1570results 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 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 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 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 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 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%.

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 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 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.

The invention relates to the field of optical fiber optics, in particular to a distributed optical fiber temperature measurement system based on Raman scattering, which comprises an optical signal excitation and separation module, a signal acquisition and preprocessing module, a temperature resolving module, a calibration and correction module, a real-time monitoring and early warning module and a management database, the system performs digital accumulation noise reduction on scattering signals through separation of Stokes light and anti-Stokes light, real-time monitoring of optical power and division of spatial positions, generates a temperature distribution curve through temperature calculation and determination of the spatial positions corresponding to the temperatures, generates calibration coefficients through selection of constant-temperature reference points and fitting of a temperature deviation curve, and performs calibration on the scattering signals. The temperature is corrected, a calibration curve is calibrated, meanwhile, light intensity attenuation is compensated, and the light temperature can be accurately measured and early warning can be carried out in time by setting multi-stage temperature early warning threshold values and monitoring temperature abnormal points.

The invention discloses an in-situ automatic calibration system and method for a multi-channel temperature acquisition instrument. The system comprises a metering port, a change-over switch, an upper computer, a multi-channel change-over switch and a standard signal source. The metering port is connected with the multi-channel change-over switch and is used for calibrating the temperature acquisition instrument; the change-over switch is connected with the acquisition circuit board and is used for switching a measurement mode and a calibration mode, in the measurement mode, the acquisition circuit board is connected with the measurement port, and in the calibration mode, the acquisition circuit board is connected with the metering port; the multi-channel change-over switch performs channel switching under the control of the upper computer, the standard signal source is connected with the multi-channel change-over switch and is used for outputting a preset standard electric signal to the metering port, the acquisition circuit board acquires the electric signal and converts the electric signal into a digital signal, and the master control digital board processes the digital signal and transmits the digital signal to the upper computer. According to the invention, a metering calibration function is added on an original temperature acquisition instrument, so that on-site rapid calibration of the multi-channel temperature acquisition instrument can be realized.

The invention provides a temperature sensor data calibration method and system, and relates to the technical field of sensor calibration, and the method comprises the steps: collecting a time sequence voltage sequence of a to-be-calibrated temperature sensor under the excitation of a temperature step; calculating a gradient change rate of the time sequence voltage sequence to obtain a dynamic response characteristic of the to-be-calibrated temperature sensor; based on the gradient change rate, the dynamic response asymmetry degree of the temperature sensor to be calibrated under temperature step excitation is calculated; establishing a thermal inertia evolution equation of the temperature sensor to be calibrated according to the dynamic response asymmetry degree; the theoretical lag amplitude of the temperature sensor to be calibrated is corrected with the trend of the thermal inertia evolution equation to be stable as the target, and the actual lag amplitude is obtained; obtaining the original measurement temperature of the target temperature by the temperature sensor to be calibrated; and correcting the original measurement temperature in combination with the actual lag amplitude and the dynamic response asymmetry degree to complete data calibration of the temperature sensor to be calibrated. And the measurement precision of the temperature sensor in a complex temperature change scene is improved.

The invention relates to the technical field of film temperature sensors, in particular to a film preparation method based on the sputtering technology, a temperature-sensitive film and a temperature sensor.The temperature sensor comprises an adhesion layer, an insulation layer is arranged on the adhesion layer, a temperature-sensitive layer is arranged on the insulation layer, the adhesion layer is made of NiCrAlY materials, the insulation layer is made of high-melting-point metal oxide materials, and the temperature-sensitive layer is made of high-melting-point metal oxide materials. The temperature-sensitive layer is an ITO-Al2O3 composite film with the mass ratio of Al to In being 1-10 wt%, the adhesion layer of the temperature-sensitive film is used for being adhered to a measured component, and a platinum wire is led out of the temperature-sensitive layer of the temperature-sensitive film to transmit electric signals. Compared with a pure ITO thin film temperature sensor not doped with Al2O3, the thin film temperature sensor based on the temperature-sensitive thin film has the advantages that a repeatability error order of magnitude is remarkably reduced, and the measurement reliability of the thin film temperature sensor based on the temperature-sensitive thin film under an extreme working condition is effectively guaranteed.

