4391results about "Radiation pyrometry" patented technology

The invention relates to an infrared spectrum baseline drift dynamic compensation method and system based on multi-parameter fusion, and the method comprises the steps: continuously obtaining spectrum data, current environment parameters and light source state data of a target oil full wave band, carrying out the feature extraction, and obtaining a baseline drift sensitive feature set and a coupling feature set; constructing a prediction model taking the baseline drift amount as output, and taking the baseline drift sensitive feature set and the coupling feature set as input; the reverse baseline drift amount based on the baseline offset of each wave band is superposed in the spectral data as compensation; according to the invention, through multi-source data acquisition and analysis, monitoring of spectrum baseline drift influence factors is realized; accurate correction of different spectral characteristics is realized through a dynamic compensation strategy special for a wave band; and through a continuous self-adaptive updating mechanism, stable tracking of the long-term drift trend is realized, and the effect of prolonging the equipment maintenance period is achieved.

The invention discloses a collaborative diagnosis method for partial discharge and overheating faults of a high-voltage switch cabinet, and particularly relates to the technical field of fault diagnosis of the high-voltage switch cabinet. Signals are synchronously acquired through ultrahigh frequency, acoustic emission and infrared sensors, and an abnormal candidate sequence is extracted through adaptive baseline segmentation; through laser calibration and time interpolation calibration, uniform event position information and timestamps are mapped; identifying potential coupling pairs of partial discharge and hot spot events based on dynamic threshold and time difference matching; generating a high-risk linkage region through spatio-temporal clustering, trajectory analysis and region fusion; updating the diagnosis model based on the high-frequency data increment, and generating a collaborative diagnosis report; the method breaks through the limitation of a static threshold value and a single sensor, and remarkably improves the diagnosis precision and adaptability of a composite fault under a complex working condition.

Disclosed are an apparatus, system, and method of a visual sensor of a tactical gear to use facial recognition technology to identify a person of interest and to cause a responsive device on the tactical gear to notify a wearer. In one embodiment, a personal protective equipment includes a responsive device integrated in a tactical gear and a visual sensor. The visual sensor of the tactical gear identifies a target person using an identity artificial intelligence model. The responsive device notifies a wearer of the tactical gear when the visual sensor identifies the target person. Further, the responsive device notifies an additional person when the visual sensor identifies a threat to a protectee of the wearer and the additional person. The responsive device may vibrate when the visual sensor of the tactical gear detects an ambient threat to the protectee of the wearer.

A temperature control device includes a temperature detector, a difference operation unit, a controller, a saturation processing circuit unit, a rewritable storage unit, and a conversion unit. The difference operation unit operates a digital value corresponding to a difference value between a detected temperature value and a target temperature. The controller calculates a manipulated variable using the digital value operated by the difference operation unit. The saturation processing circuit unit includes a digital circuit to limit an output value of the controller to a pre-set upper limit value. The rewritable storage unit stores the upper limit value read from a storage area of the rewritable storage unit and input into the saturation processing circuit unit. The conversion unit converts the output value of the saturation processing circuit unit into an analog signal to output the converted value as a control command value to the heater.

The invention provides a data detection method and system, a detection device, computer equipment and a storage medium, and the method comprises the steps: obtaining a detection signal of each wafer surface in a planetary reaction cavity, and cutting the detection signal based on a trigger signal to obtain a first signal sequence and a second signal sequence; processing the first signal sequence by adopting a classification model to obtain a material type on each wafer; querying a corresponding optical model based on the material type; and performing iterative optimization on the optical model, the first signal sequence and the second signal sequence by adopting a decoupling algorithm to obtain a temperature detection value and a reflectivity detection value. According to the method, the original detection signal is segmented into the independent signal sequences based on the trigger signal, then the material type is determined according to the independent signal sequences, the corresponding optical model is selected according to the material type, and finally the temperature detection value and the reflectivity detection value with high accuracy are obtained through decoupling according to the optical model. Accurate analysis of a single wafer signal is realized, and process repeatability and stability are greatly 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 terrain reconstruction and path planning, and particularly provides a night terrain reconstruction and path planning method and system based on multi-sensor collaboration, and the method comprises the steps: obtaining the multi-source sensing data of a night environment through a data collection module; performing multi-source data fusion processing on the multi-source sensing data to generate a night environment reconstruction model fusing multi-dimensional features; performing obstacle semantic analysis on the night environment reconstruction model, extracting static obstacle distribution information and a dynamic obstacle movement track, and constructing a composite environment map; according to the composite environment map, a passable path is generated through a dynamic optimization algorithm in combination with terrain passability parameters and kinematics constraint conditions of a mobile carrier, and path parameters are dynamically adjusted based on real-time update data of a night environment reconstruction model; when it is detected that the obstacle distance or the motion state exceeds a safety threshold value, path real-time correction and graded obstacle avoidance instruction output are triggered through multi-sensor confidence evaluation and path collision risk prediction.

