344 results about "Radiant intensity" patented technology

The invention discloses a distributed real-time monitoring and early warning system for a temperature field of a smelting furnace, and relates to the technical field of industrial process intelligent monitoring. The problems of accumulated measurement errors and non-stationary hotspot escape reconstruction hysteresis caused by static emissivity setting in an existing system are solved. Collecting multiband radiation intensity and voltage signals through time domain alignment of the multispectral sensor array and the thermocouple array; iterating emissivity parameters in real time by adopting a dynamic ash body spectrum ratio algorithm in combination with flue gas absorption characteristics; fusing non-contact and contact temperature measurement data based on weighted Kalman filtering and complementary filtering; constructing a space-time variable covariance function to carry out non-stationary Kriging interpolation; dynamically optimizing the local grid resolution by combining an adaptive grid module; the processing flow is accelerated through the parallel computing module; early warning is triggered based on abnormal probability judgment and is fed back to emissivity correction and grid optimization; according to the invention, the monitoring precision and real-time performance of the temperature field are obviously improved, and the risks of false alarm, missing alarm and equipment melting loss are effectively inhibited.

The invention provides a radiation field high-precision reconstruction method based on dynamic geometry aggregation, and relates to the technical field of radiation field reconstruction and computational physics crossing. The method comprises the following steps: extracting a corresponding attenuation coefficient as a priori value; generating a Gaussian radiation element at the position of the monitoring point; calculating the radiation intensity of any point in the space; suppressing mutation of attenuation coefficients of adjacent primitives; gathering to a high dose zone or dispersing to a low dose zone; and generating three-dimensional radiation dose rate distribution by adopting a differentiable split rendering pipeline, and calculating the radiation intensity of any query point in real time by outputting a parameterized Gaussian primitive set. Through the dynamic Gaussian primitive aggregation-physical constraint optimization dual-drive reconstruction framework, the radiation field distribution can still be accurately restored under the sparse detector condition, the error is greatly reduced compared with the traditional method, and the calculation efficiency is obviously improved.

The invention discloses a 3DGS-based integrated visual angle synthesis and sparse visual angle CT reconstruction method, which comprises the following steps: establishing an internal and external parameter matrix through X-ray scanning parameters, constructing an initial voxel space and an initialized 3DGS radiation field by combining sparse visual angle projection data and based on an ACUI strategy, modeling anisotropic radiation intensity by utilizing a radiation intensity response function, and reconstructing a 3D visual angle CT model. And generating a virtual projection by adopting volume consistency rendering. And the optimized radiation field is converted into a voxel grid, density contribution is applied to carry out voxel space reconstruction, a reconstructed voxel space is obtained, and a new 3DGS radiation field is generated. And re-rendering the virtual visual angle projection based on the new 3DGS radiation field, performing iterative optimization by using a loss function, and outputting a new visual angle synthetic image and a CT reconstruction body until a preset number of iterations is reached. And an efficient process of one-time training and dual output is realized. The efficiency and precision of X-ray imaging are improved, the radiation dose of a patient is reduced, and meanwhile, a higher-quality imaging solution is provided for medical diagnosis.

The invention discloses an intelligent earth surface solar radiation forecasting method based on satellite remote sensing, and belongs to the field of information technology and meteorological technology. The method comprises the following steps: S1, acquiring geostationary satellite observation data, satellite inversion earth surface solar radiation data and terrain factor data, and executing Z-score standardization processing; s2, performing dimensionality reduction on the standardized input sequence and the target data by using a pre-training auto-encoder to obtain latent variables of a historical sequence and a future cloud picture observation sequence; s3, inputting the dimension-reduced historical sequence into a conditional potential space diffusion model, modeling the historical satellite cloud picture sequence, and predicting a probabilistic potential variable of a cloud picture at a future moment; converting the solar radiation prediction result into a corresponding earth surface solar radiation prediction result through an inversion model; and S4, the self-encoder is adopted to perform dimension raising to obtain a final prediction result. According to the method, based on a frequency domain and space domain multi-modal feature adaptive fusion mechanism, while a complex cloud-radiation relation is modeled, predicted structural consistency and physical rationality of radiation intensity are kept.

