282 results about "Infrared thermal imaging" patented technology

This invention relates to the field of heat-sealing performance quality inspection technology for flexible packaging, and discloses an online detection system and method for the heat-sealing performance of large-scale flexible packaging. Specifically, it combines infrared thermal imaging detection technology, millimeter-wave imaging detection technology, and AI visual inspection technology. After the heat-sealing process, infrared thermal imaging detection technology is used to detect the temperature distribution during heat sealing, achieving visual quality inspection of the heat-sealing process. Then, millimeter-wave imaging detection technology is used to detect the physical structure inside the seal after heat sealing, achieving visual quality inspection of the heat-sealed product. This invention, through the sequential detection order of "infrared thermal imaging first, then millimeter-wave imaging," ensures that a product is only deemed qualified if it simultaneously passes two detection checkpoints based on different physical principles, and the results of both checkpoints are verified by the host computer. This greatly improves the overall reliability of the detection system.

The utility model relates to a kind of lens and infrared thermal imager, including lens main body, optical lens and laser ranging module, the lens main body has first accommodating cavity, the optical lens is arranged in first accommodating cavity, at least one edge of the optical lens is provided with linear cutout, the linear cutout of the optical lens and the inner wall of the first accommodating cavity are enclosed into accommodating groove, the laser ranging module is partially or wholly arranged in accommodating groove.The utility model not only can reduce the loss of optical lens in energy under the function of ensuring integrated laser ranging module, and increase the reliability of optical lens.

The application discloses an infrared thermal imaging power line circuit breaker fault diagnosis method and system based on YOLOv13, innovatively improves the original YOLOv13 model through module replacement, structure addition and characteristic adaptation, carries out light feature extraction through an infrared multi-scale temperature perception residual module, and outputs an enhanced infrared feature map; the infrared gradient guide deep convolution module is used for amplifying fault edge features, and an edge clear feature map is output; the infrared cross-scale temperature fusion module is used for processing the aligned features to generate a feature correlation graph; the MobileViT module is combined with the above-mentioned infrared special module in depth, a light-weight feature modeling system suitable for infrared fault diagnosis is constructed, a head detection output network is combined with an infrared adaptive multi-task loss function, and the accuracy of fault category and position prediction is ensured. Through the above technical improvement, the application provides a new scheme which is accurate, efficient, light-weight and highly adaptive for infrared thermal imaging power line circuit breaker fault diagnosis.

This application relates to the field of medical image processing technology, and discloses a multimodal image recognition method and system for dynamic assessment of diabetic wound healing. The method includes acquiring infrared thermal imaging images, hyperspectral images, and visible light color images of a diabetic wound collected at the same time of visit; identifying the wound boundary between the diabetic wound and surrounding tissues in the visible light color image, and determining the central reference point of the visible light color image based on the wound boundary; establishing a virtual polar coordinate system based on the central reference point and preset anatomical reference markers; extracting tissue feature information characterizing the pathological state of the wound from the infrared thermal imaging image, hyperspectral image, and visible light color image, and mapping the spatial position of the tissue feature information in its corresponding image to the virtual polar coordinate system; normalizing the mapped tissue feature information, and calculating wound healing assessment indicators based on the normalized tissue feature information in the virtual polar coordinate system.

This invention relates to the field of electrical equipment testing technology and discloses a rapid fault location device for electrical equipment based on infrared thermal imaging. It solves the problem of the inconvenience of adjusting the angle of the infrared lens to improve detection effectiveness. The device includes a housing, with a handle fixedly connected to the bottom of the housing. The handle and housing are integrally formed, and a rubber sleeve is fixedly fitted to the outer side of the handle. The housing is equipped with an adjustment mechanism and a protective mechanism. The adjustment mechanism includes a side plate located above the housing, with a rotating shaft fixedly connected to the bottom of the side plate. A receiving frame is fixedly connected to the bottom of the handle, and an inner plate is fixedly installed on the inner side of the receiving frame. The bottom end of the rotating shaft passes through the housing and is rotatably connected to the inner plate. A U-shaped plate is fixedly connected to the top of the side plate, and an inner shaft is rotatably connected to the inner side of the U-shaped plate. This invention facilitates the circumferential rotation of the support frame and the infrared lens, thereby facilitating the adjustment of the infrared lens angle to improve detection effectiveness.