A platform for characterizing biomolecules, biological tissue sections, viruses, or other particles of interest in a non-invasive, high-throughput, cost-effective, and label-free manner. The platform includes a merged set of imaging modalities including and capable of interferometric microscopy and wide-field or confocal microscopy (such as, for example, a wide-field super-resolution surface enhanced Raman spectroscopy, SERS), although some aspects may be employed with data sets only received from wide-field or confocal microscopy. Related devices, systems, methods, techniques, and variations to the same are also provided.

The invention provides a multi-sensor fusion welding temperature monitoring method and a related device, and the method comprises the steps: dividing a welding region into a plurality of sub-regions according to the spatial distribution of the welding region, and obtaining the initial temperature data corresponding to each sub-region according to various temperature sensors; performing time alignment on the initial temperature data through difference resampling of different sampling points to generate a time sequence temperature matrix; performing real-time quality detection on the time sequence temperature matrix to generate a real-time quality score, and performing weighted combination on the real-time quality score and a preset confidence coefficient parameter table to obtain a dynamic confidence coefficient result set; fusing the effective temperature data exceeding a preset confidence threshold in the dynamic confidence result set according to a fusion rule corresponding to each sub-region to obtain a fused temperature result; and the fusion temperature results of the sub-regions are subjected to time sequence splicing to obtain a global temperature curve of the welding process, so that the accuracy of temperature detection in the welding process can be effectively improved.

The invention provides a cloud condition adaptive geostationary satellite sea surface temperature inversion method based on deep learning, and relates to the technical field of sea surface temperature inversion, and the method specifically comprises the steps: obtaining geostationary satellite observation data, geographic information data, polar orbit satellite sea surface temperature and cloud products, and analyzing the sea surface temperature and atmospheric background data; performing standardization preprocessing on the obtained stationary satellite observation data; constructing a cloud detection data set; a cloud detection model of deep learning is constructed and trained; constructing a clear sky data set; a clear sky inversion model of deep learning is constructed and trained; constructing a data set for under-cloud inversion model training; constructing an under-cloud inversion model of deep learning and training the under-cloud inversion model; and integrating the cloud detection model, the clear sky inversion model and the under-cloud inversion model, adaptively calling the corresponding model according to a real-time cloud detection result, and generating a final sea surface temperature product. According to the technical scheme, the problem that in the prior art, the accuracy of a reconstructed product on the spatial structure cannot be comprehensively reflected is solved.

The invention provides a cavity target infrared characteristic calculation ray tracing method, and belongs to the technical field of infrared tracing. The method comprises the following steps: importing a CFD data source; a cuboid space grid is generated, and CFD data space distribution is interpolated and reconstructed; a target material and temperature parameters are set; determining the position of a detector and forming a detection situation relationship; gridding a detection space in the transverse direction and the longitudinal direction at the position of the cavity object to form a field pixel space; constructing a reverse ray vector direction, and counting self reflection and reflection radiation of each triangular infinitesimal according to a recursive iteration mode; reconstructing a broadband spectral reflection coefficient according to the narrowband BRDF model and the broadband spectral emissivity; and determining the reflection direction of the infrared rays based on a bidirectional reflection distribution model to realize ray tracing. According to the invention, the control of any ray tracing depth can be realized, the intersection judgment process is greatly simplified, and the problem of high-efficiency and high-precision calculation of the cavity and the low-emission material is effectively solved.

The invention relates to the technical field of power system equipment state monitoring and fault diagnosis, and discloses an arc light online monitoring method and system based on a spectrum sensing technology, and the method comprises the steps: arranging a first spectrum sensor and a second spectrum sensor corresponding to a detected target, and respectively detecting optical signals in different wavelength ranges; collecting optical data according to a set period, and identifying abnormal features according to a preset template; when the double abnormal features exist, the duration of the double abnormal features is calculated, and if the duration exceeds the corresponding reference duration, a duration reference value is generated; and performing weighted calculation on the time length analysis value, if the time length analysis value is within a preset range, giving a partial discharge abnormal prompt, and resetting the reference value. Multi-wavelength spectrum monitoring is utilized, non-contact and high-sensitivity detection of partial discharge is achieved, electrical equipment is prevented from being damaged, fault hidden dangers are found in time, and safe and stable operation of the equipment is guaranteed.

