2056results about "Thermometer testing/calibration" patented technology

The invention relates to the technical field of semiconductors, and discloses a full-temperature-zone polynomial digital temperature compensation method and system based on an SOI chip, and the method comprises the steps: obtaining the temperature frequency data of a preset temperature zone of a target SOI chip, fitting a full-temperature-zone curve, extracting a critical point of the temperature zone, dividing a segmented compensation interval according to the critical point, and obtaining the temperature frequency data of the preset temperature zone of the target SOI chip; the method comprises the following steps: calculating frequency drift amounts under different voltages to construct a full-automatic test framework, acquiring an environment temperature parameter and an instantaneous temperature value by using the framework, analyzing a temperature compensation vector of a segmented compensation interval, further monitoring a signal frequency interval output by a chip, extracting a phase noise parameter, calculating a frequency offset error amount with a preset value, and calculating the frequency offset error amount. And analyzing an error source, optimizing a polynomial compensation order, and collecting temperature drift suppression data to generate a full temperature region compensation report. According to the invention, the performance stability of the chip in a complex environment can be improved.

The invention provides a temperature monitoring method and system for a vertical buried pipe ground source heat pump, and belongs to the technical field of temperature measuration.The method and system comprise the steps that firstly, original temperature data are collected through a distributed optical fiber sensor, a temperature fluctuation matrix is constructed, and then time domain decomposition is conducted to obtain temperature fluctuation characteristic quantity; based on this, a temperature anomaly parameter is calculated and a temperature anomaly matrix is constructed. And inputting the temperature anomaly matrix into a pre-trained temperature error prediction model to obtain an error prediction value, and generating a temperature compensation matrix according to the error prediction value. And then a three-level compensation strategy is adopted, first-level compensation, second-level compensation and final correction of the temperature data are achieved in sequence, the pre-training model constructs training data through a conditional generative adversarial network embedded into a physical equation, and the reliability of the compensation effect is ensured. The technical problem that the temperature error compensation effect is poor due to the fact that temperature field distribution around the vertical buried pipe of the ground source heat pump is difficult to accurately measure in the prior art is solved.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The invention relates to the field of temperature recorder correction, in particular to a wireless temperature recorder correction system and method, and the system comprises a calibration terminal module, a reference temperature source module, a self-adaptive model matching module and a calibration compensation module. According to the invention, the reference temperature source module provides stable reference temperature by using a PID control algorithm; the adaptive model matching module determines an optimal model type and hyper-parameters by calculating skewness, kurtosis, curvature extreme point number and residual sum of squares of error distribution in combination with a random forest classifier and a Bayesian optimization algorithm; and the calibration compensation module carries out initialization and training according to the selected model and the hyper-parameter, and outputs a compensation coefficient to calibrate the recorder. According to the method, the temperature measurement precision can be effectively improved, collaborative optimization of sensor calibration and wireless transmission parameters is realized, the equipment management and calibration efficiency is enhanced, and powerful support is provided for accurate measurement and reliable operation of the wireless temperature recorder.

The present disclosure is of an atmospheric characterization system that has a central processing board that has a first and a second communication interface. Further, the atmospheric characterization system further has a first precision temperature sensor that is communicatively coupled to the central processing board via the first communication interface and positioned a distance from a first side of the processing board, wherein the precision temperature measures a first temperature and transfers data indicative of the first temperature to the central processing board. In addition, the atmospheric characterization system has a second precision temperature sensor that is communicatively coupled to the central processing board via the second communication interface and positioned the distance from a second opposing side of the processing board such that the first precision temperature sensor and the second precision temperature sensor are equidistance from the processing board and a distance between the first precision sensor and the second precision sensor is a predetermined distance, r, and the second precision temperature sensor measures a second temperature and transfers data indicative of the second temperature to the central processing board simultaneously with the transferring of the first temperature. Additionally, the atmospheric characterization system has a processor that receives the first temperature and the second temperature and calculates a value indicative of atmospheric turbulence based upon the first temperature and the second temperature, wherein the value indicative of the atmospheric turbulence is used for designing, modifying, calibrating, or correcting an optical system.