The invention provides a multi-scale photovoltaic power prediction method and system fusing numerical weather forecast and a physical information neural network, relates to the technical field of photovoltaic power prediction, and realizes rolling prediction of future meteorological parameters and horizontal radiation intensity through numerical weather forecast. The authenticity and the stability of the meteorological data are effectively improved by combining quantile mapping and cascade correction of the time sequence mode attention neural network; and through combined modeling of a physical information neural network and a time sequence characteristic network, meteorological and radiation data subjected to multi-level correction and conversion are deeply fused with a photovoltaic system physical law, and high-precision prediction of photovoltaic power is realized. The whole prediction process has automatic anomaly elimination and deletion complementation capabilities, the prediction robustness under complex meteorological conditions and extreme environments is enhanced, and the sequential response and physical consistency of photovoltaic power are optimized, so that the engineering applicability and intelligent level of the system are greatly improved.

The invention provides an electron irradiation dose on-line measurement and feedback calibration system and method, and relates to the technical field of automation control, and the system comprises a processing module which is used for converting an original dose signal into a five-path digital reading sequence, carrying out the timestamp alignment and space coordinate calibration of the five-path digital reading sequence, and outputting a calibration result; generating a three-dimensional discrete coordinate data set representing radiation field intensity space distribution; and the extraction module is used for identifying a radiation intensity global maximum value point from the three-dimensional discrete coordinate data set as a spatial registration origin, extracting two feature straight lines representing a radiation scattering dominant direction, and calculating a spatial orientation included angle between the two feature straight lines to determine a radiation scattering main influence area. According to the invention, precise processing of an original dose signal, scientific positioning of a radiation influence area and construction of a dynamic compensation model are realized through cooperation of multiple modules, a high-confidence dose value can be output, feedback calibration is completed based on a time sequence drift trend, and the precision and reliability of on-line measurement of the electron radiation dose are effectively guaranteed.

The invention relates to the technical field of infrared thermal imaging, in particular to a gas leakage quantitative calibration method and system based on multispectral feature fusion, and the method comprises the steps: configuring a multiband blackbody radiation source; building a simulated gas cloud cluster environment, obtaining configuration parameters in real time, and performing classified collection on the configuration parameters to construct a four-dimensional parameter space; acquiring infrared thermal imaging data corresponding to the simulated gas cloud cluster environment, and associating the infrared thermal imaging data with the four-dimensional parameter space to form a structured sample set; sharing the structured sample set by using a dual-channel 3D-CNN to extract radiation intensity features and cloud cluster morphological features, and splicing the radiation intensity features and the cloud cluster morphological features to obtain a fusion feature vector; non-linear mapping based on deep learning is carried out on the fusion feature vector to output a concentration prediction value; and introducing an atmospheric transmission correction factor to correct the concentration predicted value so as to obtain a concentration accurate value. The method has the effect of improving the accuracy of gas leakage concentration calibration.

The invention relates to the technical field of carbon detection, in particular to an online real-time dynamic detection method for the carbon content of converter steelmaking molten steel, which comprises the following steps: acquiring multi-source sensing data, and acquiring a molten steel surface temperature image acquired by a thermal infrared imager; acquiring multiband spectral data, namely controlling a visible band sensor to acquire radiation intensity in a range of 500-600nm, and controlling a near-infrared band sensor to acquire reflectivity characteristics in a range of 850-1100nm; analyzing and fusing the data, analyzing the temperature image, and generating a molten pool two-dimensional temperature field; analyzing the multiband spectral data, and extracting a spectral feature vector related to the carbon content; fusing the two-dimensional temperature field and the spectral feature vector, and generating a molten steel surface carbon content distribution diagram based on a pre-trained carbon content machine learning model; and outputting an optimized detection result, processing multi-node data through a distributed computing framework, and outputting a dynamic carbon content detection report. According to the invention, the effects of breaking through the limitation of traditional static detection, real-time component monitoring, full molten pool covering and dynamic feedback are achieved.