The invention provides a printing color consistency automatic calibration and management system and method, and the method comprises the steps: collecting a current environment temperature and humidity ink matching parameter density curve data dot increase compensation parameter in real time through a state detection device, and forming a current state data set; performing similarity analysis on the reference data set and the current state data set by adopting a matching degree evaluation algorithm, and judging a relationship between a matching degree numerical value and a preset threshold value; adjusting and correcting the calibration reference value and the color control parameter in the reference data set according to the offset compensation set to obtain a compensated and adjusted parameter set; on the basis of the compensated and adjusted parameter set, generating update code data by combining a current time identifier and an operator identifier, and forming new two-dimensional code information; and outputting the new two-dimensional code information to a subsequent work order carrier by adopting a code generation module, and establishing a parameter transmission tracing chain.

The invention discloses a calibration device with a spectrum self-calibration function and a high-resolution spectrum calibration method thereof. The device comprises a narrow-band light source, a broadband light source, an optical fiber isolator, a coupler, an interference system, a multi-way switch, an FP (Fabry-Perot) cavity, a collimator, an orthogonal dispersion system and a computer, wherein the orthogonal dispersion system consists of a cylindrical lens, a reflector, a virtual phase array, a grating, a focusing lens and an industrial camera; according to the device, different light source paths are gated, FP cavity modulation and orthogonal dispersion system light splitting are utilized, and an industrial camera is combined to receive light signals. According to the method, the mapping relation between pixels and wavelengths can be established, the two-dimensional spectrum is compressed into the one-dimensional calibration spectrum through light intensity modulation and normalization processing, the calibration process of the orthogonal dispersion system is simplified, and the measurement precision is improved; and system drift can be compensated in real time through self-checking calibration, and the reliability of a measurement result is ensured, so that accurate calibration and measurement of a high-resolution spectrum can be realized.

The invention, which relates to the technical field of plant safety monitoring, discloses an AI-vision-based plant safety monitoring and emergency linkage system comprising a sensing acquisition module, a feature completion module, a behavior analysis module, a risk assessment module, a deduction planning module, a linkage execution module and a model updating module. The sensing acquisition module is used for arranging a multi-mode sensing unit in a factory area, acquiring a visible light image, infrared thermal imaging data and millimeter wave radar point cloud, performing timestamp alignment and space coordinate mapping on the three types of data, and outputting an original sensing data set; the feature completion module is used for judging environment quality according to brightness and contrast indexes of a visible light image, extracting a human body point cloud cluster based on millimeter wave radar point cloud when the indexes are lower than a preset threshold value, generating three-dimensional attitude key points through clustering and a skeleton regression algorithm, performing fusion verification in combination with a human body thermal contour in an infrared image, and obtaining a fusion verification result. And outputting the human body posture feature map.

An optical device includes: a first optical system; and a second optical system. The first optical system includes a first light splitting device configured to split measurement light emitted from a first light source into a first measurement light and a second measurement light and then mix the split measurement light, a first mirror configured to add a first modulation signal by being moved in an entering direction of the first measurement light and reflecting the first measurement light, a second mirror configured to reflect the second measurement light, and a first light receiving device configured to receive the measurement light including a sample-derived signal and the first modulation signal and output a first light receiving signal. The second optical system includes a second light source configured to emit laser light, an optical modulator configured to add a second modulation signal to the laser light, and a second light receiving device configured to receive the laser light including a displacement signal generated by reflection on the first mirror and the second modulation signal and output a second light receiving signal.