An ultra-thin film wireless label can include a temperature sensor. The wireless label can be attached to an object, and the wireless label can be used as a temperature monitoring device. The wireless label can have a stacked structure laying the temperature sensor to have efficient thermal contact with the object, while being relatively insulated from the environment via an insulating layer. The temperature sensor can be calibrated, and the calibration parameters can be stored and later used to generate accurate temperature readings.

The invention discloses a high-precision temperature measuring equipment correction system, and relates to the technical field of temperature measuring equipment correction, and the high-precision temperature measuring equipment correction system mainly comprises a hardware layer, an algorithm layer and an embedded layer which are electrically connected with one another. The hardware layer is used for acquiring temperature data, humidity data and pressure data; the hardware layer comprises a temperature sensor array, a humidity sensor, a pressure sensor and an analog-to-digital converter; the algorithm layer is used for correcting the temperature data according to the temperature data, the humidity data and the pressure data, and the algorithm layer comprises a data preprocessing module, a hybrid correction module and a dynamic compensation module; and the embedded layer is used for task scheduling and temperature data output. By implementing the high-precision temperature measurement equipment correction system provided by the invention, the correction precision, efficiency and reliability of the temperature measurement equipment can be improved.

The invention discloses a real-time adaptive temperature monitoring intelligent sensor based on a deep learning algorithm, and belongs to the technical field of environmental parameter measurement and artificial intelligence. The sensor is composed of a main temperature measuring unit, an auxiliary environment sensing unit, a data acquisition circuit, a microcontroller, a deep learning processing module, a memory, a communication module and a power supply module. Multi-modal data are obtained through the auxiliary environment sensing unit, and the multi-modal data are preprocessed and then input into the self-adaptive temperature sensing network. In the adaptive temperature sensing network, a multi-mode encoder extracts time sequence characteristics of each channel, a convolution auto-encoder reconstructs a normal temperature measurement mode and performs anomaly detection, and a fusion decoder fuses output of each sensor into a corrected temperature value based on a dynamic weight formula. The method has the advantages of high real-time performance, high measurement precision, timely anomaly detection, high self-learning capability, low power consumption and the like.

The invention relates to the technical field of cable monitoring, and discloses a cable joint temperature monitoring method and a cable joint, and the method comprises the steps: obtaining the real-time insulating layer temperature data of the cable joint based on a miniature temperature sensor, and obtaining the real-time environment data of the cable joint based on an auxiliary sensor; comparing the real-time insulating layer temperature data with a real-time environment temperature value, and determining the thermal radiation direction of the cable joint; determining a temperature difference value between the real-time insulating layer temperature data and the real-time environment temperature value, and determining a predicted temperature value of the conductor crimping layer according to the temperature difference value based on the heat radiation direction; determining a predicted temperature change rate of the conductor crimping layer according to the predicted temperature value; the real-time load current of the cable connector is obtained, and the real-time temperature change rate is determined; and determining a difference ratio between the predicted temperature change rate and the real-time temperature change rate, and judging whether the temperature monitoring of the cable joint is abnormal or not. According to the invention, accurate temperature prediction and reliable abnormity judgment of the cable joint are realized.

The invention provides a battery temperature monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of temperature monitoring, and the method comprises the steps: obtaining a temperature prediction curve through a battery temperature prediction model; collecting a first temperature measured value through a target temperature sensor, and calculating a temperature difference value between the first temperature measured value and the temperature predicted value; setting a target temperature sensor to be in a standard sampling period mode or a variable sampling period mode according to a preset condition, and when the target temperature sensor is in the variable sampling period mode, calculating a calculation temperature change curve of an adjacent temperature sensor; acquiring a second temperature actual measurement value of each adjacent temperature sensor to form an actual measurement temperature change curve; judging whether the target temperature sensor fails or not according to the calculated temperature change curve and the actually measured temperature change curve; and when no fault exists, the temperature fluctuation rate is calculated, and the sampling frequency is adjusted according to the temperature fluctuation rate and the temperature difference value. The technical problem of how to reduce the energy consumption of the sensor and ensure the reliability of temperature monitoring at the same time is solved.

