5459 results about "Temperature measurement" patented technology

A non-contact temperature measurement system for calculating estimated core body temperature is disclosed. The temperature measurement system can include a sensor that can detect the temperature of a patient and the temperature of ambient surrounding. The temperature of the patient and the ambient temperature can then be used to determine a core body temperature. The temperature measurement system includes an optical module having a light emitter and a light detector. The light emitter emits a beam of light towards the patient and the light detector detects a beam of light reflected by the patient. The reflected beam is analyzed to determine a distance between the temperature measurement system and the patient.

The invention relates to the technical field of electronic manufacturing equipment, in particular to an adaptive thermal compensation system and method for a high-precision mounting head of a chip mounter, and the system comprises a temperature-deformation sensing unit, a thermal-mechanical coupling analysis unit, a dynamic compensation control unit, and a closed-loop execution unit. The temperature-deformation sensing unit collects temperature and deformation data of multiple parts of the mounting head in real time, the thermal-mechanical coupling analysis unit reconstructs a three-dimensional temperature field based on a finite element algorithm, the thermal expansion distribution quantity is dynamically calculated, the problem of rough model of traditional single-point temperature measurement is solved, and the measurement precision is improved. The dynamic compensation control unit predicts the thermal drift amount in the future 5 ms through online parameter identification and a long-short-term memory network model, a compensation strategy is adaptively adjusted in combination with the motion working condition, the closed-loop execution unit decomposes the compensation amount into displacement and torsion correction instructions, accurate offset of thermal deformation is achieved, and a whole-process thermal compensation closed loop is constructed. The precision stability of the mounting head in a complex thermal environment is improved, and the production efficiency is improved.

The invention belongs to the technical field of power system monitoring, and particularly relates to a wireless cable temperature measurement system and method, and the system comprises an operation information collection module, a layout planning analysis module, a data standardization module, a change trend analysis module, an early warning threshold adjustment module, and a fault positioning analysis module. According to the invention, cable operation data and environment information are analyzed, the coverage range, data transmission delay and signal attenuation are considered, the layout of temperature sensors is optimized, the response speed and data accuracy of a temperature sensor network are enhanced, temperature data are formatted and processed, time sequence analysis is carried out, and the temperature change trend is evaluated. Abnormal temperature risk recognition is achieved in the early stage, the accuracy of fault prediction is improved, the cable temperature risk monitoring threshold value is adjusted in combination with cable specifications and meteorological information, the timeliness and effectiveness of risk management are improved, the fault response speed and the system stability are improved, the maintenance cost is reduced, and the reliability and safety of a power grid are improved.

The invention relates to the technical field of power equipment state monitoring, in particular to an oil-immersed transformer distributed temperature measurement method based on a fluorescent optical fiber sensor, and the method comprises the steps: arranging the fluorescent optical fiber sensor in a key temperature rise region in a transformer in a partitioned and layered three-dimensional topological structure, and forming a distributed temperature measurement network; exciting light is injected through a pulse laser to excite a fluorescence signal; a dual-channel phase-locked amplification technology is used to collect signals, and a dual-weight adaptive attenuation model and an oil flow coupling compensation function are combined to demodulate the temperature; reconstructing a dynamic temperature field based on a three-dimensional thermodynamic inversion algorithm, and marking high-gradient hot spots; and temperature, load current and oil flow velocity data are fused to realize graded alarm. According to the invention, the limitation of traditional single-point monitoring is broken through, the strong electromagnetic interference resistance is excellent, a global temperature field can be accurately reconstructed, dynamic early warning is realized, and the operation safety and the operation and maintenance efficiency of the transformer are remarkably improved.

