554 results about "Infrared image" patented technology

The invention discloses a sleeve fault diagnosis method and system. The method comprises the following steps: preprocessing an acquired sleeve infrared image to filter out a non-heating part; segmenting the image of which the non-heating part is filtered out to obtain a single sleeve image; diagnosing the sleeve fault according to the segmented single sleeve image. According to the invention, theinfrared image of the transformer sleeve is preprocessed and segmented, therefore, an infrared image of a single sleeve is obtained; the temperature of each part of the sleeve can be conveniently obtained by converting the gray scale of each pixel in the gray scale map of the infrared image of the single sleeve into the corresponding temperature value, the method is simple but very ingenious, thefaulted sleeve and the faulted area can be quickly positioned, the specific fault type can be judged, and convenience and quickness are achieved.

This invention discloses a method for generating building energy-saving optimization strategies based on UAV infrared imaging, specifically relating to the field of building energy-saving management technology. The method includes acquiring infrared images, timestamps, location coordinates, and air conditioning records collected by a UAV during target building inspections; stitching the infrared images together according to the location coordinates; extracting the room activation status and set temperature from the air conditioning records according to the timestamps; and outputting a temperature map and operation table. By collaboratively organizing the infrared inspection results, room air conditioning operation information, and control area constraints at the edge into an action list, room execution sequence, and area execution sequence, energy-saving recommendations can be transformed from static recommendations into strategy results with constraint resolution, prioritization, and batch execution capabilities, relatively improving the problems of recommendation conflicts and implementation difficulties.

The application discloses a kind of light weight small target detection method and system based on bimodal channel reconstruction and adaptive fusion, the method includes: in RGB feature branch and IR branch respectively constructs a new light weight convolution module, and then obtains double branch light weight convolution module;Respectively extract visible light image and infrared image, input the obtained RGB and IR feature map to multimodal channel reconstruction and adaptive fusion module, generate bimodal fusion features for target detection;Introduce SD loss to construct total loss function to train light weight small target detection model, obtain final detection result for image test;The application can accurately extract small target features under different scales while maintaining light weight, highlight key target features in multimodal, suppress redundant information within modal, enhance the detection accuracy and efficiency of model to multimodal target in complex scene.

The invention relates to a device and method for detecting the liquid level height of melt in a copper pyrometallurgy slag ladle, and belongs to the technical field of metallurgy, the device comprises a plurality of infrared cameras in one-to-one correspondence with tank bodies, and further comprises an infrared control box and an upper computer, and the upper computer is externally connected with a dust removal system; the infrared cameras are arranged above the tank bodies and used for collecting infrared images of the tank bodies, all the infrared cameras are electrically connected with the infrared control box, the infrared control box is electrically connected with the upper computer, and the upper computer is electrically connected with a plurality of sound-light alarm devices which are in one-to-one correspondence with the tank bodies and used for alarming the liquid level heights in the tank bodies. The front end of the tank body is provided with an anti-shielding detection device used for detecting whether a transport vehicle passes by or not, and when the anti-shielding detection device detects that the transport vehicle passes by, the upper computer controls the dust removal system to be started. According to the invention, cinder ladle discharge monitoring can be realized, the safety risk of equipment and personnel is reduced, and the cinder ladle alternation efficiency is improved.

This invention provides a method and system for generating visible light to infrared images based on a prototype-guided diffusion model, relating to the field of computer vision technology. The method includes: collecting visible light images to be converted; loading a pre-constructed set of infrared prototype features and pre-trained model parameters; and inputting the image and feature set into a prototype-guided diffusion model network. This network generates the corresponding infrared image through the collaborative work of its internal prototype feature construction, local prototype attention, and noise prediction modules. This invention effectively solves the problems of poor physical consistency and detail distortion in generated images caused by insufficient modeling of infrared thermal features in existing methods by extracting thermal radiation prototypes from real infrared data and introducing them as strong semantic priors into the diffusion generation process. This significantly improves the thermal structure realism and detail fidelity of the synthesized infrared image.

