245 results about "Thermography" patented technology

The invention relates to the technical field of image recognition, in particular to a lightning arrester fault thermal imaging picture recognition method and system combined with gaze prediction, and the method comprises the steps: carrying out the down-sampling of an original thermal imaging image to a fixed size, sequentially passing through a multi-layer convolution and a Spatial Softmax layer, and outputting a predicted gaze point track sequence, extracting a key area and a non-key area according to the intensity of the fixation point track sequence; reconstructing the key area to obtain a compressed and recombined target area; inputting the non-key region into a variational auto-encoder to obtain a low-dimensional potential feature vector; and inputting the image-structure joint feature representation into an EffiCroprViT model, and finally obtaining a lightning arrester fault classification result. Local and global features are efficiently fused, the calculation complexity is reduced, background noise interference is effectively suppressed, real-time and accurate identification and early warning of the fault state of power equipment are realized, and the fault classification method has the advantages of high efficiency, high reliability and high reliability. Therefore, the safety and stability of power grid operation are ensured.

The invention relates to the field of data processing, in particular to a multi-parameter collaborative optimization method and system based on a data center cooling system, and the method comprises the steps: obtaining a cooling subsystem of a computing equipment integrated cabinet, and carrying out the short-time temperature analysis of the computing equipment integrated cabinet based on infrared monitoring data and temperature sensing data, if it is confirmed that the limiting temperature of the component is not higher than the corresponding preset temperature threshold value according to the current temperature distribution, and it is confirmed that the continuous heating temperature is lower than the preset temperature change threshold value based on the temperature change trend, the temperature change trend and the current temperature distribution are obtained; if yes, returning to the step of executing multi-modal data acquisition on the computing equipment integration cabinet and the cooling subsystem, and otherwise, synthesizing the predicted temperature data, obtaining a cooling subsystem configuration strategy and setting the cooling subsystem. According to the invention, the cooling monitoring and adjustment of the computing equipment of the data center are realized by integrating the data collected by the temperature sensor and the thermal imaging probe which are reasonably arranged.

The methods described herein provide improvements in composite infrared absorption imaging. The scanning approach described herein reduces erroneous measurements caused by thermal drift and optical interference that occurs between light scattering from the top surface of the sample and light scattering from the underlying substrate. Embodiments described herein relate to imaging and spectroscopy, and more particularly, to improvements in photo-thermal imaging and spectroscopy systems, and techniques for obtaining spectral information characterizing optical properties and / or materials or chemical compositions of a sample, such as information related to infrared (IR) absorption spectroscopy.

The invention relates to the technical field of high-place operation safety equipment, in particular to an outer wall defect detection method based on infrared thermography, which comprises the following steps: acquiring a construction building drawing of each building, acquiring report records about wall body cracks in an intelligent property platform and forming a plurality of crack type sets and related crack type sets, combining the related crack type sets into a related crack set, determining a crack building drawing of each building in combination with report records, determining a plurality of crack clustering centers of the corresponding building according to the crack building drawing, and determining whether the crack clustering centers are inner side defect points or not according to the crack clustering centers and the target positions; determining an outer wall detection position of the infrared thermal image according to the inner side defect point, and controlling the detection unmanned aerial vehicle to move to the outer wall detection position to obtain a corresponding outer wall infrared thermal image; and determining whether a temperature abnormal area exists or not according to the outer wall infrared thermal image so as to determine wall defects. Through crack clustering and directional detection, the problems of blind detection, low efficiency and insufficient accuracy in outer wall defect detection are solved.

The invention discloses a gas leakage detection method. The method comprises the following steps: S10, carrying out denoising and image enhancement on an acquired visible light image and an acquired thermal infrared image; s20, carrying out image feature point matching; s30, fusing the visible light image and the thermal infrared image after registration; and S40, gas leakage detection based on the improved YOLOv8 framework. According to the invention, thermal imaging, multispectral and visible light imaging multi-source fusion technology is adopted, so that the problems of efficient detection and accurate identification of multiple types of gases in a broadband range are solved.