The invention discloses a multi-target path planning method and device, equipment and a storage medium, and relates to the technical field of traffic path planning, and the method comprises the steps: obtaining solar radiation data and original map data, carrying out the multi-source data fusion based on the solar radiation data and the original map data, and obtaining the radiation road network data; based on the radiation road network data, a total cost function of the path length is constructed through an accumulated cost function of the path length and a heuristic function of the estimated cost, and candidate paths are generated according to the total cost function; on the basis of the radiation road network data, calculating the path average radiation intensity of the candidate path, and further obtaining the energy recovery amount of the candidate path; constructing a dual-target cost function based on the total cost function and the energy recovery amount, adjusting node priorities and screening and updating a non-dominated solution set according to the dual-target cost function, and generating a target candidate path set according to the non-dominated solution set; and determining an optimal balance path in the target candidate path set through multi-dimensional index quantitative evaluation and balance coefficient sorting.

The present invention relates to a device for measuring a line current. Said device comprises at least three sensor elements having paramagnetic centres, a pump-radiation source, an optical system, and at least three photodetectors which function as part of receiving systems and are each associated with a sensor element. In addition, the device contains two magnetic field sources which generate different bias magnetic fields for each sensor element. The pump-radiation source emits pump radiation into the optical system, which distributes the pump radiation to the sensor elements and thereby irradiates the paramagnetic centres with the pump radiation. These centres emit fluorescence radiation, the intensity and phase shift of which depend on the AC drive signal of the evaluation and control device and on the magnetic flux density acting upon them. The fluorescence radiation is separated from the pump radiation by the optical system and guided onto the photodetectors. The evaluation and control device generates a single-frequency sinusoidal AC drive signal having a frequency of 22 MHz (-4 MHz / +7 MHz), or within a range of 18 MHz to 29 MHz. The lock-in amplifiers are coupled to the sensor elements and evaluate the output signal of the photodetectors with respect to the AC drive signal in order to produce measurement values. Based on these measurement values, the evaluation and control device determines an estimated value for the magnitude of the line current in the line.

The invention discloses a three-dimensional combustion multi-parameter field inversion method based on two-dimensional infrared imaging and hyperspectral light field imaging, and belongs to the technical field of flame combustion detection. The invention aims to solve the problem of low reconstruction precision caused by limited spontaneous radiation information and poor low-temperature region signal sensitivity in the existing combustion flow field temperature field reconstruction. Comprising the following steps: obtaining a flame two-dimensional infrared temperature distribution image and a flame hyperspectral light field image; a two-dimensional blackbody radiation intensity curve and a three-dimensional blackbody radiation intensity curve are obtained through calibration according to the blackbody radiation law; combining the corresponding image gray values to obtain two-dimensional infrared radiation intensity, three-dimensional visible radiation intensity and three-dimensional infrared radiation intensity; determining a temperature threshold value of the high-temperature area; constructing a multispectral radiation source term matrix equation, and reconstructing a three-dimensional temperature field; obtaining a separated flame hyperspectral light field image, and reconstructing a low-temperature region and a reconstructed temperature field; and combining with a high-temperature region reconstruction temperature field to obtain a whole temperature field. The method is used for three-dimensional combustion multi-parameter field inversion.

The invention relates to a non-Lambert surface emissivity inversion method, belongs to the technical field of infrared optical measurement and radiation modeling, solves the technical problems of low precision and poor model stability of non-Lambert surface emissivity inversion, and comprises the following steps: measuring original radiation intensity of a non-Lambert surface of a to-be-tested material in different emergent directions; converting the original radiation intensity into directional reflectivity; on the basis of the generalized Lorentz function, diffuse reflection background items are superposed, and a physical prior model is constructed; physical constraint is carried out on the physical prior model parameters; the parameter residual network generates a parameter field, and the parameter field is input into the optimized physical prior model; and carrying out hemispherical integration, and converting the directional reflectivity into directional-hemispherical emissivity. The device and the method are used for infrared thermal imaging measurement, material radiation characteristic characterization and engineering detection in a complex environment.

