single data source of a traditional numerical mode is broken through, and joint modeling of gridding station features and numerical forecasting data is realized. According to the forecasting element screening strategy based on the temperature local change equation, forecasting day key meteorological element combinations are selected through physical equation constraints, the scientificity of feature selection is improved, and blindness of a traditional machine learning method is avoided.

This application relates to a control method, apparatus, control device, equipment, computer-readable storage medium, and computer program product for a water heater. The method includes: acquiring the outlet temperature of hot water in the heating pipes of the water heater; calibrating the outlet temperature based on outlet temperature correction parameters to obtain a calibrated corrected outlet temperature; the outlet temperature correction parameters are obtained based on the outlet temperature obtained by the hot water flowing through the heating pipes and a reference temperature of the hot water; controlling the operating power of the water heater's heating system according to the target temperature and the corrected outlet temperature, so that the heated corrected outlet temperature reaches the target temperature, wherein the heating system is used to heat the water in the heating pipes. This method enables more precise control of the heating power of the heating system, resulting in a higher consistency between the actual temperature of the hot water to be discharged and the user-set target temperature, thereby improving the user's water comfort.

The invention provides a servo motor temperature correction coefficient optimization and multistage early warning system and method. Comprising a data acquisition module used for acquiring a first temperature value and a second temperature value; the temperature correction module is used for calculating a temperature difference value according to the third temperature value and the second temperature value; the correction coefficient optimization module is used for carrying out online optimization on the temperature correction coefficient in the temperature correction model and carrying out iterative updating to obtain a target temperature correction coefficient; the early warning judgment module is used for dividing the current working state of the servo motor into one of a normal state and at least three levels of early warning states, and generating early warning level information corresponding to the early warning state; and the early warning output module is used for outputting a corresponding early warning signal and a control instruction to an upper control device and / or a human-computer interface according to the early warning grade information so as to implement graded early warning control on the operation of the servo motor. The method can improve the temperature correction precision, achieves the dynamic optimization of the correction coefficient, and improves the temperature early warning precision of the servo motor.

The invention provides an active air supply type transformer substation main transformer chamber cooling method and system, and the method comprises the steps: obtaining an oil temperature set value Ts, a top oil temperature measurement value Tc, and a radiation temperature Td, calculating a temperature difference value delta T according to Ts and Tc, calculating a correction value delta T according to Td through a proportional function Fw, and inputting the difference value between the temperature difference value delta T and the temperature correction value delta T into a PID algorithm, temperature control feedback used for adjusting the air supply amount is output; the PID algorithm comprises a proportionality coefficient Kp, a differential coefficient Kd and an integral coefficient Ki, and the integral coefficient Ki is equal to 0. According to the method, the integral part in the PID algorithm is deleted, and the correction value delta T is introduced, so that the corrected temperature difference value delta T is directly associated with the top oil temperature measurement value Tc, and frequent start and stop of the fan are avoided while the response speed of the fan for cooling is increased.

The power distribution network operation risk assessment method based on the traffic flow propagation theory comprises the following steps: constructing a weather state transition model, and obtaining probability distribution under different meteorological conditions; establishing a photovoltaic output probability density function based on Beta distribution, and generating a photovoltaic output scene; establishing a space-time propagation model of photovoltaic disturbance in the power distribution network; introducing the dynamic influence of the line current on the temperature, and establishing a line resistance temperature correction model; on the basis of a load flow calculation result, establishing a load flow correction model based on LWR model output disturbance density; constructing a comprehensive risk assessment index system including dimensions of voltage out-of-limit, line overload, system loss and the like; and the established comprehensive risk assessment index system is applied to an IEEE 33 node system, simulation verification is carried out based on an MATPOWER software package in an MATLAB environment, and dynamic evolution characteristics of the operation risk of the power distribution network under a traffic flow propagation theory are analyzed. According to the method, through multi-dimensional modeling and a dynamic coupling mechanism, fine evaluation of the whole process from disturbance generation to propagation diffusion is realized.

The application discloses a mechanism-driven fixed-pollution-source flue gas flow velocity acoustic wave monitoring method, aiming at the problems of low two-dimensional flow velocity field resolution, lack of measured data and temperature affecting acoustic velocity to cause errors in the prior art, and the method is characterized in that: firstly, a mechanism-driven simulation model is constructed based on thermal flow physical characteristics, and a multi-working-condition temperature field and a flow velocity field simulation data set are generated; secondly, a flow velocity reconstruction network fusing space-TOF features is constructed and trained; finally, acoustic time-of-flight (TOF) data are collected in real time, the acoustic velocity and the TOF data are corrected in combination with the measured temperature of a thermocouple, and the two-dimensional flow velocity field is output by inputting the corrected data into the trained network. The application solves the data bottleneck through the mechanism-driven model, improves the space-time resolution by using the network, eliminates the acoustic velocity error by combining the temperature correction, and realizes high-precision real-time monitoring of the fixed-pollution-source flue gas flow velocity, thereby providing technical support for fine supervision of industrial flue gas flow fields.