The invention discloses a real-time automatic focusing hyperspectral acquisition method and a real-time automatic focusing hyperspectral acquisition device. The real-time automatic focusing hyperspectral acquisition method comprises the following steps: step 1, acquiring dark background pixel signals; 2, automatic focusing is carried out; 3, repeating the step 2 until the requirement is met, recording automatic focusing data, and performing spectrum acquisition to obtain original spectrum data; step 4, calculating a full-width object distance matrix of the original spectral data based on the phase difference finally obtained in the step 3; 5, correcting the original spectral data based on the full-width object distance matrix to obtain corrected spectral data; and step 6, calculating the corrected reference plate spectral data based on the corrected spectral data and the dark background pixel signal, calculating the reflectivity of the target object to be measured, and realizing real-time automatic focusing hyperspectral acquisition. The method innovates a phase difference analysis method, and efficiently processes light change and target offset in a dynamic scene; the combination of the two improves the focusing precision and stability, effectively solves the problem that the scanning target in the dynamic scene is liable to defocus, and achieves the efficient adaptation of the dynamic scene.

The invention discloses an ultra-high-speed imaging device based on acousto-optic filtering modulation. The ultra-high-speed imaging device comprises a spectrum modulation system, a spectrum imaging system and a data processing system. The spectrum modulation system utilizes an acousto-optic tunable filter (AOTF) to dynamically modulate broadband continuous spectrum light, narrow-band illumination light which rapidly changes along with time is generated, and time information of a dynamic scene is effectively mapped to a spectrum dimension. And the spectral imaging system images the spectral coded dynamic scene to the hyperspectral camera to realize acquisition of spectral space-time information. The data processing system performs spectral crosstalk correction, channel separation and demosaicing reconstruction on the acquired original mosaic image, and recovers a time sequence image according to a spectrum-time mapping relation, thereby realizing single-shot superspeed imaging in a dynamic process. The device has the advantages of being simple and compact in structure, flexible in time window, high in imaging fidelity and the like, and has wide application prospects in the fields of rapid dynamics such as microfluidics, laser processing and ultrafast physics.

The invention relates to the technical field of electrical equipment insulation performance detection, in particular to an insulating oil dielectric loss test system based on temperature compensation, which comprises a temperature acquisition module for acquiring insulating oil temperature data and environment temperature data; the dielectric loss measurement module measures a dielectric loss value and a dielectric loss angle through a self-adaptive anti-interference algorithm, and synchronously records voltage and frequency; the intelligent compensation module matches temperature characteristic parameters for different temperature intervals, and compensates a dielectric loss detection value through a segmented temperature compensation model; the state analysis module judges the aging degree and state of the insulating oil according to the compensated dielectric loss value and acid value, generates a multi-stage early warning signal and a diagnosis report by combining the breakdown voltage and the moisture content, and dynamically adjusts the test frequency according to the oil sample type and the operating age limit; and the cloud management platform stores historical data and compensation parameters, establishes a performance degradation model, analyzes a dielectric loss trend and generates maintenance suggestions. Therefore, the problems of insufficient test precision, poor environmental adaptability and the like in the prior art are solved.

The present disclosure relates to an infrared camera module comprising an infrared image sensor, an outer window, inclined with respect to an optical axis of the infrared image sensor and held in a window mount comprising a shape adapted to cooperate, in a removable manner, with a receiving part surrounding a hole passing through a glazing, and an interface part providing a mechanical link between the window mount and the infrared image sensor.

The invention discloses a reconstruction spectral imaging system based on an electromagnetic drive Fabry-Perot resonant cavity, and belongs to the field of spectral imaging. The system comprises an optical lens group, an electromagnetic driving device, a Fabry-Perot resonant cavity, a photoelectric detection array and a calculation unit, the cavity length of the Fabry-Perot resonant cavity can be adjusted through the electromagnetic driving device. The optical lens group receives light reflected or emitted by an external to-be-measured target scene and carries out collimation processing, and then the light enters the Fabry-Perot resonant cavity. The Fabry-Perot resonant cavity screens the incident light based on the resonance condition of the cavity length of the Fabry-Perot resonant cavity, and the screened light is emitted to the photoelectric detection array; the photoelectric detection array converts the incident light intensity into an electric signal and outputs the electric signal to the calculation unit; and a spectrum reconstruction model is built in the calculation unit, and a hyperspectral image of the to-be-measured target scene is obtained by using the spectrum reconstruction model based on the electric signal. The working range and the spectral imaging precision of the spectral imaging system based on the Fabry-Perot resonator are improved, the technological requirements are reduced, and the engineering applicability of the spectral imaging system based on the Fabry-Perot resonator is improved.