The application provides a kind of dual-band infrared temperature measurement method and temperature monitoring method and computing device, the method comprises: determining the wavelength range corresponding to first temperature interval and second temperature interval, the first temperature interval and the second temperature interval include first temperature, second temperature and third temperature, the first temperature and the second temperature determine the first temperature interval, the second temperature and the third temperature determine the second temperature interval;Select fourth temperature in the first temperature interval and the second temperature interval;At the fourth temperature, change wavelength in the wavelength range, obtain the relationship curve of radiation intensity and radiation wavelength;Determine the selected wavelength on the relationship curve;The selected wavelength is used for the temperature measurement of the first temperature interval and the second temperature interval.According to the technical scheme of the application, more accurate dual-band measurement temperature is realized.

The invention provides an air motion weak point target detection method and system based on an infrared sequence image. The method comprises the following steps: obtaining an infrared sequence image with at least one moving target; the infrared sequence image comprises frame radiation intensity diagrams with continuous time, and the frame radiation intensity diagrams are positive integers greater than 1; processing the frame radiation intensity graph to obtain a frame difference mean value graph; calculating to obtain an optimal segmentation threshold value through a maximum between-class variance method by utilizing the difference mean value diagram; taking the optimal segmentation threshold as a threshold, and performing binarization processing on each differential mean image to obtain a frame candidate point binary image; in the candidate point binary image, a pixel point with a pixel value of 1 is a target position candidate point; adding all the candidate point binary images to obtain a candidate point aggregation image with all the target position candidate points; and obtaining a linear motion track of each moving target based on the target position candidate points in the candidate point aggregation graph.

This invention discloses a method and system for detecting wall radiation information through flame penetration. The method determines the radiation wavelength range, and within this range, establishes a wall radiation intensity detection model and a flame radiation intensity detection model, showing the distribution of wall radiation intensity and flame radiation intensity with radiation wavelength. It also obtains the radiation wavelength λ when the wall radiation intensity equals the flame radiation intensity. eq The peak wavelength λ when the wall radiation intensity is at its maximum. max When the radiation wavelength λ eq Less than the peak wavelength λ max At that time, the wavelength for detecting wall radiation information is the peak wavelength λ. max When the radiation wavelength λ eq Greater than the peak wavelength λ max At that time, the wavelength for detecting wall radiation information is the radiation wavelength λ. eq The wall radiation information is detected according to the detection wavelength determined above. The present invention finds a suitable band range for wall radiation detection by accurately quantifying wall radiation and flame radiation, and can obtain wall radiation information by penetrating the flame.

The invention provides a power grid equipment monitoring method and system based on multi-source satellite power grid image data processing, and the method comprises the steps: firstly obtaining heat radiation temperature data and contour data of equipment from an infrared satellite and a visible light satellite, and carrying out the time-space synchronization processing; secondly, extracting temperature gradient distribution information from the heat radiation temperature data, and identifying and sequencing local overheating areas in combination with radiation intensity difference; enhancing equipment contour edge identification according to the sequence to obtain an enhanced contour image; superposing the data with thermal radiation temperature data, and extracting comprehensive distribution characteristics to determine an initial fusion weight; identifying a temperature distribution imbalance region, evaluating the reliability of the two types of data sources, and adjusting the weight in combination with the operation state of the equipment to obtain a final ratio; the two types of data are weighted and fused according to the proportion, and a final temperature distribution image is obtained through temperature field distortion correction; and extracting the geographic position of the overheat area and mapping the geographic position to the equipment layout diagram to complete power grid equipment thermal anomaly monitoring. Through the scheme of the invention, the thermal anomaly of the power grid equipment can be monitored.

The invention relates to the technical field of irrigation prediction, in particular to a soil moisture content-based irrigation water consumption prediction method. According to the method, the water consumption rate is calculated by synchronously obtaining the photosynthetic radiation intensity and the matrix water content in a sliding time window; determining a load index representing moisture extraction resistance based on a mean ratio of radiation to consumption rate, and constructing a fluctuation transmission index reflecting matrix hydraulic connectivity based on a ratio of variation coefficients of the radiation and the consumption rate; combining the two indexes to generate a hydraulic blocking risk coefficient for identifying recessive drought caused by capillary fracture; and finally, predicting the actual water demand according to the risk coefficient and the preset maximum irrigation amount. According to the method, physiological regulation of crops and physical water shortage of the substrate can be effectively distinguished, the judgment accuracy of the microcosmic hydraulic communication state of the substrate is remarkably improved, then irrigation water consumption prediction is more targeted and timeliness, and mistaken irrigation or leakage irrigation is avoided.