The application relates to the field of artificial intelligence, and provides a kind of unsupervised infrared image to visible light image conversion method, device and equipment. The method comprises: obtaining an infrared image to be converted;Obtain a visible light image;The infrared image is input into an image generation model to obtain a visible light image output by the image generation model;Wherein, the image generation model is generated based on an infrared sample image, a visible light sample image, a first image discrimination model and a second image discrimination model, the image generation model is trained using a preset loss function, and the preset loss function is calculated based on a gradient loss function of the visible sample image, a total pixel loss function, a standard generative adversarial network loss function and a cycle consistency loss function. The embodiment of the application improves the accuracy of converting infrared images into visible light images.

This application relates to the technical field of grain processing quality inspection, and in particular to a grain quality infrared image recognition equipment, which includes a housing with a turntable rotatably mounted inside the housing. A drive source is provided between the turntable and the housing, and multiple storage cylinders are arranged on the turntable. This utility model, through the annular layout design of the turntable carrying multiple storage cylinders, combined with the rotation control of the drive source, can realize multi-channel parallel detection of grain samples. When one storage cylinder is under the infrared detector for detection, other storage cylinders can simultaneously complete operations such as feeding, unloading, or vibrating and spreading, avoiding the "intermittent detection" drawback of traditional single-channel equipment. At the same time, the two discharge pipes, combined with the eccentric setting of the electric telescopic rod, can automatically switch the opening and closing state of the baffle according to the detection results, realizing dynamic sorting of qualified and unqualified grains without manual intervention, significantly improving the detection and sorting efficiency in large-scale grain processing scenarios.

The application provides a degenerated infrared image restoration method and system, which comprises the following steps: applying an image degradation factor corresponding to an image degradation mechanism and adapted to each infrared image in an infrared image sample to construct different types of degraded images based on different image degradation mechanisms; training a super-resolution processing model based on at least one type of degraded image to obtain a degenerated infrared image restoration model; inputting a current infrared image with the image degradation factor into the degenerated infrared image restoration model to perform image restoration processing on the current infrared image by the degenerated infrared image restoration model. The application corresponds to obtain different types of degraded images by multiple modeling methods, and further trains the super-resolution processing model by the combination of different types of degraded images to restore the infrared image acquired under diversified meteorological environments with high quality.

This invention discloses a method for detecting overheating of transmission line conductors and ground wires based on infrared image spatial positioning. It comprises an infrared image acquisition module, a conductor and related component extraction module, a conductor and ground wire judgment module, and a conductor and ground wire overheating detection module. The conductor and related component extraction module includes a conductor extraction module, a U-shaped hanging ring extraction module, and a tower head extraction module. This achieves fully automated detection throughout the entire process, from automatic access to UAV infrared images, to precise segmentation of key components, to intelligent identification of conductors and ground wires based on spatial topology, and finally to comprehensive judgment of multi-component related overheating. The beneficial effects of this invention are: it can integrate infrared temperature information and image spatial structure information to accurately distinguish between conductors and ground wires and drain wires; it can perform integrated positioning and correlation analysis of abnormal overheating of conductors and ground wires with their associated tower damage fittings, achieving a more accurate and reliable diagnosis of conductor and ground wire overheating defects and their root causes.

The application provides a forest and grassland fire early identification and positioning method based on infrared thermal imaging and visible light fusion, and belongs to the technical field of forest and grassland resource protection and ecological safety monitoring. The method comprises the following steps: synchronously collecting infrared and visible light images and recording the space-time information of a monitoring platform; performing pixel-level registration on the two images; extracting a thermal anomaly suspected area from the infrared image based on a dynamic background temperature field, and extracting a smoke suspected area from the visible light image based on color, texture and motion features; performing spatial correlation analysis on the suspected areas extracted from the two channels, and combining the area growth rate and temperature rise rate of continuous multiple frames to construct a fire evolution model to confirm a fire point; calculating the three-dimensional geographic coordinates of the fire point based on the photogrammetry collinear equation and a digital elevation model; and generating and outputting alarm information containing the three-dimensional coordinates and fire intensity. The application realizes early and accurate identification and positioning of forest and grassland fires, and significantly reduces the false alarm rate.