This invention discloses a data acquisition and analysis method and system for detecting apparent defects in tunnel structures. The method includes: simultaneously scanning the tunnel lining surface using visible light, infrared thermal imaging, and three-dimensional point cloud to obtain a spatiotemporally aligned multimodal raw dataset; performing point cloud registration and multi-source data fusion processing on the multimodal raw dataset to construct a three-dimensional model of the lining surface with temperature attributes; based on the three-dimensional model, using a dual-channel convolutional neural network to extract visible light crack features and infrared leakage features, respectively, and outputting candidate defect maps; performing spatial topological structure analysis on the candidate defect maps to generate a set of quantitative indicators; inputting the set of quantitative indicators into a spatiotemporally evolving hidden Markov model to determine the immediate risk level and evolution trend report of each defect area, and associating it with the spatial coordinates of the three-dimensional model. Using this invention, defect risks can be dynamically assessed and development trends predicted, improving detection efficiency and accuracy.

The utility model belongs to the field of fire fighting equipment discloses a kind of disparity-free infrared thermal imaging fire helmet of application AR screen display, including fire helmet main body and the protective shell connected in the front of helmet by damping pivot.The protective shell is integrated with infrared camera, visible light camera and binocular AR display screen located in the same horizontal line, and completely eliminates parallax.It also includes data processing module and battery module fixed on helmet, and data processing module has double light fusion, wireless transmission and beidou positioning function.The shell of key component adopts double-layer vacuum heat insulation design, and can resist 260 DEG C high temperature.The utility model liberates firefighter's both hands, realizes disparity-free, high-definition thermal imaging observation, improves fire scene investigation efficiency and rescue safety, and environmental adaptability is stronger.

This invention provides an infrared thermal imaging method, relating to the field of infrared thermal imaging technology. The method utilizes a germanium infrared lens in an infrared thermal imaging system, whose surface is sequentially composed of subwavelength micro / nano structures and an anti-reflection film structure from the inside out. The infrared thermal imaging method includes: focusing target infrared radiation through the germanium infrared lens onto an infrared detection array; the infrared detection array converting the target infrared radiation into an electrical signal matrix; performing noise reduction and gain correction on the electrical signal matrix to obtain a preprocessed electrical signal matrix; performing temperature compensation on the preprocessed electrical signal matrix based on a temperature compensation formula and a transmittance temperature model to obtain a corrected signal matrix; and sequentially performing non-uniformity correction, image enhancement, and pseudo-color mapping on the corrected signal matrix before outputting and displaying the result. Using the method of this invention, higher transmittance, lower reflection loss, and more stable thermal imaging can be achieved.

The present application relates to a small target detection device, a detection method and application enhanced by cross-modal image information fusion. The detection device comprises: an image acquisition module for acquiring a visible light image and an infrared thermal imaging image; a feature extraction module comprising a double-flow backbone network for extracting multi-scale features of the images, wherein a micro-domain enhancement convolution module (MECM) is integrated in the backbone network; a fusion module for adaptively fusing feature maps of two modalities through a cross-modal feature coupling module (CMFCM) at a specific level; a feature enhancement module for multi-scale enhancement of the fused features through a feature pyramid structure and a multi-scale aggregation pooling module (MAPM); and a detection module for target detection based on the enhanced features and outputting the results.

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.