The invention relates to the technical field of mode recognition, in particular to a transformer substation equipment temperature measurement method and system based on visible light guidance. Firstly, a visible light image, an infrared thermogram and vibration spectrum data are synchronously collected, a dynamic compensation coefficient matrix is constructed through illumination intensity analysis, the dynamic compensation coefficient matrix is applied to the infrared thermogram, and illumination interference compensation is achieved. And then, inputting the corrected infrared thermogram and visible light image into a pre-trained heterogeneous atlas matching model, and identifying the category and three-dimensional coordinates of the target equipment. And based on the equipment category information, calling a standard temperature field template in the digital twin model library, establishing a heat conduction path model in combination with the vibration spectrum data, and generating a temperature field prediction reference map of the equipment. And finally, through pixel-by-pixel deviation analysis, inputting the temperature deviation value, the image features and the vibration data into the probability graphic model, and outputting equipment fault information. The method can realize high-precision temperature measurement and fault diagnosis.

The invention discloses a temperature measurement precision optimization method based on multiple sensors, and belongs to the technical field of temperature measurement, and the method specifically comprises the steps: deploying a temperature monitoring array which comprises a fixed position basic sensor group and a position adjustable auxiliary sensor group; scanning the target area through an infrared thermal imaging device to generate a thermal field temperature gradient distribution map; identifying a high dynamic change region boundary based on the thermal field temperature gradient distribution map, and extracting geometric feature parameters of the boundary; constructing a heat flow propagation prediction model according to the boundary geometric feature parameters, and calculating a key monitoring node space coordinate set on a heat conduction path; generating a sensor deployment instruction according to the key monitoring node space coordinate set, and dynamically scheduling an auxiliary sensor group to move to a target position; fusing the temperature data streams of the basic sensor group and the auxiliary sensor group, and executing space-time calibration calculation to generate an optimized temperature field distribution diagram; according to the invention, the coverage integrity and the result accuracy of temperature measurement in a dynamic scene are 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 discloses an intelligent self-monitoring temperature management system for a box-type substation, and relates to the technical field of intelligent power grid equipment monitoring. The problems that an existing system is large in temperature measurement deviation, low in reliability, delayed in early warning, inaccurate in hot spot positioning and extensive in heat dissipation control are solved. According to the scheme, multi-source signals are acquired in parallel through a data acquisition module, and a temperature time sequence is extracted; a boundary calibration module is adopted to fuse data to generate a three-dimensional boundary condition; the multi-physical field solving module obtains an internal temperature / stress field; the physical information prediction module is fused with a heat transfer physical constraint training graph neural network to predict a hotspot migration trend; the hierarchical scheduling module is used for solving a fan and oil pump collaborative optimization instruction in real time based on model predictive control; according to the invention, the accuracy of internal temperature monitoring of the box transformer substation, the reliability of hot spot prediction and the accuracy of heat dissipation control are remarkably improved, the insulation life of equipment is effectively prolonged, and the operation safety and reliability of the system are improved.

The invention relates to the technical field of temperature measurement, in particular to a multi-zone temperature distribution real-time calibration method based on a heating body, which comprises the following steps of: 1, etching on the surface of a metal alloy heating body of which the resistance temperature coefficient is greater than a preset material threshold value to form N discrete series resistance heating units which are electrically connected in series but thermally discrete; 2, establishing a resistance-temperature dynamic relation library of each discrete series resistance heating unit; 3, synchronously measuring the real-time resistance value of each unit when the heating body works; 4, reversely deducing the temperature of a unit center point through a unit exclusive relational expression according to the real-time resistance value, and reconstructing a continuous temperature distribution matrix on the surface of the heating body in combination with a heat conduction equation; and 5, comparing the target temperature field with the real-time temperature field matrix, and adjusting the driving power of the corresponding unit in the out-of-tolerance region. Through continuous calibration and temperature adjustment, accurate control of a temperature field can be maintained in different use environments.