The invention relates to the technical field of temperature control, in particular to an accurate control method and system for a rapid temperature change test box. The method comprises the following steps: acquiring an internal temperature parameter of a test box in a running state in real time based on a multi-sensor array; performing temperature error self-adaptive calibration on the internal temperature parameters of the test box, and constructing a three-dimensional temperature space distribution field; carrying out dynamic temperature transfer evolution on the three-dimensional temperature space distribution field and carrying out test box temperature change situation analysis so as to generate temperature change situation characteristics, and constructing a dynamic temperature change test box twinborn model; carrying out stage-by-stage temperature change rate calculation on a preset test box operation log so as to generate a temperature change state feature of each stage; and performing staged dynamic temperature change simulation on the dynamic temperature change test box twinborn model based on the temperature change state characteristics of each stage, thereby generating temperature change trend prediction data of each stage. According to the invention, rapid and accurate temperature change control of the test box is realized.

The invention provides a strain and temperature synchronous calibration method and device based on distributed optical fiber sensing, and relates to the technical field of optical fiber sensing calibration. Initial measurement node spacing and distribution density are obtained, reflected signals are captured according to simulated optical fiber layout, and time delay, intensity and phase change of the reflected signals are recorded; calculating a strain value and a temperature value of each measurement node, establishing a calibration model of a strain and temperature relationship, performing simulation by adopting a polynomial fitting method, obtaining and correcting real-time data, establishing a self-adaptive measurement node adjustment mechanism, and generating a calibration deviation coefficient by analyzing the deviation between the current monitoring data and a correction value. According to the invention, through the dynamic layout of the distributed optical fiber sensors and the self-adaptive measurement node adjustment mechanism, the high-precision calibration of the strain and the temperature of the key area of the structure is realized.

The invention provides a distributed optical fiber temperature detection double-end correction device and method, and belongs to the technical field of optical fiber logging, the upper end of a logging optical cable is connected with a ground reference optical fiber ring, and the lower end of the logging optical cable is connected with an optical fiber grating sensor; the electronic temperature sensor is placed in the ground reference optical fiber ring, the measurement and control module is connected with the electronic temperature sensor, and the temperature of the ground reference optical fiber ring is measured through the electronic temperature sensor; the pump light source and the DTS measurement module are connected with the COM optical splitter; the optical switch is used for switching DTS distributed optical fiber measurement and optical fiber grating sensor measurement; temperature values measured by the DTS distributed optical fiber and the optical fiber grating sensor serve as reference data to adjust measurement parameters of the DTS measurement module, and double-end correction of DTS temperature measurement data is completed. The ground reference optical fiber is combined with the electronic thermometer, and the optical fiber grating sensor is adopted underground, so that distributed optical fiber temperature measurement double-end correction is realized.

The invention provides a tunnel deformation monitoring system and method based on a distributed optical fiber sensing technology, and relates to the technical field of tunnel monitoring. A spiral winding type optical fiber is arranged in the longitudinal axis direction of the surface of a tunnel lining, a transverse optical fiber is arranged on a key section, and the data acquisition frequency is set to be 1Hz. Dividing the optical fiber into a plurality of data acquisition points at equal intervals, obtaining the real-time temperature and Brillouin frequency shift change of each point, measuring the temperature and strain sensitivity coefficient, and calculating the total strain; calculating long-term temperature strain compensation based on the long-term temperature component, generating an instantaneous temperature difference through the real-time temperature and the long-term temperature component, further calculating instantaneous temperature strain compensation, subtracting the two kinds of strain compensation from the total strain to obtain stress strain, and evaluating the deformation level of the tunnel based on the stress strain. And the accuracy of evaluation is judged through clustering analysis.

The invention provides a semiconductor chip automatic test optimization system, and belongs to the technical field of electrical variable measurement. Comprising an acquisition module used for establishing an electrical variable time sequence arranged according to a time sequence, a drift analysis module used for calculating a short-time fluctuation amplitude value, a long-term drift slope and a high-frequency noise amplitude value based on the impedance time sequence arranged according to the time sequence, and a contact judgment module. The evaluation module is used for constructing a contact impedance coefficient based on a short-time fluctuation amplitude value, a long-term drift slope and a high-frequency noise amplitude value in a jth sliding window, and evaluating and optimizing the contact impedance coefficient, and the data marking module is used for marking electrical variable measurement data corresponding to a test channel which is evaluated to be instable in contact as low confidence. According to the system, the ith test channel of the temperature sensor chip can be tested more accurately, the short-time fluctuation amplitude value, the long-term drift slope and the high-frequency noise amplitude value are calculated at the same time, multi-source data participates, and the test accuracy is improved.