The application discloses a fan blade damage identification method based on structural vibration modal feature transmission and image recognition. The method constructs a three-layer deep learning architecture composed of an upper structure dynamic network, a lower visual network and a joint fusion network, realizing deep fusion of multi-modal information. Among them, the upper structure dynamic network implicitly extracts the structural dynamics characteristics of the blade through the acceleration sensor signal to perceive the internal state anomaly; the lower visual network identifies the surface damage of the blade by fusing the visible light and infrared image features collected by the unmanned aerial vehicle; the joint fusion network realizes deep fusion and collaborative decision of the above-mentioned structural features and visual features through cross-modal attention and Bayesian inference. The application significantly improves the accuracy, robustness and environmental adaptability of damage identification by fusing the internal dynamic response of the blade and the external visual information, and provides an efficient solution for realizing intelligent state monitoring and operation and maintenance of the fan blade.

The application provides a processing method and system for recognizing and positioning a plurality of illumination fusion pads, wherein the method comprises the following steps: step 1, providing an infrared radiation source at the bottom of a pad product; step 2, acquiring an infrared image and a visible light image of the pad product respectively; step 3, performing image fusion processing on the infrared image and the visible light image to obtain a fusion image; and step 4, recognizing and positioning the area of the pad of the pad product in the fusion image based on a template matching technology. The processing method and system for recognizing and positioning a plurality of illumination fusion pads can replace manual recognition of the welding position on the pad, realize fully automated welding, and greatly reduce the labor cost.

This invention relates to the field of medicinal material identification technology, specifically to a method and system for identifying the authenticity of medicinal materials based on AI vision. The method includes the following steps: iteratively generating candidate images and comparing them with images of genuine medicinal material slices, adjusting the generation logic based on the comparison results. This invention constructs a latent vector mapping relationship consistent with the visual features of images of genuine medicinal material slices, combines image reconstruction errors for anomaly extraction, and enhances the perception of adulteration locations. The pixel-by-pixel reconstruction error method can locate areas with slight deviations in shape or color, and based on this, extracts the thermal decay curve of the isotopic infrared image sequence. Through time constant fitting calculation, it completes a quantitative modeling of the thermal conductivity characteristics in space, and further calculates the spatial gradient of the thermal decay time constant, realizing the quantification of the boundary strength of the material's thermal diffusion behavior, forming a thermal anomaly diffusion gradient map, providing physical property basis for subsequent multi-spectral fusion.

A detection method and system for a leaked gas based on multi-data fusion, and an electronic device, relating to the technical field of gas detection. The method comprises: acquiring a plurality of compressed images obtained by respectively compressing a plurality of first infrared images; on the basis of the plurality of compressed images, predicting a position of a potential leaked gas as a candidate position; extracting, respectively from a plurality of second infrared images, sub-images at the candidate position as infrared sub-images; and on the basis of all of the infrared sub-images, predicting a first classification result for the candidate position, wherein the first classification result is used for indicating the existence of a leaked gas at the candidate position or the absence of a leaked gas at the candidate position. By means of embodiments of the present application, rapid and accurate detection of a leaked gas can be achieved.

This invention relates to image registration methods, specifically to an infrared and visible light image registration method. It addresses the problem that existing infrared and visible light image registration methods cannot simultaneously achieve both efficiency and accuracy. This invention first acquires multiple sets of visible light images and corresponding infrared images of a target at different distances, and processes them using the SIFT operator and RANSAC algorithm. A table is then created to record the transformation matrix from the infrared image to the visible light image at different distances. Subsequently, the visible light image to be registered and the corresponding infrared image are input into a trained convolutional neural network for processing. The output is the shooting distance values ​​of the visible light and infrared images to be registered. The corresponding transformation matrix is ​​obtained by looking up the table, and the infrared and visible light images are registered using this transformation matrix. The RANSAC algorithm is used to remove mismatched feature points, and combined with the distance prediction accuracy of the convolutional neural network, the accuracy of the transformation matrix is ​​doubled. Because of the pre-established table, feature point matching and matrix calculation are not repeatedly performed on each frame of the image, significantly improving the registration speed.