The invention provides a method for calculating segmented day-age and all-day-age power of piglet heating equipment, and relates to the technical field of temperature control, and the method specifically comprises the following steps: building a linear fitting model in two stages according to the cooling law that piglets at the age of 1-20 days are fast in the front and slow in the rear, and calculating the basic power. And when the deviation between the actual temperature and the standard temperature of the corresponding section is greater than the temperature deviation threshold, introducing a temperature correction term. When the weak baby proportion is larger than a weak baby threshold value, a weak baby correction term is introduced, and the power is increased to meet the weak baby heat preservation requirement. And calculating the final power after temperature correction and weak gain correction. According to the technical scheme, the problem that in the prior art, the staged precise temperature control requirement of the piglets at the age of 1-20 days cannot be met is solved.

The present invention discloses a method for correcting and maintaining the temperature of a discharge lamp, belonging to the technical field of discharge lamp temperature correction, and comprising the following steps: measuring multiple sets of vertically measured temperature values ​​and tilted measured temperature values ​​of the discharge lamp under a tilt angle of ; fitting the multiple sets of measured vertically measured temperature values ​​and tilted measured temperature values ​​to obtain a relationship; measuring the actual tilted measured temperature and calculating the actual temperature value through the relationship; and adjusting a cooling component based on the difference between the actual temperature value and the target temperature value so that the temperature of the discharge lamp is maintained at the target temperature value. The method for correcting and maintaining the temperature of a discharge lamp proposed by the present invention can effectively monitor and correct the temperature of the discharge lamp in real time, and dynamically adjust the cooling intensity of the cooling component through an adjustment component based on the difference between the actual temperature value and the target temperature value. The method is convenient and easy to implement.

An apparatus for correcting a temperature of an object using a shutter may comprise a temperature measurement module for measuring the temperature of the object and a temperature of the shutter, a noise temperature calculation module for calculating the temperature due to noise using the measured temperature of the shutter, and a temperature correction module for correcting the temperature of the object by subtracting the calculated temperature due to noise from the measured temperature of the object.

The invention discloses a sow oestrus detection method and device based on thermal imaging and deep learning, and the method comprises the steps: S1, collecting the infrared thermogram sequences of an ear root region and a vulva region of a target sow, and generating dual-region time sequence thermal imaging data; s2, performing temperature correction and key point positioning on the double-region time sequence thermal imaging data, and generating a region temperature characteristic spectrum through improved YOLOv8n model processing; and S3, inputting the regional temperature characteristic spectrum into a bidirectional long short-term memory network, extracting a temperature change trend, generating an estrus characteristic vector, and determining the estrus state and stage of the sow. The method can accurately and efficiently detect the oestrus state of the sow, and provides a scientific basis for agricultural production.

A measurement device (1) comprises: a detector (10) that measures an object to be measured; a temperature sensor (80) that measures the temperature of the object to be measured at the time of measurement; and a control unit (102) that is capable of switching a temperature input mode between an automatic input mode for automatically acquiring the temperature detected by the temperature sensor and a manual input mode for receiving a manual input of the temperature of the object to be measured at the time of measurement, and that corrects the measured temperature of the object to be measured on the basis of the temperature acquired by the automatic input mode or the manual input mode.

This invention relates to the field of energy engineering technology, specifically disclosing a method and system for predicting the power consumption of a gas turbine unit. The method includes: identifying a window of extremely slowly varying operating conditions through a monitoring system, constructing a scatter plot, identifying closed narrow hysteresis loops to determine nonlinear hysteresis effects, completing wall thermal inertia analysis and quantifying the total wall heat flow rate; correcting combustion temperature drift based on the total wall heat flow rate to obtain the true combustion temperature; constructing an air-fuel ratio correction model in the sensitive range of the slightly open gas regulating valve to achieve dynamic matching of gas flow; eliminating gas consumption distortion components to obtain hysteresis-free true gas consumption values, and finally obtaining hourly and daily gas consumption prediction ranges without dynamic interference through cumulative calculation and system deviation calibration. The system includes: a hysteresis identification module, a temperature correction module, an opening degree adjustment module, a gas consumption analysis module, and a prediction output module. The solution effectively improves the accuracy of gas consumption prediction under extremely slowly varying peak-shaving conditions.

A segmented inflation control method, device, equipment and computer readable storage medium, comprising: calculating the inflation flow of the object to be tested according to the volume, pre-inflation pressure, inflation duration, pre-set ambient atmospheric pressure, pre-set efficiency coefficient and temperature correction coefficient of the object to be tested; starting the PWM control valve to inflate the object to be tested according to the inflation flow of the object to be tested to determine whether the current inflation pressure of the object to be tested is within the target pressure range; if it is determined that the inflation pressure of the object to be tested is within the target pressure range, switching to the PID controller to continue inflating the current object to be tested to the pre-inflation pressure, solving the technical problems of long inflation duration and low inflation accuracy in related art, achieving fast rough inflation first and accurate fine inflation later, and improving inflation efficiency and pressure control accuracy.