The invention relates to the technical field of industrial temperature measurement, in particular to a high-temperature heating body hearth temperature distribution measurement method, which comprises the following steps of: establishing a quantitative mapping relation model between real-time input electric power and theoretical heating intensity of a heating body; a limited number of temperature sensor arrays are arranged at key positions of the internal space of the hearth; synchronously acquiring a real-time temperature measurement value of the temperature sensor array and real-time input electric power data of the heating body; calculating and generating theoretical temperature field distribution covering the three-dimensional geometric model; obtaining a corrected temperature value; calculating the temperature residual error of the corrected temperature value and the theoretical temperature field distributed at the corresponding position of the sensor; expanding the discrete temperature residual error into a full-space three-dimensional residual error distribution field; and outputting the three-dimensional real-time temperature distribution field of the hearth. Dynamic lag compensation and convective heat transfer compensation algorithms are adopted, lag and errors in measured values can be corrected in real time, and it is ensured that measured data at high temperature have high response speed and accuracy.

The invention relates to the technical field of health monitoring, and discloses an infant body temperature real-time monitoring and early warning method and system, and the method comprises the steps: collecting the body temperature of a user and the environment temperature at fixed time intervals; calculating an abnormal degree according to the user body temperature and historical user body temperatures; the abnormal degree is adjusted according to the environment temperature, and the collection interval duration is shortened according to the final abnormal degree; acquiring user body temperature fluctuation data after the acquisition interval duration is shortened in a preset duration, judging whether the user body temperature is abnormal or not again according to the user body temperature fluctuation data, calculating a body temperature difference value between a maximum value and a minimum value of the user body temperature in the preset duration, and calculating an adjacent acquired user body temperature fluctuation value; calculating a user body temperature abnormal value according to the body temperature difference value and the maximum value of the user body temperature fluctuation value; and obtaining a body temperature abnormal level according to the body temperature abnormal value of the user, and performing body temperature abnormal level early warning. According to the invention, comprehensive analysis and dynamic adjustment are realized, and the early warning accuracy of abnormal body temperature is improved.

The invention relates to the technical field of temperature control, in particular to a temperature sensor fusion compensation method and system based on Kalman filtering, and the method comprises the steps: collecting an original measurement signal, and carrying out the preprocessing; constructing a feature vector matrix and a diagonal feature value matrix of each sensor according to a preprocessing result; updating the state vector and the covariance matrix through a Kalman filtering algorithm to generate an optimal state estimation value; according to the residual distribution of each sensor and KL divergence evaluation, adjusting the weight of each sensor; and after the sensor weights of the normal sensor and the abnormal sensor are adjusted, weighted summation is carried out on the weight of each sensor and the optimal state estimation value, and a final temperature measurement value is generated. Through the Kalman filtering algorithm, the judgment of people on the influence degree of high-frequency noise and equipment errors on the sensor is improved; and the weight of each sensor is dynamically adjusted through residual calculation and KL divergence evaluation, so that the robustness and compensation precision of the system are remarkably improved.

The invention discloses an oil temperature monitoring system and method for an oil-immersed transformer, and relates to the technical power equipment state monitoring field, and the system comprises a temperature sensor module, a data acquisition module, a data processing and analysis module, an early warning module and a fault diagnosis module; the temperature sensor module comprises a plurality of temperature sensors distributed at different positions of the oil-immersed transformer and is used for acquiring oil temperature data in the transformer in real time; the data acquisition module is connected with the temperature sensor module and is used for collecting oil temperature data acquired by a temperature sensor and transmitting the data to the data processing and analyzing module; the data processing and analyzing module is used for processing and analyzing the collected oil temperature data; the early warning module is used for sending out an early warning signal when the data processing and analyzing module detects that the oil temperature is abnormal or predicts that the hot spot temperature exceeds a safety threshold value; according to the invention, the problem that the fault of the transformer cannot be accurately monitored and intelligently diagnosed is solved.