This invention discloses a method and system for testing the compressive strength of concrete in building engineering, relating to the field of concrete strength testing technology. The method includes: acquiring ultrasonic propagation data, infrared thermal imaging sequences, and three-dimensional surface topography point clouds of concrete components to form a multi-dimensional physical field data set; performing cross-modal fusion processing on the data set to generate a feature mapping map of internal defects in the concrete and a material homogeneity distribution spectrum; calling a pre-trained strength prediction model to analyze the feature mapping map and distribution spectrum to obtain predicted compressive strength values ​​and markers of structurally weak areas; spatially weighting the predicted values ​​based on the markers to generate corrected compressive strength values; and outputting a test report and maintenance recommendations based on the corrected values ​​and distribution spectrum. This method improves the accuracy of strength testing and the comprehensiveness of defect identification.

The application discloses a kind of based on molten pool state feedback's titanium alloy laser welding pore control method and system, by design adjustable electromagnetic stirring power and frequency electromagnetic generating module connection magnetic field exerting component, establish the matching process parameter library of electromagnetic stirring and laser welding, cooperative adjustment infrared blue light composite laser welding process parameter, including infrared laser power, blue light laser power, welding speed and defocusing amount.Again using high-speed camera device carries infrared thermal imaging monitoring molten pool state, simultaneously construct real-time monitoring and feedback control system, to realize titanium alloy welding overall closed-loop control.Adopt the method of the application can realize the stirring of molten pool in laser welding process, make pore effectively escape, avoid the pore defect caused by gas not in time to escape under the condition that laser welding cooling speed is faster.Titanium alloy laser welding pore rate is reduced to 2% and below, compared with traditional laser welding method reduces more than 80%, significantly improves welding quality stability.

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 present application provides a coke level intelligent monitoring and automatic control system in a saturated steam environment, relates to the field of petrochemical industry, and comprises a dehydration bin, a data acquisition module and a data transmission module; the data acquisition module comprises a laser radar level gauge and an infrared thermal imaging monitor; the laser radar level gauge is fixedly connected to the top end face of the inner side of the dehydration bin; the infrared thermal imaging monitor is arranged on the opposite side of the feed inlet; an equipment execution module is connected to the data transmission module; the equipment execution module comprises an intelligent grab bucket mechanism; the intelligent grab bucket mechanism is arranged at the top end of the inner side of the dehydration bin; an electric sliding block is slidably connected to an electric sliding rail, so that the coke level, water level, flow state and coke form can be captured in all dimensions, the limitation of traditional single parameter monitoring is broken, and comprehensive and reliable data support is provided for subsequent control decision; and the problem that the operator cannot observe the discharging condition of the coke tower bottom chute and cannot timely adjust the coke beating operation due to the steam diffusion in the dehydration bin is solved.

This invention relates to the field of medical data mining technology, specifically to a system for assessing eye muscle fatigue in myasthenia gravis based on infrared thermal imaging. First, the degree of blood circulation impairment is determined based on the temperature changes of pixels in various directions within a speckled region. Then, based on the number of speckled regions and the concentration of hot spots, a speckled region influence value reflecting local blood circulation and metabolic abnormalities is determined. Next, combining the degree of blood circulation impairment, the speckled region influence value, and the speckled region distribution, a comprehensive reference degree of eye muscle fatigue is determined. Furthermore, considering the distribution of speckled regions under the influence of grease, the degree of blood circulation impairment, and the characteristic that the reference degree of eye muscle fatigue typically does not change, a corresponding grease influence value is determined. Thus, combining the reference degree of eye muscle fatigue and the grease influence value allows for a more accurate determination of the eye muscle fatigue assessment value, resulting in better assessment of eye muscle fatigue in myasthenia gravis based on this value.

The application discloses a kind of IGBT module's failure prediction method and system, including IGBT module, the input end of the IGBT module is electrically connected with operating monitoring system bidirectionally, and the output end of the operating monitoring system is electrically connected with control circuit bidirectionally.The application is collected by contact thermocouple, thermistor, infrared thermal imaging camera, diffusion coefficient monitoring module, mobility monitoring module, carrier concentration monitoring module, short-circuit test module and Qg test module to IGBT module internal data and is transferred to control circuit after integration by integrated collection module, terminal processor processes data and transmits it to IGBT module operating prediction system to predict and judge, can improve the monitoring mode of existing IGBT module, can monitor and predict the existing and future state of IGBT module, user can timely master the unexpected dangerous condition of IGBT module in running process, avoid the safety of IGBT module is influenced.