The invention relates to the technical field of spraying process control, and discloses a spraying process self-adaptive adjustment method based on temperature measurement. The method comprises the steps that target coating parameters and base material physical property data are obtained, and initial spraying control parameters are generated through a first intelligent calculation model in combination with historical process data and real-time environment monitoring data; when spraying is executed, heat distribution data of a spraying area are collected in real time through a temperature sensing device, and according to the difference between the heat distribution data and a preset target temperature interval, technological parameters are dynamically corrected through a first self-adaptive regulation and control algorithm; meanwhile, a machine vision system is used for capturing actual coating morphological characteristics, and after the actual coating morphological characteristics are compared with target parameters, excitation parameters are adjusted in a partitioned mode through a second self-adaptive regulation and control algorithm so as to optimize uniformity; and collecting whole-process data, comprehensively evaluating the whole-process data through the second intelligent calculation model to generate a process optimization instruction, and updating the first intelligent calculation model and the first self-adaptive regulation and control algorithm parameters according to the process optimization instruction.

The invention discloses a hydration heat monitoring and dynamic regulation and control method and system in a mass concrete pouring process, and relates to the technical field of concrete pouring, and the method comprises the steps: pre-burying a plurality of dual-mode temperature measurement probes in concrete, collecting dual-mode temperature field data in the concrete in real time, and synchronously collecting environmental parameters; carrying out preprocessing, dynamic weight distribution and data fusion on the obtained dual-mode temperature field data; according to the unsteady state heat transfer equation and the hydration heat model, a finite element heat conduction model is constructed, and the total hydration heat and the temperature difference trend are inverted through actually measured temperature field data; predicting a concrete core and surface temperature difference and a surface and environment temperature difference in a future set time period by combining an LSTM neural network model; and according to the predicted temperature difference result, the cooling water flow rate and the cooling water temperature are subjected to closed-loop regulation. Through the combination of dual-mode sensor temperature measurement and heat inversion, the hydration heat temperature difference in the concrete can be predicted in advance, a cooling scheme is regulated and controlled in real time in a linkage mode, and temperature stress cracks are avoided.

The invention provides a casting system temperature intelligent control method which comprises the following steps: acquiring a casting mold characteristic area, and setting a thermocouple in the mold characteristic area based on casting structure characteristics; a random forest model is established according to thermocouple temperature measurement results and casting quality detection results, recursive feature elimination is carried out, correlation between thermocouple temperature measurement data and casting quality is discriminated, the number of thermocouples is optimized, and the thermocouples are screened; and analyzing according to the temperature data of the thermocouple temperature measuring points, the cooling process parameters and the corresponding casting quality, constructing the relationship among the cooling process parameters, the initial temperature of each mold thermocouple and the casting quality through a gradient lifting decision tree model, and controlling the temperature of the casting system based on the relationship. By arranging the thermocouple and based on the random forest model and the gradient boosting decision tree model, the temperature control accuracy is improved, the temperature is adjusted in time, and the purposes of optimizing the casting process, reducing defects and ensuring high-quality manufacturing of the aluminum alloy hub are achieved.

The invention discloses a multi-target and long-distance field domain temperature measurement method based on dual-spectrum imaging. A visible light camera module and an infrared camera module are included. Obtaining internal parameters and external parameters in the visible light camera module and the infrared camera module, and optimizing the internal parameters and the external parameters; performing quick image feature search and image feature stereo matching on the acquired visible light image and infrared image to realize identification and positioning during image measurement; registering and fusing the visible light image and the infrared image by adopting a double-spectrum image fusion algorithm to obtain a fused image; carrying out image intersection measurement positioning and temperature measurement area stereo matching on the image; performing systematic edge calculation on the image by adopting a data-based intelligent analysis algorithm, and analyzing a temperature change trend according to the obtained image data to obtain the temperature of the measured object; the current running state of the detected power equipment is evaluated, the equipment fault is diagnosed, and the application end is used for storing, displaying and processing the detection result; and the temperature detection accuracy of the power equipment is effectively improved.

