2965results 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 invention relates generally to devices, methods and systems for acquiring plant data. Disclosed is a field-deployable sensor attachable to plants for acquisition of plant-related data comprising: a probe including; a probe body with at least one aperture therethrough which locates the placement and spacing of one or more thermally conductive pins within the tissue of a plant; the one or more thermally conductive pins having distal and proximal ends, said distal end traversing through said aperture in the probe body and insertable into the tissue of the plant, and said proximal end located within the deployable sensor; such that when inserted into the tissue the pin approaches thermal equilibrium with the temperature of the region of the tissue in which the pin is located; and, a temperature sensor (T-sensor) enclosed within the deployable sensor located adjacent the proximal end of the pin to acquire the temperature of the proximal end of the pin; such that the T-sensor through the thermal equilibration of the pin with the plant tissue acquires plant tissue temperature data.

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 relates to a two-parameter calibration-free pulverized coal temperature measurement method based on acoustic tomography, and the method comprises the following steps: 1, arranging a plurality of loudspeaker and microphone combination modules around a measurement field domain for transmitting and receiving acoustic signals, and forming an annular acoustic sensor array; step 2, multi-frequency sound transit time and amplitude attenuation measurement; 3, constructing a tomography inversion problem model of sound velocity and sound attenuation distribution; 4, respectively realizing tomography inversion of sound velocity and sound attenuation distribution through an improved joint iterative reconstruction method SIRT, and solving pulverized coal accumulation slowness and sound attenuation coefficient distribution under each frequency; 5, calculating a corresponding multi-frequency complex wave number through the multi-frequency slowness and the sound attenuation coefficient in each grid; step 6, constructing a temperature decoupling model of a complex wave number; and 7, regarding the temperature decoupling model of the complex wave number as a nonlinear objective function optimization problem, establishing a nonlinear objective function, and performing parameter decoupling and temperature calculation.

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 discloses a temperature-sensing cable alarm test method and device based on the Internet of Things, and relates to the technical field of temperature-sensing cable monitoring. Voltage, current and frequency fluctuation models are constructed based on real-time temperature data to simulate a high-voltage impact scene, temperature over-limit and response lag conditions are effectively identified, temperature change is monitored through real-time slope, and the temperature-sensing cable alarm test method and device based on the Internet of Things are obtained. The method can respond to timely abnormal conditions, greatly improves the detection sensitivity of the cable in different environments, reduces the false alarm rate, introduces a transient power model, can accurately calculate the transient power and temperature change rate of the cable during high-voltage impact, improves the response speed under extreme conditions, and improves the reliability of the cable. And whether the cable responds within the specified time can be quickly identified, the safety in emergencies is remarkably improved, the frequency component of the temperature signal is analyzed through Fourier transform, transient high-frequency false alarm and low-frequency real fire signals are effectively distinguished, the false alarm frequency of the system is greatly reduced, and the reliability of the whole device is enhanced.

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 discloses a sensor temperature error compensation method and device based on artificial intelligence. The method comprises the following steps: collecting measurement data and temperature data of a sensor; based on the temperature data, performing temperature error compensation on the measurement data by using a neural network model based on deep learning to obtain error-compensated measurement data; wherein the neural network model is obtained based on the following training: preprocessing training data in a training data set, and calculating an error value of the neural network model based on the preprocessed training data; and network parameters of the neural network model are updated based on the error value. The technical problem that the precision of the sensor is not high due to temperature influence is solved.

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 relates to a data calibration method, device, equipment and medium for a medical-grade high-precision temperature sensor, and the method comprises the following steps: carrying out the drawing of a curve based on a preprocessing temperature data set and a second collection temperature set, and obtaining a first temperature curve and a second temperature curve; time alignment is carried out on the first temperature curve and the second temperature curve, an offset point between the first temperature curve and the second temperature curve is recognized through a preset temperature offset detection algorithm, offset point labeling is carried out on the first temperature curve, and a labeled temperature curve is obtained; and performing response analysis on the to-be-calibrated temperature sensor based on the marked temperature curve to obtain a sensor response characteristic parameter, and calibrating the to-be-calibrated temperature sensor based on the sensor response characteristic parameter, thereby solving the problems of aging and the like caused by manufacturing process difference, use environment change and long-time use, and improving the calibration accuracy of the to-be-calibrated temperature sensor. And the temperature sensor may have errors of different degrees.