The application relates to the field of infrared thermal imaging technology, and particularly provides an infrared thermal imaging AI intelligent temperature measurement method.The method comprises the following steps: image input and preprocessing, receiving infrared images and sunlight images photographed by an infrared thermal imager, classifying based on pixel value differences, and preprocessing to obtain binary images; image cutting, cutting the binary images, and identifying the boundaries of numbers and symbols; characteristic value calculation and extraction, dividing regions according to the boundaries of the numbers and symbols, and performing feature extraction to construct a characteristic vector; number classification and identification, comparing the characteristic vector with a pre-trained K-nearest neighbor algorithm (KNN) model to identify the numbers and symbols; and image number output, combining the identified numbers and symbols into complete temperature values, outputting the identification result, and storing the identification result for comparison diagnosis.The method automatically and accurately identifies temperature information in the infrared images, and realizes intelligent comparison diagnosis.

The invention relates to the technical field of sugarcane spica monitoring, and discloses a sugarcane spica flowering intelligent monitoring system, which is characterized in that a hyperspectral image and an infrared image are acquired, the hyperspectral image and the infrared image are acquired and registered into a multi-source image data set, and a spica area binary mask image is segmented; extracting morphological structure characteristics, spectral reflection characteristics and thermal radiation characteristics, calculating a visibility index KJ, a wave band reflectivity BS and a radiation temperature value FP based on the extracted characteristics, calculating a determination value P, and comparing the determination value P with a hybridization threshold ZY; according to the method, the hyperspectral image and the infrared image of the sugarcane spica are collected, the hyperspectral image obtains the fine spectral reflection characteristics of the sugarcane spica so as to analyze the physiological state of the sugarcane spica, and the infrared image is used for assisting in obtaining the overall shape, contour and thermal radiation information of the spica, and especially, the image characteristics are enhanced in a weak light environment; therefore, the sugarcane spica area can be accurately identified, and the effective distinguishing between the spica and the background can be realized.

The present disclosure relates to a computer implemented method for detecting artifacts in infrared (IR) illuminated IR images. Artifacts are separated from real objects by analyzing results of regression line fits to histograms of pixel values. Artifacts will have smooth transition gradients and therefore will show smaller deviations of the regression line fit to the histogram data.

The application discloses a kind of based on track keeping's unmanned aerial vehicle thermal infrared image splicing method and system, it is related to image splicing technical field, including steps: constructing image set;Obtain the matching feature point of any pair of to-be-spliced unmanned aerial vehicle's thermal infrared image respectively, and the re-projection error of matching feature point is generated alignment item by the similar transformation matrix of to-be-spliced thermal infrared image;The actual distance between the center of reference image and the thermal infrared image of any unmanned aerial vehicle is calculated, and the track trajectory protection item is obtained between the center point of similar transformation matrix and reference image by pixel distance;Alignment item and track trajectory protection item are weighted and summed to construct global optimization objective function, and global optimization objective function is converted into linear least square model with similar transformation constraint to solve, and generate spliced thermal infrared panoramic image.The application minimizes the cumulative error of splicing process, while ensuring the integrity of global structure.

This invention discloses a near-infrared image dehazing method based on bright area clustering optimization. The method is characterized by first acquiring a hazy near-infrared image, then constructing an image dehazing model and building a Gaussian pyramid for the hazy near-infrared image. Candidate bright area binary masks are extracted and refined at each scale, and after mapping and fusion, a baseline candidate bright area binary mask and scale persistence features are obtained. Next, feature extraction and cluster analysis are performed on the baseline candidate bright area binary mask, and a physical consistency cost function is constructed based on an atmospheric scattering model for verification, obtaining a global atmospheric light estimate. Then, the global atmospheric light estimate is used for normalization and adaptive dark channel extraction and fusion to obtain an initial transmittance distribution, which is then refined and constrained to obtain an optimized transmittance distribution. Finally, the dehazed image is reconstructed based on the atmospheric scattering model. The advantages are improved transmittance estimation accuracy and edge preservation capability, achieving high-quality restoration of hazy near-infrared images.