This invention relates to the fields of physiological signal processing and emotion recognition technology, and discloses a method for recognizing physiological and emotional states of diverse populations. The method includes: acquiring facial video streams, infrared thermal imaging, and electrodermal signals; performing spectral adaptive enhancement based on skin color to obtain a spectrally enhanced video stream; inputting the spectrally enhanced video stream into a spatially modulated attention network to obtain a remote photoplethysmography waveform; extracting temperature distribution features from infrared thermal imaging; extracting electrodermal response features from electrodermal signals; aligning the three signals spatiotemporally and constructing alternative features for the failed signal based on the signal-to-noise ratio; inputting the three signals and alternative features into a multimodal signal pattern recognition network for weighted fusion, outputting a fused physiological feature; inputting the fused physiological feature into a population-level verification network for population adaptive matching and individual baseline correction, outputting the final emotional state. This invention achieves robust, fair, and accurate emotion recognition for diverse populations.

The application provides a kind of based on unmanned aerial vehicle's river surface floating object monitoring method and system, belong to water environment protection monitoring field, including: obtaining the river bank boundary line data of target area and utilize the river bank boundary line data to build river bank model;Based on the river bank model, utilize unmanned aerial vehicle to cruise and obtain laser radar point cloud data, visible light image data and infrared thermal imaging data;The visible light image data and the infrared thermal imaging data are fused to obtain fused image data;Utilize the fused image data and the laser radar point cloud data to determine river surface floating object.The application can not only rely on image to determine the appearance characteristics of floating object, but also can accurately obtain its position, volume and other key information by means of point cloud data, greatly improving the accuracy of river surface floating object monitoring.

The application relates to a cooking utensil state detection method, an intelligent range hood and a computer device, wherein the method comprises the following steps: performing infrared thermal imaging on a target region above a heated cooking utensil to obtain a real-time temperature matrix corresponding to the target region; the real-time temperature matrix comprises a plurality of temperature values, and each temperature value corresponds to a corresponding position in the target region; gradient analysis is performed on each temperature value in the real-time temperature matrix to obtain a corresponding gradient amplitude matrix; the gradient amplitude matrix comprises a temperature gradient amplitude corresponding to each temperature value; based on each temperature value in the real-time temperature matrix and the gradient amplitude matrix, a heat diffusion coefficient of the cooking utensil is determined; and based on the heat diffusion coefficient, the current state of the cooking utensil is identified. Through the application, the problem that the actual state of the cooking utensil cannot be accurately detected is solved, and the state of the cooking utensil is accurately detected, so that the user can timely avoid the safety and health risks caused by the change of the state of the cooking utensil.

This application discloses an intelligent diagnostic method and system for leakage risk of metal roof nodes based on image recognition. The method includes: S1, multimodal data acquisition and preprocessing; S2, node region localization and feature extraction; S3, multi-scale visual Transformer feature fusion; S4, leakage feature identification and classification; S5, leakage risk assessment and early warning; and S6, model iteration and optimization. This application utilizes simultaneous acquisition and pixel-level registration of visible light and infrared thermal imaging to simultaneously acquire the surface texture information and temperature distribution information of nodes. By fusing global context and local detail features using a multi-scale visual Transformer network, it can effectively correlate weakly correlated features across modalities, thereby overcoming the limitations of single-modal detection. It can detect both visible surface defects and hidden problems such as internal water accumulation, reducing false alarm and missed detection rates.