The invention relates to the technical field of temperature sensor detection, in particular to a distributed optical fiber temperature sensor detection device which comprises a shell, a detection cavity is formed in the shell, two guide openings communicated with the outside are symmetrically formed in the detection cavity, and two guide rollers are fixed to the outer wall of the shell. A temperature measuring optical fiber is inserted between the guide rollers, a heat insulation inner pipe is jointly inserted into the two guide openings, a temperature sensing contact is fixed to the inner wall of the heat insulation inner pipe, one end of the heat insulation inner pipe is fixed to the outer wall of the shell, and a heat insulation sleeve is rotationally connected to the outer wall of the heat insulation inner pipe; according to the invention, when the position of the temperature measurement optical fiber is adjusted, the temperature measurement optical fiber can be isolated, and the adverse effect of the external temperature on the internal temperature of the detection cavity is reduced.

A temperature sensing system includes a plurality of resistive segments connected in electrical series. Each resistive segment defines a material different from a material of an adjacent resistive segment, and the plurality of resistive segments are joined at sensing junctions to define a plurality of sensing junctions along a length of the resistive segments. A temperature deviation is calculated from the plurality of sensing junctions based on electric potential at each of the sensing junctions.

The invention discloses a thermal control instrument fault self-diagnosis system based on multi-source data fusion, and relates to the technical field of prediction and health management. The thermal control instrument fault self-diagnosis system based on multi-source data fusion comprises the following steps: a data collection and arrangement module used for collecting thermal control state data in real time and preprocessing the thermal control state data; the feature construction and extraction module is used for performing thermal deviation anomaly judgment on the preprocessed thermal control state data; the state intelligent evaluation module is used for performing temperature trend comparison on the thermal control state data after the thermal deviation abnormity judgment; the diagnosis linkage control module is used for fusing thermal deviation abnormity judgment and a temperature trend comparison result to execute control and participate in adjustment; and the result displaying and filing module is used for sorting and recording the measuring point diagnosis result and the processing state. The problems that false alarm is caused by wall temperature thermocouple signal drifting and abrupt change, fusion analysis of adjacent measuring points and operation states is lacked, and real overheating and instrument faults are difficult to distinguish are solved.

The invention relates to the technical field of heat pump systems, in particular to a heat pump system temperature sensor fault diagnosis and fault-tolerant control method, which comprises the following steps that: a system calculates a temperature change rate based on a current temperature average value and a temperature average value in the previous second, and performs working condition identification in combination with the running state of a compressor; generating a working condition state label according to the working condition identification result; determining a current behavior template curve based on the working condition state label and the temperature change rate, extracting a temperature sliding sequence of the sensor in a second before the current moment, and generating a comprehensive behavior score by combining the current behavior template curve, the temperature sliding sequence and a sensor behavior deviation item; combining the comprehensive behavior score, the score stability adjustment item, the trend score value and the sensor behavior deviation item to generate a health score of the sensor; and the system performs normalization processing on the health score to generate a fusion weight, and the system outputs a temperature value in combination with the fusion weight and the thermal inertia offset compensation term.

The invention relates to the technical field of thermotechnical measurement and signal processing, in particular to a multi-sensor linkage heat flux density-temperature real-time acquisition and error compensation method, which comprises the following steps: S1, constructing an embedded sensing array on a surface to be measured; s2, synchronously acquiring original measurement values of the sensors by taking 10ms as a period, and generating an original data matrix with a timestamp identifier; s3, extracting a three-dimensional temperature gradient field, and calculating to obtain a convective disturbance intensity coefficient of each measurement point; s4, establishing a dynamic error compensation model, and performing point-by-point error correction on the original data matrix; s5, cross validation is carried out, and credibility evaluation parameters are generated; and S6, carrying out weighted fusion, and outputting a final heat flux density-temperature coupling measurement value. According to the invention, through multi-sensor array cooperative acquisition, dynamic error compensation and credibility weighted fusion, high-precision, strong-anti-interference and high-credibility output of heat flux density and temperature measurement is realized.