The invention relates to the technical field of bolt tightening, and provides an intelligent bolt tightening control method and system based on axial force measurement. Comprising the steps of collecting bolt identification and process parameter data, collecting temperature measurement data, and obtaining sound velocity compensation parameters and elastic modulus compensation parameters. And zero-load preloading data are collected and processed to generate zero-load baseline data, and a self-calibration model is obtained. Axial force data and ultrasonic echo data are collected, and an axial force fusion estimation result is obtained. And comparing an axial force fusion estimation result with target axial force data. And when in the target interval, fine twisting control is carried out based on model predictive control and a micro-stepping strategy, and the controllable damping unit is driven to carry out energy absorption and stopping. And acquiring an axial force fusion estimation result when the target axial force is reached, processing the data in the holding stage to obtain an axial force rebound check result, and if the axial force rebound check result exceeds the limit, performing secondary twisting control. According to the scheme, refinement and traceability of the bolt tightening process are achieved.

The present disclosure provides a method for measuring flow velocity of multilayer groundwater using distributed optical fiber with point-source active heating, comprising: setting and optimizing field test parameters; conducting a background temperature monitoring test; performing a point-source active heating distributed temperature measurement test, including conducting multiple rounds of heating tests; denoising the obtained multi-point source thermal plume attenuation signal data of the groundwater; searching for the peak value of temperature-permeability curve based on an automatic multi-scale peak search algorithm; performing secondary processing on the peak data; estimating the groundwater flow velocity. The method of the present disclosure solves the problem that the existing groundwater flow velocity measurement technology cannot simultaneously measure multiple points and multiple layers, and it can avoid groundwater contamination during the measurement process.

The invention relates to the technical field of fire-fighting engineering, and discloses a real-time fireproof monitoring data transmission system for fire-fighting engineering construction, which comprises a fire parameter analysis module, an environmental data analysis module, a fire source positioning module, a model construction module and a safety database. The fire parameter analysis module generates a temperature change record table through gridding temperature measurement nodes, estimates the smoke diffusion rate, and evaluates the thermal stress and deformation risk of the building structure; the environment data analysis module associates the air velocity with the smoke diffusion rate and corrects the parameter weight of the evaluation model; the fire source positioning module generates a fire source three-dimensional positioning map by using multispectral imaging equipment; the model construction module constructs a dynamic fire assessment model according to multi-dimensional data and outputs a comprehensive threat level; the security database stores building material parameters, historical case characteristics, and dynamic threshold rules. According to the system, through multi-module cooperation and multi-data fusion, the accuracy and timeliness of fire-fighting monitoring are improved, and the system is suitable for safety management of fire-fighting engineering.

The invention relates to a temperature field and deformation field synchronous measurement system and method based on laser speckle DIC and temperature field algorithm temperature measurement. The system comprises a 3CCD color camera, a lens, a three-band filter, a monochromatic light source, a mechanical support adjusting platform, a triangular support and a computer. A test piece is actively illuminated by blue laser, and a color image containing three channel sub-images of red, green and blue on the surface of a high-temperature sample before and after deformation is acquired by a 3CCD color camera. A temperature field algorithm is used for analyzing sub-images of the R channel and the G channel after deformation to calculate a temperature field of the surface of the test piece, and a digital image correlation method is used for analyzing sub-images of the B channel before and after deformation to obtain a strain field of the surface of the test piece, so that synchronous measurement of the temperature field and the deformation field of the surface of the test piece is realized. The principle is simple, the system structure is compact, temperature field measurement is not interfered by speckles, and non-contact, high-precision and synchronous measurement of a material deformation field and a temperature field under the action of force and thermal loads can be achieved.

The invention discloses a PID temperature control system and method for a semiconductor etching machine, and relates to the field of temperature control, and the system comprises a coupling relation construction module, a temperature sensing confidence module, a decoupling compensation module, a coupling relation dynamic updating module, and a transient temperature change control module. According to the invention, by constructing the coupling relation matrix and the inverse matrix thereof, decoupling control of multi-area temperature control is realized, cross interference is effectively suppressed, and the temperature control precision is improved. And a multi-point temperature measurement fusion and anti-interference algorithm is introduced, so that the temperature measurement accuracy and the system robustness are enhanced. A response residual vector is associated with a control vector, and a coupling matrix is dynamically optimized, so that the system has self-learning and model self-adaption capabilities and adapts to working condition changes. And a transient temperature change quick response mechanism is set, so that the control priority can be improved and the PID parameters can be adjusted when the temperature changes suddenly, the response speed and the control stability of the system to abnormal temperature change are remarkably improved, and the thermal uniformity and the process consistency in the etching process are ensured.