The invention relates to the technical field of interference suppression, in particular to an electromagnetic compatibility optimization method and system for a ship shaft frequency converter, and the method comprises the steps: carrying out the term-by-term judgment of sensitive interference energy, current errors and switching loss after the discretization and jump limitation based on a frequency sequence, and screening out a boundary-crossing sequence, the genetic algorithm executes cross combination and amplitude superposition in the residual sequence, a new frequency set is formed through transformation and rearrangement, frequency points are distributed in a plurality of intervals to be reorganized, the switch state is predicted and updated one by one through Kalman filtering, observation residual errors are corrected in real time, and the frequency points are reorganized. The harmonic distortion rate, the radiation intensity and the instruction change amplitude are synchronously output by taking the time index as a sequence, the deviation is compensated at the amplitude and phase level, the harmonic index and the radiation index are controlled in an agreed range, the switching loss and the instruction change are within threshold values, and a complete closed loop covering frequency generation, harmonic correction and sequence updating is formed.

The invention discloses a temperature measurement method and system for correcting organism emissivity difference through AI modeling, and relates to the technical field of organism emissivity difference temperature measurement, and the method comprises the steps: collecting the multiband infrared radiation intensity data of the surface of an organism through a multispectral imaging device; the multi-band infrared radiation intensity data are input into a space-time convolutional neural network, a wavelength-time dependent dynamic emissivity function is output, the space-time convolutional neural network comprises a physical constraint layer, and the physical constraint layer takes the Planck radiation law as priori knowledge to be embedded into a network structure; a differentiable physical engine is adopted to optimize the dynamic emissivity function, neural network parameters are adjusted by minimizing a loss function containing a physical constraint term, and the physical constraint term represents the gradient difference between the actually measured radiation intensity and the theoretical radiation intensity; and generating pathological tissue emissivity disturbance data by using a generative adversarial network, and adding the disturbance data into a training data set to enhance the generalization ability of the model.

The application belongs to the technical field of zinc powder purification, and provides a condensation and sedimentation system for zinc powder purification, which comprises the following steps: collecting a time sequence of original radiation intensity of a condensation chamber, performing frequency spectrum analysis through fast Fourier transform, calculating energy values of high and low frequency band frequency domain signals, solving a signal coherence factor and calculating a transmittance attenuation coefficient, constructing a metal thin film radiation compensation model based on a long short-term memory network, inputting the attenuation coefficient and the time sequence of original radiation intensity to output a corrected real temperature of the condensation chamber, expanding an inference layer of a full connection neural network structure, outputting a calibrated attenuation coefficient through the inference layer, selecting an effective attenuation coefficient input model by comparing a deviation threshold value, dynamically responding to temperature measurement nonlinear attenuation caused by zinc film deposition, guaranteeing production continuity and product quality of zinc powder purification, adapting to industrial multi-working condition operation requirements, being convenient to operate and controllable in cost.

This utility model discloses a radiation detection device. The device includes: a signal control module connected to the object under test, used to output a current to the object under test after a set delay, causing the object to emit a radiation signal; a detection module connected to the signal control module, used to detect the radiation signal emitted by the object under test in at least one set wavelength band, and input the detection data into the signal control module; and an industrial control module connected to the signal control module, used to receive the detection data after a set delay and convert it into radiation intensity information. This utility model embodiment improves the accuracy of radiation detection.