The invention discloses a lightning arrester temperature compensation method based on a DSA-CTCM network. The lightning arrester temperature compensation method comprises the following steps: acquiring historical environment data of a lightning arrester; performing data preprocessing on the historical environment data of the lightning arrester; the method comprises the following steps: constructing and training to obtain a temperature compensation model through historical environment data after data preprocessing based on a dual-stage self-attention and MambaNet time sequence convolutional network; inputting real-time environment data of the lightning arrester into the temperature compensation model to obtain predicted temperature data, and calculating a temperature deviation value between the real-time temperature data and the predicted temperature data; a dynamic feedback mechanism is established, a compensation coefficient of the temperature compensation model is dynamically generated according to the temperature deviation value, the compensation coefficient is fed back to the temperature compensation model so as to adjust parameters of the temperature compensation model, and performance evaluation is conducted on the temperature compensation model; according to the lightning arrester temperature compensation method based on the construction of the DSA-CTCM network, environmental data of different time steps can be accurately identified and weighted, and the accuracy of temperature compensation is improved.

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 chip circuit compatible with platinum thermal resistance, NTC and digital semiconductor temperature measurement. According to the circuit, three temperature measurement principles are fused, a single-chip implementation scheme of temperature measurement and acquisition of PT100 / PT1000 / NTC thermistors outside a multi-channel chip and temperature measurement of PN nodes inside the chip is fused, and a time division multiplexing mode is adopted, so that the measurement matching performance among channels is improved, and the power consumption is reduced. During calibration, the internal PN node array temperature measurement channel is calibrated firstly, error correction is performed on the analog front-end circuit, and then the external temperature measurement channel is calibrated by using the precision of the PN node array, so that the calibration efficiency is improved. Reasonable reference voltage is adopted for different internal and external temperature measurement circuits, and for an external temperature measurement channel, differential voltage between two pins is selected, so that the influence caused by driving current deviation is counteracted in calculation. For an internal PN node temperature measurement channel, an internal low-temperature-drift reference voltage VREF is selected, and the influence caused by the reference voltage deviation is counteracted from calculation.

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%.

The invention discloses a temperature calibration method and system for a temperature sensor, and belongs to the technical field of temperature testing, and the method specifically comprises the steps: reading temperature data in real time through an intelligent temperature sensor, and transmitting the temperature data to a processing system; the processing system verifies and decodes the received data and then constructs a self-adaptive temperature reference model in combination with historical temperature data and current environment parameters; temperature deviation is identified, deviation reasons are analyzed through a machine learning algorithm, the temperature change trend is predicted, and correction parameters are automatically generated; the correction parameters are automatically distributed to the equipment end through the intelligent contract, so that instant adjustment and effect feedback of equipment setting are realized; the processing system collects feedback data, evaluates an adjustment effect, optimizes a self-adaptive temperature reference model and corrects a parameter generation strategy according to the adjustment effect, and forms a closed-loop optimization mechanism; according to the invention, the calibration efficiency and precision are improved, the environmental adaptability is enhanced, and the method is especially suitable for high-precision measurement requirements under extreme temperature conditions.

The invention provides a fiber grating sensor testing device and method, and the device comprises a temperature box which is configured to adjust the temperature and maintain the temperature at a preset temperature; the stretching mechanism partially stretches into the temperature box, the tested piece is located in the temperature box and installed on the stretching mechanism, the stretching mechanism is constructed to move to a preset position so as to stretch the tested piece, and the tested piece is a fiber grating sensor; the fiber bragg grating demodulation device is configured to demodulate the reflection wavelength of the measured piece to obtain wavelength data; and the acquisition and processing device is configured to acquire displacement data of the measured piece and obtain a strain sensitivity coefficient based on the wavelength data, or acquire temperature data of the measured piece and obtain a temperature sensitivity coefficient based on the wavelength data.

The invention relates to the technical field of wireless temperature measurement, and provides a wireless barbecue thermometer signal emission control method and a wireless barbecue thermometer. The signal emission control method comprises the following steps: determining whether the wireless barbecue thermometer is in a signal shielding state or not based on the change condition of the environment temperature under the condition of determining that the wireless barbecue thermometer is in a use state based on the food temperature and the environment temperature; and when the wireless barbecue thermometer is in the signal shielding state, adjusting the signal transmitting power of the power amplifier in a preset first power adjustment mode so as to increase the signal transmitting power of the wireless barbecue thermometer. By adopting the technical scheme, whether the wireless barbecue thermometer is in the signal shielding state or not can be judged according to the environment temperature change condition, and automatic adjustment of the signal transmitting power is realized in combination with the shielding state, so that the influence of signal shielding on signal transmission of the wireless barbecue thermometer can be reduced; and thus, the use experience of the user can be improved.