The invention discloses a temperature measurement method and device, equipment and a medium. The method comprises the following steps: acquiring a current resistance value of a target thermistor of a temperature sensor; a resistance temperature data set of the target thermistor is obtained, and the resistance temperature data set comprises multiple groups of resistance temperature value pairs of the corresponding relation between the temperature and the resistance; based on the resistance temperature data set, generating a piecewise polynomial fitting function corresponding to the target thermistor; and determining a current temperature value output by the temperature sensor based on the current resistance value and the piecewise polynomial fitting function. The temperature signal is processed through the fitted piecewise polynomial fitting function, so that the complexity and nonlinear change of the signal can be better adapted, the risk of over-fitting is effectively reduced, and the accuracy of the output temperature of the thermistor is improved.

The invention relates to a turbine blade global temperature field reconstruction method based on a multi-modal physical constraint network, and belongs to the technical field of aero-engine thermal management. Aiming at the problems of insufficient global heat conduction path modeling, lack of physical rules and blank region differentiation perception, carrying out normalization and position coding on sparse temperature measurement points to form a Transform encoder input sequence; extracting features through an encoder and compressing the features into global feature vectors through self-attention pooling; decoding the image into a temperature field image by adopting a U-Net generator fused with jump connection; a multi-scale discriminator is constructed, a semantic weighting mechanism is introduced, and differentiated weights are distributed to cooling holes, tenons and pressure surface areas; a physical constraint loss and local energy conservation loss are constructed based on a heat conduction equation, and a weighted training model is combined with confrontation loss and temperature error loss. The method is used for providing high-precision temperature distribution data support for turbine blade structure optimization design, cooling system efficiency evaluation and thermal fatigue prevention.

The invention discloses a method for online reconstruction of a temperature field of a cutting area of a temperature measurement end mill. The method comprises the following steps: constructing a milling cutter three-dimensional model; establishing a milling heat conduction model; finite element analysis software is used for conducting heat conduction positive problem simulation under different heat flow densities; extracting a temperature value of each node and calculating a temperature sensitivity coefficient; acquiring a temperature data sequence at the temperature measurement position; establishing and training a heat conduction inverse problem algorithm model; acquiring real-time temperature data and predicting heat flux density through a temperature measurement module; and on-line reconstruction of the temperature field of the cutting area is realized in combination with the temperature sensitivity coefficient and the predicted heat flux density. The method can monitor the cutting temperature in real time, optimize the machining parameters, prolong the service life of the cutter and improve the machining precision.

The invention relates to the technical field of boiler temperature measurement, in particular to a waste heat boiler three-dimensional temperature field construction method and system and a medium. The method comprises the following steps: performing optical fiber sensor grid deployment on the waste heat boiler to obtain a distributed temperature acquisition network; sampling the distributed temperature acquisition network to obtain a boiler real-time temperature sequence; performing data preprocessing on the boiler real-time temperature sequence to obtain a boiler initial temperature field; based on the initial temperature field of the boiler, fluid dynamic model parameter construction is conducted on the waste heat boiler, and a boiler fluid characteristic parameter set is obtained; performing multi-physical field coupling on the boiler fluid characteristic parameter set to obtain a boiler theoretical temperature field; acoustic sensor array arrangement and data acquisition are carried out on the waste heat boiler, and acoustic spectrum acquisition data are obtained. By fusing various temperature field data, respective advantages and limitations can be complemented, and comprehensive and accurate temperature information of the waste heat boiler is obtained.