The application discloses a ship engine room infrared thermal image and vibration combined diagnosis method based on a multi-mode, relates to the technical field of mechanical equipment state monitoring, and synchronously collects infrared thermal image data and vibration data of a contact area between a bearing seat and a mounting base structure in an engine room operation process, forms an infrared thermal imaging frame sequence and a vibration signal data sequence through data processing; constructs a contact area thermal image sequence and a radial vibration attenuation sequence according to the infrared thermal imaging frame sequence and the vibration signal data sequence, and maps to a unified time axis for consistency determination; aggregates time sub-sections with inconsistent evolution rhythms to form a thermal-vibration response deviation trend, judges the thermal-vibration response deviation trend, and outputs thermal-vibration response deviation results of the contact area. The method is suitable for positioning and discriminating abnormal contact between a bearing seat and a mounting base of a ship engine room through time sequence correlation analysis of thermal image information and vibration information for combined identification of the structure contact state.

This invention discloses a battery health diagnosis method based on multimodal image fusion, relating to the field of battery health diagnosis technology. The method includes the following steps: simultaneously acquiring visible light and infrared thermal imaging images of the battery, and dividing the battery into local diagnostic units based on prior data; extracting visible light and infrared thermal imaging feature vectors from the local diagnostic units, and generating cross-modal consistency constraints by calling a pre-constructed cross-modal consistency constraint model; calculating the bimodal correlation degree of each unit by combining the feature vectors and cross-modal constraints to determine the unit failure mode; when the failure mode is a high-confidence failure, analyzing its spatial expansion trend using a spatial clustering algorithm based on graph connectivity; and generating a battery health diagnosis result by combining the unit failure mode and spatial expansion trend. This invention significantly reduces the impact of environmental interference and occasional anomalies through collaborative analysis and consistency constraints of multimodal images.

A method for identifying the location of an indoor fire source based on infrared thermal images of the outer surface of a glass curtain wall is provided. [Solution] The steps include: data structure construction: mainly including steps of constructing a fire dataset, temperature distribution of the outer surface of the glass curtain wall, image extraction and processing; construction and training of a Resnet deep learning model; and fire source location determination using the Resnet deep learning model. In the early stages of fire development, a reconnaissance drone equipped with an infrared thermal imaging camera is operated to fly outside the glass curtain wall of the fire floor, and the position of the reconnaissance drone is adjusted to obtain a complete infrared thermal image of the outer surface of the glass curtain wall of the fire floor. The infrared thermal image of the outer surface of the glass curtain wall acquired by the infrared thermal imaging camera is input to a trained Resnet-50 deep learning model, and the model outputs the fire source location number after analysis.

The application relates to a defect detection method, system, device and medium of a gas insulated switchgear. The method comprises the following steps: acquiring infrared thermal images and high-resolution visible light images of a GIS device to be detected, and inputting the images into a CAFF-DINO model after preprocessing and registration; extracting a thermal distribution feature map and a surface texture feature map through a Swin-Transformer backbone network, and generating a cross-modal correlation feature map; performing channel splicing on the thermal distribution feature map, the surface texture feature map and the cross-modal correlation feature map to obtain a stacked feature map, and adjusting the channel dimension to a preset dimension to obtain a fusion feature map; inputting the fusion feature map into a DINO detection head to obtain a defect detection result; and the defect detection result comprises defect category and defect position information. The method can realize high-precision collaborative detection of internal and external defects of the GIS device.

1. The name of the design product: portable acoustic imaging instrument. 2. The use of the design product: the design product is used for acoustic imaging detection, sound source positioning, etc. 3. The design points of the design product: the shape of the product. 4. The picture or photo that best indicates the design points: design 2 perspective view 1. 5. Designate design 2 as the basic design. 6. Other circumstances that need to be explained: design 1 is the product form of the portable acoustic imaging instrument with other functional modules, such as infrared thermal imaging module; design 2 is the portable acoustic imaging instrument.