The invention discloses a plasma welding auxiliary device for water pump shell production, and relates to the technical field of welding auxiliary equipment. The air pressure difference data, the weight data and the tension data are simultaneously collected through the analysis module, and the actual mass of the filtered matter on the surface of the filter screen is accurately calculated in combination with the weight change of the residue collection box after shutdown, so that compared with a traditional judgment mode which only depends on the air pressure difference, the interference factor of'abnormal air pressure difference caused by airflow fluctuation 'can be eliminated, and the judgment accuracy is improved; the air pressure difference change caused by unit filtering capacity is calculated, the threshold value is not a fixed value and is dynamically adjusted according to historical filtering data, and misjudgment caused by working condition change is avoided; and the analysis module incorporates four parameters of light radiation intensity, gas flow rate, temperature and humidity into a sterilization rate formula, when abnormity occurs in the welding process, the abnormity of the sterilization rate can be found in time, the required light radiation intensity is calculated and adjusted, and the sterilization rate is guaranteed.

The application provides an infrared image super-resolution method based on physical guidance visual autoregression. A physical encoder is constructed to extract a temperature field, a radiation intensity field, a thermal gradient field and a thermal diffusion field from a low-resolution image to form a multi-branch physical prior representation; a physical guidance scale-by-scale autoregression generator is designed to embed the physical prior as a condition into an image encoder, to modulate the rotation position coding constraint space relationship through the temperature gradient, and to introduce a physical condition cross-attention mechanism to promote the feature interaction of the thermal similar areas; and a physical consistency verification layer is established to implement a temperature range hard constraint, a radiation energy conservation soft constraint and a thermal diffusion smooth structure constraint. The method effectively solves the problem of physical inconsistency caused by the visual autoregression model ignoring the infrared physical characteristics, significantly improves the temperature accuracy, energy conservation and physical consistency of the reconstructed image, and is suitable for infrared accurate temperature measurement, thermal radiation quantitative analysis and thermal target detection and identification scenes.

Optoelectronic measuring device (1) for frequency-resolved measurement of the intensity of electromagnetic radiation (10), comprising multiple measurement channels (M1, M2, ..., M m ), wherein a first of the measurement channels (M1) has a first spectral sensitivity and another of the measurement channels (M2, ..., M m ) exhibits another spectral sensitivity that differs from the first spectral sensitivity, and several collimators (K1, K2, ..., K k ) to collimate the electromagnetic radiation (10), wherein - through each of the collimators (K1, K2, ..., K k ) a separate optical path to one or more of the measurement channels (M1, M2, ..., M m ) runs and each of the measurement channels (M1, M2, ..., M m ) is arranged, an intensity of the collimators (K1, K2, ..., K) is arranged, an intensity of the collimators (K1, K2, ..., K k ) collimated electromagnetic radiation (10) to measure, - the optoelectronic measuring device (1) more collimators (K1, K2, ..., K k ) as measuring channels (M1, M2, ..., M m ) includes, and - the optoelectronic measuring device (1) comprises a radiation distribution means (3) which is set up and arranged to direct the electromagnetic radiation (10) onto the collimators (K1, K2, ..., K k ) to distribute, wherein the radiation distribution means (3) comprises a scattering element and / or an optical fiber.

The invention relates to the technical field of solar simulation adjustment, and discloses an intelligent controllable method and system for simulating dynamic change of solar radiation. Long-term irradiation data are obtained from a database and a local weather station and fused, the discontinuity of the daily boundary is overcome by applying a circumferential mapping and clustering method, and the maximum daily radiation intensity, the typical sunrise moment and the sunset moment of each month are obtained; on the basis, constructing an attenuation model taking a monthly typical value as a benchmark, introducing random disturbance and physical constraints conforming to meteorological statistical characteristics, generating intra-month daily simulation parameters, further utilizing a trigonometric function improvement model to dynamically represent the daily simulation parameters of the current month as target irradiation intensities at all moments, standardizing the target irradiation intensities and mapping the target irradiation intensities into command control quantities, and calculating the target irradiation intensities. Precise reproduction of the natural solar radiation curve by the illumination intensity is realized; then actual light intensity is detected through an irradiation sensor, execution errors are calculated, control action quantity is generated in real time through a PID control law, and finally execution quality is evaluated through a control action quantity sequence.

A method of determining beta radiation intensity based on calculated resonance frequency and calculated quality factor can include providing an electrical sensor comprising at least one prong, irradiating the first composite material of the one of the plurality of planar surfaces and the material of the second section with beta radiation from a beta radiation source; measuring at least one impedance value from the electrical sensor with an impedance analyzer; calculating at least one resonance frequency value based on the measured at least one impedance value; calculating at least one quality factor value based on the calculated at least one resonance frequency value; and determining the beta radiation intensity based on the calculated at least one resonance frequency value and the calculated at least one quality factor value.