The application relates to the technical field of power equipment inspection, in particular to a power equipment inspection method and system based on visual identification; the method comprises the following steps: collecting visible light images, infrared images, ultraviolet images and environment working condition identifiers, and generating a multi-environment three-mode inspection data set; mapping the visible light images, the infrared images and the ultraviolet images to an insulator cross-mode surface coordinate grid to obtain a three-mode coordinate observation point set, and generating a mode environment applicability structure; constructing a three-mode time sequence fingerprint, analyzing the time sequence change relationship of the three-mode time sequence fingerprint based on the environment working condition identifiers, and identifying a high-humidity sensitive grid set; performing state integration processing on the three-mode time sequence fingerprint of the spatial position in the insulator cross-mode surface coordinate grid, generating pollution flashover hidden danger judgment information of a target insulator, and outputting a power equipment inspection result containing the pollution flashover hidden danger judgment information. The application realizes the positionable inspection judgment of insulator pollution flashover hidden dangers in a high-humidity pollution environment.

The application provides a power plant area inspection method and inspection system based on multi-modal perception fusion, comprising: acquiring infrared images, electric signals, vibrations and environmental parameters by using multi-modal perception equipment, performing space-time labeling and signal denoising preprocessing; mining cross-modal joint features through a deep learning encoder, modeling multi-modal causal relationships by using mutual information and time sequence gradient sensitivity, dynamically generating an optimizable causal attention weight matrix to drive the generation of abnormal classification and root cause contribution integral graph; combining with a device mechanism model library to realize semantic matching of abnormal root causes and output of a structured diagnosis report, and supporting continuous adaptive optimization of the model based on actual feedback, which improves the accuracy and explainability of power plant equipment abnormality recognition, and realizes efficient intelligent diagnosis for complex coupled scenes.

The application discloses an infrared image adaptive atmospheric correction method and device based on a radiation transmission model, and belongs to the technical field of remote sensing image radiation correction. The method first extracts the spatial range, imaging time and observation geometry parameters of an image scene, constructs a scene-based atmospheric profile grid by distance inverse ratio weighted interpolation based on a reanalysis atmospheric profile, and combines a digital elevation model and a view zenith angle to correct and apply terrain and observation geometry constraints to generate control node input parameters. Then, the atmospheric radiation transmission model is called in batches to obtain the hyperspectral results of each control node, and the transmittance and path radiance parameters of the infrared target band are extracted by spectral response function convolution. Finally, the control node parameters are reprojected to the original image coordinates, the four-neighbor-domain bilinear interpolation and nine-neighbor-domain weighted interpolation results are adaptively fused for each pixel, the full-resolution atmospheric parameter field is recovered, and the observed radiance at the ground is inversed.

A method and device for detecting obstacles on a power grid inspection route, an electronic device and a computer readable storage medium are provided. The method comprises: in response to a trigger detection condition, obtaining a to-be-detected visible light image and a to-be-detected infrared image of the power grid inspection route; fusing the to-be-detected visible light image and the to-be-detected infrared image based on a collection angle, respectively; performing feature recognition on the fused to-be-detected visible light image and the fused to-be-detected infrared image, respectively; and performing obstacle detection based on first to-be-detected contour features and second to-be-detected contour features obtained through the feature recognition, to obtain an obstacle detection result. The method and device provided in the embodiments improve the accuracy and efficiency of power grid inspection.

This application belongs to the field of power plant technology and discloses a method, apparatus, equipment, and storage medium for module fault detection. This application collects inspection images of each photovoltaic string according to the flight path corresponding to the photovoltaic power plant. The inspection images include initial infrared images and initial visible light images. Then, module fault detection is performed on the initial infrared images and initial visible light images respectively to obtain infrared fault detection results and visible light fault detection results. Finally, the target fault type is determined based on the infrared fault detection results and visible light fault detection results. This application first collects clear and complete inspection images of each photovoltaic string according to the flight path corresponding to the photovoltaic power plant, then performs module fault detection on the initial infrared images and initial visible light images respectively, and then determines the target fault type based on the infrared fault detection results and visible light fault detection results. It can automatically detect photovoltaic module faults based on the initial infrared images and initial visible light images.

1. The name of the design product: infrared gun sight thermal imager. 2. The use of the design product: the design product is used for obtaining infrared images of objects. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.