The invention discloses a temperature measurement sensor data processing method and system in a chemical synthesis environment. The method comprises the steps of original data acquisition and preprocessing, sensor drift compensation, dynamic response optimization and anomaly detection and adaptive calibration. The system comprises an original data acquisition and preprocessing module, a sensor drift compensation module, a dynamic response optimization module and an anomaly detection and adaptive calibration module. Through multi-module deep fusion of LSTM drift compensation and adaptive Kalman filtering, + / -0.5 DEG C measurement precision is realized in a range of 80-300 DEG C; the MPC predictive control compresses the thermal inertia lag of the sensor from 500ms to less than or equal to 80ms, so that the sudden rising / dropping temperature in the synthesis reaction can be effectively captured, and the product decomposition caused by local overheating is avoided; isolated forest anomaly detection and least square calibration are combined, so that the maintenance period of the sensor in a strong corrosion environment is prolonged from 7 days to 90 days, and the annual maintenance cost is reduced by 65%.

Novel tools and techniques are provided for implementing an encoder capable of performing a self-calibration or self-correction process, and more particularly methods, systems, and apparatuses are provided for implementing an encoder capable of performing a process to calibrate itself or correct a signal of a sensor at different detected temperatures of an environment. In various embodiments, the encoder includes an exciter and a sensor capable of detecting a position of the exciter and generating a signal based on the position of the exciter. The encoder can then perform one or more steps to calibrate itself or self-correct a signal at different temperatures and calculate one or more values to correct a signal generated by the sensor.

The invention discloses a power equipment temperature monitoring and early warning system and method based on wireless communication, and relates to the technical field of temperature monitoring, the system comprises a wireless temperature measurement terminal box and a mobile terminal APP, the wireless temperature measurement terminal box and the mobile terminal APP establish communication connection based on a wireless network, and the wireless temperature measurement terminal box is fixedly installed on power equipment; the wireless temperature measurement terminal box comprises an electromagnetic environment judgment module which monitors and judges whether interference exists in the environment where power equipment is located in real time based on an electromagnetic sensor and synchronizes a result into a temperature drift compensation analysis module; and the temperature monitoring module monitors temperature data in the power equipment in real time based on a temperature sensor. Through electromagnetic environment judgment and temperature drift compensation, historical data and a model are combined to dynamically correct interfered temperature data, the influence of electromagnetic interference is eliminated, real-time monitoring is matched with graded alarm, hidden dangers can be found in time, response can be made according to risk grades, accidents are avoided, and wireless connection adapts to complex scenes.

The invention discloses an industrial Internet of Things intelligent equipment control method. The method comprises the following steps: S1, data recording: a monitoring mechanism monitors temperature values of different time points in a closed shell in an operation process of intelligent equipment; s2, drift calibration: the driving mechanism controls the calibration mechanism to perform drift calibration on the corresponding abnormal temperature sensor; s3, data analysis: predicting the operating temperature of the equipment by the time sequence model, dynamically adjusting an alarm threshold according to historical data, and judging whether the monitoring temperature of the equipment exceeds the threshold or not; and S4, equipment starting and stopping: the driving mechanism controls the starting and stopping mechanism to perform power-off processing on the intelligent equipment. The control module and the monitoring mechanism are arranged, and the type of a data exception source is judged while the running state of the equipment is monitored through temperature; by arranging the driving mechanism and the start-stop mechanism, the intelligent equipment stops running; the calibration mechanism is arranged to carry out drift calibration on the sensor of the detection mechanism.

The invention relates to the technical field of fault diagnosis, and discloses a temperature sensor fault diagnosis method and system, and the method comprises the following steps: processing industrial furnace multi-source sensing data, and obtaining a standardized multi-physical field feature data set; processing the standardized multi-physics field feature data set to obtain a multi-physics field coupling feature vector; processing the multi-physical field coupling feature vector and the network topology structure of the temperature sensor to obtain a health state evaluation result of the temperature sensor; processing the health state evaluation result of the temperature sensor and historical fault data to obtain a sensor fault prediction report; and processing the fault sensor data and the surrounding health sensor data to obtain a data compensation result of the fault sensor. Under the monitoring of a temperature sensor network in a complex industrial environment, the reliability and the safety of the system can be remarkably improved, and the shutdown loss and the safety risk caused by sensor faults are reduced.