The invention discloses a temperature real-time monitoring method and system based on mass concrete continuous pouring, and the method comprises the steps: collecting data in a mass concrete continuous pouring process in real time through the arrangement of sensors, forming a global temperature set of temperature values at each collection moment, obtaining the temperature value of each layer at each collection moment according to pouring layering, and carrying out the real-time monitoring of the temperature of each layer; forming a layered temperature set of the temperature values of each layer; determining a concrete pouring abnormal index; determining a dynamic early warning threshold value in the concrete continuous pouring process, determining a multi-stage early warning and response mechanism according to comparison between the concrete abnormal index and the threshold value, and generating an early warning control signal; and based on the early warning control signal, controlling the water cooling equipment and carrying out real-time monitoring feedback. According to the method, the specific temperature conditions of each layer at different acquisition moments can be precisely known, the positions of the layers with abnormal temperature can be more precisely positioned, structural cracks caused by temperature incoordination between the layers are avoided, and real-time monitoring of the temperature of mass concrete continuous pouring is achieved.

The invention discloses an infrared temperature measurement calibration method and device for a CMAS high-temperature corrosion thermal barrier coating. The method comprises the following steps: preparing a thermal barrier coating sample coated with CMAS and provided with holes in the side surface; placing the sample in a high-temperature furnace, and inserting a high-temperature thermocouple into the sample temperature measuring hole; adjusting the high-temperature infrared thermometer to align a temperature measuring light path of the high-temperature infrared thermometer with a to-be-measured area on the surface of the sample; heating the high-temperature furnace to a preset temperature and preserving heat; and comparing thermocouple and infrared temperature measurement data in real time, adjusting the infrared emissivity to enable the difference between the thermocouple and the infrared temperature measurement data to be within a preset error range, and determining the infrared emissivity parameter of the sample at the temperature. According to the method provided by the invention, the infrared temperature measurement parameters of the thermal barrier coating under different CMAS corrosion conditions can be accurately calibrated, so that the corresponding infrared emissivity is obtained, and a key technical support is provided for checking and evaluating the high-temperature CMAS corrosion service life of the thermal barrier coating and testing the reliability of the service life. Meanwhile, the device adopted by the invention is simple in structure, simple and convenient to operate, accurate and effective in test result and good in application value.

The invention provides an Internet of Things smart farm monitoring method and system, and relates to the technical field of agricultural Internet of Things, and the method comprises the steps: executing the triggering type sensing operation of crop growth and environment abnormality at a field end side visual node of an Internet of Things smart farm based on a preset triggering condition, and outputting an end side initial sensing data set; performing non-redundant feature screening on an end-side initial sensing data set, extracting a key feature set, executing a staged slow aggregation operation through a low-power-consumption communication network, outputting batch feature data packets according to a link state, and realizing field light-flow transmission; the cloud processing platform receives the batch feature data packets, then calls the agronomy knowledge set for restoration and diagnosis, outputs a farm monitoring diagnosis result, generates a field equipment linkage instruction according to the farm monitoring diagnosis result, sends the field equipment linkage instruction to the execution equipment, and outputs an equipment linkage response result, so that the farm monitoring efficiency and accuracy are improved, and the farm monitoring accuracy is improved. Intelligent management is realized, and the field operation cost is reduced.

The invention provides a compact hyperspectral imager optical system and an imaging method thereof, which are used for solving the technical problems that the overall size of a front telescopic assembly in a traditional hyperspectral imager optical system is difficult to compress, the installation and adjustment difficulty is relatively large, or the incident energy is lost and the space coverage capability is insufficient. And the technical problems of low energy utilization rate and difficulty in improving the sensitivity and the signal-to-noise ratio of the hyperspectral imager of the traditional Dyson type dispersion light splitting assembly are solved. The invention provides a compact hyperspectral imager optical system, which comprises an off-axis two-image-reflection telecentric optical path system based on a free-form surface and a Dyson light splitting system based on a curved surface prism, and realizes high regulation and control capability on light through multiple degrees of freedom of a curved surface shape. Compared with the prior art, the high-spectral imaging device has the advantages that the high-spectral imaging device is simple in structure, high image quality, small distortion and good telecentricity are achieved, meanwhile, the curved prism serves as a dispersion light splitting element, the whole spectrum has high light splitting efficiency, and the signal-to-noise ratio and sensitivity of the high-spectral imaging device can be improved.