The invention relates to the technical field of numerical control machine tool control, in particular to a data-driven numerical control machine tool temperature compensation method and system, and the method comprises the steps: comparing the variation trend of temperature data and the difference of the amplitude between a temperature measurement point and a homologous measurement point; obtaining a temperature interference degree by combining the similarity of the autocorrelation degree of the temperature data between the temperature measuring point and the homologous measuring point, and determining a temperature weight coefficient by combining the correlation degree between the displacement data of the main shaft of the numerical control machine tool in the main direction and the temperature data of any homologous measuring point of each temperature measuring point at all acquisition moments; and compensating the temperature of the numerical control machine tool at the current moment. The invention aims to improve the precision of temperature compensation of the numerical control machine tool.

The invention discloses a light field tomography system and a flame three-dimensional temperature field reconstruction method, and belongs to the technical field of flame temperature measurement. The problem that the temperature field reconstruction error of an existing light field tomography method is large is solved. The method comprises the following steps: firstly, shooting a light field image of a measured flame by using a light field tomography system, dividing a space region where the measured flame is located into micro-element bodies, and then performing flame radiation ray tracing from each pixel point on the light field image of the measured flame; establishing a radiation transfer equation set according to a tracing result of flame radiation light, obtaining a reconstruction equation set according to the established radiation transfer equation set, and solving the reconstruction equation set based on multi-point accurate temperature measurement value information of a thermocouple to obtain black body spectrum radiation intensity of each infinitesimal body of the flame; and finally, converting the black body spectrum radiation intensity of each infinitesimal body into the temperature of each infinitesimal body to realize temperature field reconstruction. The method can be applied to flame three-dimensional temperature field reconstruction.

The invention discloses an artificial stratum freezing engineering monitoring and early warning method and system based on digital twinning, and relates to the field of underground engineering. According to the method, the three-dimensional geometric structure of an artificial stratum freezing engineering site, freezing pipe arrangement, the preset temperature of freezing liquid and stratum physical and mechanical parameters are calculated according to the three-dimensional geometric structure, the freezing pipe arrangement, the preset temperature of freezing liquid and the stratum physical and mechanical parameters; the stratum thermophysical parameters serve as the actual situation of the freezing project and are input into the numerical model, and prediction data of all positions of an artificial stratum freezing project site within preset time are output; determining the numerical model as a trained numerical model based on the preset value, the prediction data and the real temperature of the rock-soil body monitored at each temperature measurement point in real time; based on the trained numerical model, determining target prediction data of each position of the artificial stratum freezing engineering site within a preset time; based on the target prediction data, determining a freezing result of the on-site artificial stratum freezing project; and according to the freezing result and a preset deformation standard, determining an abnormal freezing result and carrying out early warning. And the monitoring and early warning efficiency of the freezing effect is improved.

The invention relates to a mass concrete raft foundation three-dimensional temperature field reconstruction method, and relates to the technical field of concrete raft foundation structure three-dimensional temperature field reconstruction. The method comprises the following steps: arranging temperature sensing optical fibers in a plurality of temperature measurement areas of a concrete raft foundation to be measured; constructing an optical fiber temperature measurement monitoring system, and obtaining space-time temperature data; a temperature field prediction model is constructed, the temperature field prediction model is based on a physical information neural network, and a data loss function, a physical loss function and an initial condition loss function are fused; performing multi-objective loss function joint optimization training on the temperature field prediction model based on the space-time temperature data; utilizing the trained temperature field prediction model to predict the temperature value of the concrete raft foundation to be measured at any time and space point coordinates; and reconstructing a three-dimensional temperature field based on a prediction result output by the temperature field prediction model. By adopting the method, high-precision reconstruction of the three-dimensional temperature field of the mass concrete raft foundation can be realized.