The invention provides a cabinet three-dimensional temperature field monitoring method and device, and the method comprises the steps: arranging four temperature sensors at the positions of left and right columns at the rear part of a cabinet and the left and right middle positions of the rear side of the top of the cabinet respectively, and forming vertical and horizontal coordinate distribution points covering a key heat distribution region of the cabinet; collecting temperature data of the four temperature sensors at preset coordinate positions, and inputting the temperature data into a three-dimensional temperature field reconstruction algorithm model; processing the temperature data by adopting a bilinear interpolation method, and calculating the temperature value of any position in the cabinet; and according to a hot air convection rule, introducing height direction temperature gradient correction into the three-dimensional temperature field reconstruction algorithm model so as to eliminate the influence of heat convection on a temperature monitoring result. The three-dimensional temperature distribution in the cabinet can be accurately reflected, the temperature monitoring precision and real-time performance are improved, and the installation and maintenance cost is reduced.

The invention provides a surface thermometer calibration system. The surface thermometer calibration system comprises a surface heat source device, a control host, a temperature control thermometer, a reference surface thermometer and a standard thermometer, the surface heat source device comprises a glass cover, a constant-temperature disc heat source, an upper protection structure, an adjustable support and a cooling fan. The control host comprises a dual-channel high-precision thermodetector, a dual-channel program-controlled output voltage-stabilized power supply and a control module, and the control module is used for obtaining measurement results of the temperature control thermometer, the reference surface thermometer and the standard thermometer and dynamically adjusting the output voltage of the dual-channel program-controlled output voltage-stabilized power supply according to the measurement results. Temperature control of the constant-temperature disc heat source is achieved. According to the surface thermometer calibration system designed and developed by the invention, the reliability and the calibration efficiency of surface thermometer calibration can be remarkably improved, and the reliability of surface temperature value traceability is ensured.

The invention provides a thermocouple temperature measurement adaptive anti-interference method and system applied to an instrument, and relates to the technical field of temperature measurement and control, and the method comprises the steps: obtaining an original thermocouple temperature measurement signal generated by a thermocouple body, carrying out the cold end compensation of the original thermocouple temperature measurement signal, and obtaining a standard thermocouple temperature measurement signal; respectively processing the standard thermocouple temperature measurement signals to obtain corrected thermocouple temperature measurement signals; the corrected thermocouple temperature measurement signal and the closed-loop manipulated variable are used as observed quantities to be input into the extended state disturbance model, an unknown equivalent disturbance quantity corresponding to the corrected thermocouple temperature measurement signal is obtained, and a predicted temperature deviation value and a predicted equivalent disturbance quantity are obtained through an extended state observer; and dynamically adjusting the gain of the PID controller by using a fuzzy self-tuning algorithm, carrying out superposition processing on the PID control quantity and the compensation quantity corresponding to the predicted equivalent disturbance quantity, and compensating the temperature controller by using a temperature regulation and control instruction. According to the invention, the steady-state disturbance suppression capability and the response speed can be improved.

The invention relates to the technical field of power supply thermal management control, and discloses a high-voltage variable-frequency power supply thermal management control method for improving energy efficiency, and the method comprises the following steps: carrying out the order reduction processing in combination with a solar high-temperature thermal power generation system, and obtaining a low-dimensional model; carrying out data fusion by using Gaussian process regression and a Kalman filtering algorithm, and reconstructing temperature field information of the system; establishing a multi-objective optimization function, and dynamically adjusting a weight optimization objective; generating a control parameter sequence by using an improved particle swarm optimization algorithm, and adjusting a control decision in real time through iterative optimization; the optimized control parameters are input into a multi-rate hierarchical control system for division execution; and detecting a fault type and switching to a corresponding fault-tolerant control mode. According to the method, a multi-physical field coupling model and an intrinsic orthogonal decomposition technology are combined, an accurate coupling model of an electromagnetic field, a temperature field and a flow field in the high-voltage variable-frequency power generation system is established, through order reduction processing, the dimension of the model is reduced, the calculation complexity is remarkably reduced, and the calculation efficiency is improved.