This invention relates to the field of image sensing data processing and discloses a method for diagnosing the thermal environment of blue-green spaces in cold-region cities based on multispectral remote sensing. The method includes the following steps: acquiring multispectral remote sensing images, three-dimensional building elevations, and solar apparent shape parameters; calculating the illumination shading coefficient of blue-green space pixels to form a three-dimensional dynamic shadow mask; constructing a microscopic phase transition evolution operator using the sensitivity gradient of radiation intensity in different polarization directions and mid-infrared reflectivity; inputting the mask and operator into the thermal infrared radiation measurement equation to reconstruct the dynamic surface temperature; solving the surface energy balance equation based on the dynamic surface temperature, separating the latent heat storage of phase transition energy, and constructing a latent heat buffer index; and performing a comprehensive diagnosis of the thermal environment health based on this index. This invention effectively overcomes the temperature measurement errors caused by complex shading and phase state interweaving, accurately isolates the latent heat energy of phase transition, and achieves precise positioning and objective quantitative diagnosis of microclimate anomalies in cold-region cities.

The invention discloses a radiation refrigeration material multi-factor coupling aging test device and method, and the device comprises an aging treatment device which comprises a rotatable platform, an environment simulation cabin, a temperature control wind system, a UV irradiation system, a multi-mode raining system, an automatic condensation system, and a central control unit. The rotatable platform is used for placing a radiation refrigeration material and realizing three-dimensional rotation; the temperature control wind system comprises a temperature adjusting unit and a wind speed adjustable fan which are arranged on the environment simulation cabin; the UV irradiation system comprises an ultraviolet light source array arranged at the top of the environment simulation cabin, and a light intensity controller and a radiation intensity probe which are arranged in the environment simulation cabin; the multi-mode raining system is used for simulating a humid environment and raindrop impact; the automatic condensation system is used for simulating a condensation phenomenon in a high-humidity environment; the central control unit is used for setting and regulating operation parameters of the whole testing device. The device simulates the influence of various factors on the performance of the radiation refrigeration material in a real natural environment, and has high universality and flexibility.

The present application relates to a hyperspectral remote sensing image radiation normalization method, in particular to a hyperspectral remote sensing image relative radiation normalization method based on pseudo-invariant region pairs, which solves the technical problems of low spatial matching accuracy and spectral feature deviation of the existing relative radiation normalization method based on pixels. The present application adopts superpixel segmentation, morphological processing and superpixel guided method to screen pseudo-invariant regions, then adopts a self-correction model based on spatial-spectral constraints to adaptively learn the relative radiation normalization of the high light remote sensing spectral image to be corrected, adopts a quantitative method, which can not only fully utilize the spatial-spectral features of the hyperspectral remote sensing image, but also adaptively correct the radiation intensity of the hyperspectral remote sensing image in different time phases, improve the consistency and quantitative inversion accuracy between time sequences, thereby improve the accuracy and consistency of the relative radiation normalization, and is suitable for the radiation normalization of high spatial resolution, complex ground object scene hyperspectral remote sensing images.

This invention discloses a method for extracting orthogonal radiative eigenmodes in lossy structures. For electromagnetic structures containing lossy materials, resistive loading, and other dissipation mechanisms, this invention obtains the scattering T-matrix of the structure under a preset incident mode basis. Utilizing the property that the T-matrix is ​​a complex symmetric matrix under reciprocity conditions, the Autonne-Takagi decomposition method is used to decompose this complex symmetric matrix, yielding a set of mutually orthogonal radiative eigenmodes in the sense of radiated power and their corresponding radiated intensity parameters. The obtained radiative eigenmodes can be used for mode decomposition and physical interpretation of the radiation and scattering characteristics of lossy structures, and are applicable to the design and optimization of various practical lossy electromagnetic structures such as resistive-loaded antennas, scatterers containing dielectric losses, and absorbing material structures.