The invention provides a non-contact multi-mode thermal imager temperature measurement method, and relates to the technical field of non-contact temperature measurement, and the method comprises the steps: collecting the three-dimensional structure information of a measured object, obtaining infrared thermal radiation data, and collecting meteorological parameters; identifying the material and the surface state of the object, and adjusting an infrared emissivity parameter by using a deep learning model; performing cross-modal feature alignment on the related data; and inputting the meteorological parameters into the environment interference model to correct the infrared signal, determining whether the temperature measurement data is qualified, and if yes, repeating until the temperature measurement of the measured area is completed. According to the invention, by fusing the multi-modal data and utilizing the deep learning model, the space-time attention mechanism, the environment interference model and the like, the dynamic calibration of the infrared emissivity, the feature alignment of the multi-modal data and the effective compensation of the environment interference are realized; the problems of large environmental interference, difficult emissivity calibration, insufficient complex scene adaptability and the like of a traditional method are solved, and the temperature measurement precision and reliability are improved.

The invention relates to the technical field of optical fiber sensing, and provides a distributed fiber bragg grating temperature measurement method for boiler wall temperature measurement, which comprises the following steps of: firstly, preparing a sensor probe consisting of grating optical fibers, connecting the sensor probe with a demodulator, and starting the demodulator after the sensor probe is mounted; the laser is started, a wide-spectrum light source emitted by the laser enters the optical fiber, when the wall temperature of the boiler changes, the effective refractive index and the grating period of the grating are changed, then the Bragg wavelength moves, the data demodulation module detects the movement amount of the wavelength and converts the movement amount into corresponding temperature data, and the temperature data are transmitted to the optical fiber. Then analyzing, calculating and displaying the data; the temperature of the temperature measuring point of the furnace wall is measured through the sensor probe based on the fiber bragg grating, the demodulator analyzes the temperature data and displays the temperature data through the display screen, and therefore accurate temperature measurement of the furnace wall is achieved.

The invention discloses a high-temperature surface contact thermal resistance elimination method based on double thermocouple compensation, and belongs to the technical field of material thermal property characterization and testing. The method comprises the following steps: synchronously acquiring double-thermocouple temperature, and obtaining a temperature difference signal through filtering calibration and environment correction; calculating the real-time heat flux density according to the corrected temperature difference, the Seebeck coefficient and the dynamic correction factor; establishing a nonlinear dynamic coupling model containing contact thermal resistance parameters, and performing temperature interval division; identifying a contact thermal resistance parameter on line by adopting a self-adaptive recursive least square algorithm, and generating a dynamic thermal resistance compensation value; and applying the compensation value to a double-thermocouple signal according to the weight, and outputting accurate high-temperature surface temperature. According to the method, data acquisition and preprocessing, dynamic heat flow correction, nonlinear segmented modeling, self-adaptive online identification and refined compensation output strategies are adopted, the influence of high-temperature surface contact thermal resistance can be effectively eliminated, and the accuracy and reliability of temperature measurement in the high-temperature environment are remarkably improved.

The invention discloses a platinum resistor high-precision temperature measuring device capable of automatically identifying a wiring mode. The platinum resistor high-precision temperature measuring device comprises a power supply module, a signal detection module, an isolation module, a signal processing module and a cold end temperature measuring module. The power supply module supplies power to the signal detection and processing module. The signal detection module comprises a sensing probe, a wiring identification circuit, a constant current source, a measuring circuit and an analog-to-digital conversion circuit. The sensing probe measures the measured temperature, the wiring identification circuit automatically judges a two-wire system, a three-wire system or a four-wire system and feeds back a result, the constant current source provides positive and negative constant current excitation, and the measuring circuit collects and processes feedback voltage and then sends the feedback voltage to the analog-to-digital conversion circuit. The analog-to-digital conversion circuit is connected with the signal processing module through the isolation module, and the signal processing module calls a corresponding algorithm according to a wiring identification result and outputs final temperature data. According to the invention, high-precision temperature measurement at the grade of + / -0.02 DEG C can be realized in the range of-200 DEG C to 850 DEG C under the three / four-wire system and low-speed sampling conditions.