The invention provides a photovoltaic module fault image recognition system based on infrared thermal imaging analysis, and relates to the field of image recognition, comprising: an asynchronous image acquisition module calculates a response delay value based on component spatial distribution, a shielding state and a thermal capacity coefficient, and generates a dynamic scheduling path to control an infrared thermal imager to capture component images of different thermal response processes; the thermal anomaly trend analysis and recognition module constructs a time difference thermal response matrix, recognizes continuous multi-frame candidate temperature rise areas with the temperature rising continuously, and builds a temperature trend prediction model to judge thermal anomaly; the response behavior intervention and disturbance execution module calculates a disturbance influence factor, decides to apply disturbance to a target or an adjacent component and triggers image acquisition; and the routing inspection scheduling feedback updating module dynamically adjusts the priority and frequency of the acquisition path according to the thermal anomaly judgment result and the intervention data.

The invention discloses a fire early warning cooperative system composed of a thermal imaging double-spectrum intelligent ball, an intelligent analysis platform and a fire extinguishing unmanned aerial vehicle, which is applied to the technical field of fire early warning, and comprises the thermal imaging double-spectrum intelligent ball, an integrated visible light sensor and a thermal imaging sensor, and a double-spectrum fusion monitoring technology is adopted to carry out omnibearing and all-weather monitoring; the intelligent analysis platform simulates a fire spreading path based on a fire spreading prediction model of a fluid dynamics and machine learning algorithm, generates a three-dimensional fire danger thermodynamic diagram, and completes a whole-process response from regional early warning to command center decision making to unmanned aerial vehicle cluster task distribution through a multi-level early warning mechanism; the fire extinguishing unmanned aerial vehicle adopts a multi-model collaborative operation system to meet the fire extinguishing requirements of different fire scenes. According to the invention, in a complex and changeable fire scene, the fire hazard can be quickly and accurately identified, and the efficient disposal of fire extinguishing operation is realized.

The invention provides a perfluorohexanone active fire extinguishing system applied to an energy storage power station, and belongs to the technical field of active fire extinguishing systems, the perfluorohexanone active fire extinguishing system comprises a multi-mode composite detection array composed of a thermal imaging sensor, an air pressure sensor, a visible light camera and an ultraviolet light sensor, the multi-mode composite detection array is configured to collect temperature field data, air pressure data, visible light video streams and ultraviolet spectrum data in the energy storage battery cabin by a preset timestamp synchronization mechanism, and output four-mode original data streams to the thermal runaway micro-hotspot recognition engine and the like; early discovery, accurate positioning, fine release, true suppression and self-evolution full-closed-loop active fire extinguishing of the energy storage power station in the high-altitude extreme environment are achieved, and the safety, economical efficiency and long-term maintainability of the energy storage power station are remarkably improved.

The invention discloses an insulation hidden danger diagnosis method for a multi-mode alternating current power supply system for a transformer substation, and relates to the technical field of power system insulation state monitoring, and the method comprises the following steps: obtaining acoustic signal data, thermal imaging data and electrical parameter data; performing synchronous feature processing on the acoustic signal data, the thermal imaging data and the electrical parameter data to generate synchronous feature group data; performing multi-modal interaction feature extraction on the synchronous feature group data to form electricity-sound-heat anomaly triple data; and performing cross feature fusion on all the electricity-sound-heat anomaly triple data to obtain a multi-modal fusion feature vector. According to the method, the time synchronism of the multi-modal abnormal events is forcibly correlated by establishing the electricity-sound-heat anomaly triple data, the abnormal events with time correlation in the multi-modal data can be effectively identified, the problem of missing detection caused by single-modal analysis is solved, and therefore the reliability of a diagnosis result is improved.