The invention discloses a high-precision temperature measurement system and device suitable for profound hypothermia. The high-precision temperature measurement system comprises an excitation module, an acquisition calibration module and a signal processing module. The excitation module is connected between the signal processing module and the acquisition calibration module, generates an excitation signal according to a control signal of the signal processing module, and transmits the excitation signal to the acquisition calibration module; the acquisition and calibration module comprises a temperature acquisition unit and a calibration unit, and the temperature acquisition unit is used for accessing an external temperature sensor and outputting a corresponding original electric signal; the calibration unit is connected to the excitation loop and outputs a standard calibration signal; the signal processing module receives the original electric signal or the standard calibration signal output by the acquisition calibration module, processes the original electric signal or the standard calibration signal, and outputs an excitation control signal to the excitation module to adjust parameters of the excitation signal; and meanwhile, a mode control signal is output to the acquisition and calibration module so as to switch the working mode of the temperature acquisition unit or the working mode of the calibration unit. According to the invention, the accurate measurement requirement of the profound hypothermia + / -0.001 K can be met.

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 distributed optical fiber temperature measurement verification device and method.The device comprises a constant temperature device, a lifting device, a measurement and control host and automatic verification software, the constant temperature device comprises a constant temperature bath and a constant temperature control device, the constant temperature bath comprises a mixing area and a working area, the lifting device drives a test tool to ascend and descend, and the test tool fixes a temperature measurement optical cable; the temperature measurement optical cable is connected with the temperature measurement host, the temperature measurement host feeds back a temperature measurement value to the measurement and control host, the measurement and control host compares the measurement value with a temperature value of a medium in the constant temperature device, and distributed optical fiber temperature measurement verification is achieved. The method passes a temperature measurement range and accuracy test; performing a temperature resolution test; performing a spatial resolution test; testing positioning accuracy; a single-channel test time test comprises six tests, data are automatically collected and analyzed, and a verification report is generated. The device is reasonable in structural design and high in universality, automatic control over the verification process is achieved, data collection, analysis, calculation and report generation are all automatically completed, and verification efficiency is improved.

The invention discloses a multi-temperature-zone staged temperature monitoring management and alarm system and method for kelp drying, and belongs to the technical field of temperature data processing, and the system comprises a temperature zone division module which is used for dividing a drying zone into four temperature zones and monitoring the temperature in real time through a temperature sensor, and a data acquisition module which is used for arranging distributed optical fiber sensors and transmitting the data to a data processing module. The system comprises a temperature acquisition module which acquires temperature data and performs dynamic error correction, a central control module which comprises a data fusion unit, a dynamic threshold calculation unit and a regulation and control instruction generation unit and is used for performing multi-scale noise reduction processing, dynamically updating the temperature threshold of each stage and generating a regulation and control instruction, and an alarm module which comprises a probability analysis unit and a thermodynamic constraint unit. The temperature overrun risk analysis module is used for analyzing the temperature overrun risk, and the power regulation and control module is used for adjusting the heating power of an overrun temperature area and adjusting the running speed of the conveying belt. According to the kelp drying system, the bottlenecks of a traditional drying system in precision, stability and energy efficiency are solved, and intelligence and high reliability of the kelp drying process are achieved.

The invention relates to the technical field of sensors, in particular to a passive wireless temperature sensing method for a high-temperature strong electromagnetic interference environment. Comprising the following steps that a temperature signal is collected through a sensing circuit, and the sensing circuit comprises an inductor and a capacitor; obtaining a resonance signal by utilizing magnetic coupling of a reading circuit and the sensing circuit; processing the resonance signal to obtain a temperature measurement value; the resonant frequency is dynamically corrected by considering the coupling effect of the temperature, the coil line width thermal expansion, the parasitic capacitance temperature coefficient and the working frequency; the mutual inductance coefficient is compensated by considering the cooperative influence of the magnetic conductivity, the loss angle tangent and the coupling distance; errors caused by electromagnetic interference are corrected through beat frequency characteristics of the electromagnetic interference frequency and the resonant frequency, and the multi-physical-field coupling influence under the high-temperature and strong-electromagnetic-interference environment can be dealt with.