The present application relates to a kind of microphone and infrared thermal imaging combined positioning cable fault positioning method and system.The present application detects heat source due to abnormal discharge by infrared thermal imager.Infrared radiation all carries the characteristic information of object, after the power signal radiated by the heating site of object is converted into electric signal by photoelectric infrared detector, imaging device can simulate the spatial distribution of object surface temperature, finally, after system processing, form thermal image video signal, just obtain the thermal image corresponding to object surface heat distribution.The system is composed of infrared thermal imager and display two parts, infrared thermal imager is by non-contact detection infrared energy, and it is converted into electric signal after signal amplification and processing, generates thermal image, shows temperature distribution in space in the form of image, obtains spatial infrared thermal imaging chart.The present application reduces imaging range, reduces calculation amount;Make the accuracy of detection greatly improve real-time performance, system is simple and easy to realize.

This invention belongs to the field of mechanical engineering, specifically relating to a train model adaptive cleaning system based on multimodal perception. This system automatically identifies the three-dimensional contours and contamination distribution of different train models by fusing laser point clouds, visible light images, infrared thermal imaging, and onboard communication information. It generates spatially matching cleaning paths and media parameters by combining 3D reconstruction and semantic annotation of key components. Through closed-loop feedback, it dynamically corrects the spray intensity, improving cleaning coverage and avoiding structural interference. It integrates water resource reuse and energy recovery mechanisms, significantly reducing water and energy consumption, achieving efficient, safe, and environmentally friendly fully automated train cleaning. For example, train braking energy recovery technology converts kinetic energy into electrical energy through regenerative braking, significantly improving energy conversion efficiency. Simultaneously, the equipment flushing water reuse system effectively replaces conventional water resources by accumulating and reusing water resources, achieving water conservation and energy reduction.

This application provides a method and system for smoke and fire recognition based on multispectral image fusion, relating to the field of data processing. The method acquires visible light imaging sequences, infrared thermal imaging sequences, and gimbal pose sequences of the target monitoring area and constructs scene commitment identifiers; it generates joint observation units based on unified spatiotemporal calculations and extracts multimodal increments to form cross-modal increment ledgers; it filters candidate anomalies based on structural destructiveness, thermal behavior persistence, spatial expansion, and cross-modal synergy; it performs cross-modal playback comparisons using a counterfactual surrogate fragment library and generates causal preemption chains; it combines asynchronous evidence ledgers to determine self-sustaining signs and establishes cross-regional inheritance relationship graphs; and it constructs a risk takeover ledger based on modal dominance switching trajectories and outputs graded smoke and fire alarm results. Implementing this technical solution facilitates the effective differentiation between smoke and fire anomalies and non-fire disturbances under multispectral observation conditions, thereby improving the accuracy of smoke and fire recognition based on multispectral image fusion.

This utility model discloses an aircraft brake pad wear and temperature detection system based on infrared thermal imaging, including a temperature detection module for detecting brake pad temperature, a central control module, and an alarm module installed in the cockpit. The temperature detection module consists of multiple detection mechanisms, each including two thermal imagers mounted on opposite sides of the brake pad. The central control module receives and processes infrared images transmitted from the thermal imagers. The alarm module receives alarm signals from the central control module and is connected to the central control module via a wireless transmission module. The advantages of this utility model are that it not only allows for real-time monitoring of brake pad temperature but also monitors brake pad wear, facilitating subsequent maintenance.

This invention discloses a deep learning-based intelligent AOI defect classification and detection system for PCBs, comprising a multimodal image acquisition module that simultaneously acquires optical and infrared images of the PCB board, a hierarchical decision classification module that receives image pairs and sequentially performs defect localization, multi-branch feature fusion, defect classification, and confidence output, and a feedback optimization module that filters samples based on confidence and triggers incremental learning. By introducing an infrared thermal imaging module that is triggered synchronously with electrical performance testing and fusing it with high-resolution optical images, this invention constructs a multi-physical-dimensional detection information source. This enables the system to capture defect features that are difficult to detect using traditional pure optical methods, thereby significantly improving the detection rate and classification accuracy of hidden and complex defects, and solving the problem of missed detection and misjudgment caused by a single dimension of detection information.