The invention relates to the technical field of remote sensing image intelligent processing, in particular to a multi-scale progressive surface temperature fusion downscaling method and device, and the method comprises the steps: preprocessing a surface temperature image in a multi-scale image library; constructing a multi-scale training data set containing the surface temperature and at least one auxiliary parameter; constructing a surface temperature downscaling network based on multi-parameter fusion, and constructing a domain transformation network based on heterogeneous high-frequency information guidance; training a surface temperature downscaling network and a domain transformation network based on a progressive dual-network joint training strategy; finely adjusting the downscaling model meeting a preset low-medium resolution condition; and performing low-medium-high progressive downscaling on the low-resolution surface temperature image to be processed to generate a multi-scale progressive surface temperature meeting a target high-resolution condition. The method fully considers the problem of descending scale difference of different resolutions, achieves the maintenance of the physical characteristics of the surface thermal field, and improves the processing efficiency of large-area remote sensing data.

The invention discloses an intelligent spectrum temperature measurement method based on a gated hybrid expert model, and the method comprises the steps: carrying out the registration of a multi-channel image, extracting an average gray value in a region of interest, and calculating the gray value ratio between different channel pairs; each group of channel pair corresponds to one expert sub-model, the gray value ratio of the channel pair is input of the expert sub-model, and each expert sub-model gives a preliminary prediction temperature according to the gray value ratio of the corresponding channel; the plurality of expert sub-models are constructed into a gated hybrid expert framework based on a gated network BiGRU, and the gated network distributes a corresponding weight coefficient to each expert sub-model; and carrying out weighted summation on the temperature prediction value output by each expert sub-model and the corresponding weight coefficient to obtain a final prediction temperature value. According to the method, the gray value ratio is serialized, intelligent decision making is carried out by using the time sequence modeling capability of the BiGRU network, adaptive fusion of all expert models is realized, and errors caused by emissivity changes are effectively inhibited.

Performance evaluation and structural optimization methods for a high-power semiconductor laser chip, and a performance evaluation system for a high-power semiconductor laser chip. The performance evaluation method for a high-power semiconductor laser chip comprises: providing a window on an N-side electrode of a chip to be tested (step 1); keeping the chip in an operating state (step 2); allowing a quantum well active region of the chip to generate spontaneous emission, so that the spontaneous emission is imaged outside the chip (step 3); acquiring, by means of a spectrograph, a spectrum of the spontaneous emission outside the chip and obtaining a two-dimensional distribution of a quantum well temperature of the chip in the operating state; and acquiring, by means of a CCD camera, an image of the spontaneous emission imaging outside the chip and obtaining a two-dimensional distribution of charge carriers in the quantum well of the chip in the operating state (step 4). According to the performance evaluation and structural optimization methods for a high-power semiconductor laser chip, the distributions of the temperature and the charge carrier concentration in the quantum well of the chip to be tested in the operating state in which the resolution is freely adjusted can be obtained. Operations of the methods are convenient, and implementation is simple and easy, thereby efficiently improving the accuracy of an evaluation result.

The invention provides a temperature measurement system and compensation method of non-direct contact fluid, and relates to the technical field of temperature detection. The temperature measurement system comprises a dynamic compensation module, a steady-state deviation compensation module and a steady-state judgment module, the temperature sensor collects the temperature value of fluid which is not in direct contact with the temperature sensor, and the temperature value is subjected to hysteresis compensation through the dynamic compensation module. The steady state judgment module judges whether the temperature is in a steady state or not according to the temperature value subjected to hysteresis compensation, and if not, the temperature value subjected to hysteresis compensation is output; if yes, a steady-state deviation compensation module carries out steady-state deviation compensation on the temperature value after hysteresis compensation and then outputs the temperature value. The temperature measurement system can effectively improve the accuracy and response characteristics of non-contact fluid temperature measurement by combining dual mechanisms of dynamic compensation and steady-state deviation compensation.

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to a real-time icing detection method based on unmanned aerial vehicle multi-mode image fusion, which comprises the steps of multi-mode image acquisition, image preprocessing, multi-mode image fusion, icing detection model construction, real-time icing detection and early warning and system integration. Unmanned aerial vehicle control, image acquisition, image fusion, data processing, model reasoning and early warning notification are integrated to an unmanned aerial vehicle edge computing platform, and early warning information is transmitted to a ground control center in real time through a 5G module. The power transmission line icing detection efficiency, accuracy and real-time performance are comprehensively improved, an advanced, reliable and efficient solution is provided for safe and stable operation of a power system, and the method has remarkable technical advantages and wide application prospects.