The invention relates to the technical field of unmanned aerial vehicle detection and security and protection, and discloses a low-altitude unmanned aerial vehicle dual-mode detection method based on micro Doppler radar and infrared thermal imaging. According to the method, a monitoring area is continuously scanned through a micro-Doppler radar, and when a suspected target with the signal intensity lower than a preset threshold value is recognized, an infrared thermal imaging device is triggered to be started. The infrared device directly adjusts the orientation and focuses to a specific area according to the target orientation and distance information provided by the radar, and obtains a high-resolution thermal imaging sequence. And then the radiation temperature distribution, the temperature gradient and the thermal profile morphological characteristics of the target are analyzed, and final judgment is completed. According to the invention, on-demand starting and rapid and accurate guiding of the infrared sensor are realized, the overall power consumption of the system is reduced, and the cooperative detection response speed and the identification precision of the rapid moving target are improved at the same time.

The invention discloses a multi-mode safety perception emergency linkage system, method, equipment and medium. The system comprises a multi-mode perception module, and a thermal imaging double-spectrum intelligent ball is used for temperature detection and smoke detection; the intelligent analysis module is in communication connection with the multi-mode sensing module, receives the detection data transmitted by the thermal imaging double-spectrum intelligent ball, analyzes the detection data to judge the type of a fire behavior, calculates an optimal flight path when the fire behavior is judged, and generates a fire extinguishing instruction containing the coordinate position of a fire source and the optimal flight path; the unmanned aerial vehicle linkage module is in communication connection with the intelligent analysis module; and the comprehensive control module is in communication connection with the intelligent analysis module. When temperature abnormity and smoke signals are captured at the same time, the two kinds of detection data are verified mutually, the false alarm problem of a traditional single detection mode is solved, and more importantly, the fire type can be accurately judged.

1. The name of the design product: thermal imaging night vision device. 2. The use of the design product: for night observation patrol, etc. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention discloses a self-identification and early-warning method for abnormal high temperature of a vehicle in a free flow state, and the method achieves the precise identification of vehicle tire overheating and fire hazards through the fusion of thermal imaging analysis and a dynamic scene modeling technology. The method comprises the following steps: firstly, positioning a tire area in a thermal imaging image in real time by using a Yov11 model, segmenting an axle and a tread through a clustering algorithm in combination with temperature distribution and position characteristics, calculating a local average temperature and quantifying an abnormal index; meanwhile, environmental interference is eliminated by adopting a dynamic background modeling technology based on statistical analysis, efficient classification is performed on smoke areas in combination with a full convolutional neural network, and a smoke probability is output. Furthermore, the system dynamically evaluates the comprehensive risk level by fusing the temperature abnormal data and the smoke detection result, and links a grading early warning mechanism. According to the method, the detection precision and the response speed in a complex free flow scene are remarkably improved, the method can be widely applied to the fields of logistics transportation, dangerous goods vehicle monitoring and the like, and intelligent guarantee is provided for driving safety.

The AI-based intelligent dehumidifier comprises a central server and multiple sets of intelligent dehumidifiers, the multiple sets of intelligent dehumidifiers are matched with attributes of the Internet of Things, the central server is in information transmission with the intelligent dehumidifiers through the Internet of Things, and each intelligent dehumidifier comprises a dehumidifier shell. And the thermal imaging camera is used for high-angle shooting and monitoring of a temperature field distribution diagram of the evaporator and the capillary tube. The AI simulation algorithm which can intelligently predict the frosting state and the frosting time of the intelligent dehumidifier, delay the frosting speed and accelerate the defrosting process is arranged in the intelligent dehumidifier in a matched mode, the air volume of a draught fan and the operation frequency of an inverter compressor can be automatically adjusted according to environment changes and equipment states, and therefore the dehumidification efficiency is optimized; by predicting the frosting condition of the evaporator and taking measures in advance, the defrosting time and frequency can be remarkably reduced, and the dehumidification efficiency is greatly improved.

The invention discloses an intelligent networking driving recording system based on multi-mode perception. The intelligent networking driving recording system comprises a perception layer, a processing layer, an application layer and a block chain evidence storage module. The invention further discloses a data tamper-proofing method of the intelligent networked driving recording system based on multi-mode perception, which comprises the following steps: S1, synchronously acquiring thermal radiation data, radar point cloud data and video image data in a driving environment through the infrared thermal imaging sensor, the 4D millimeter wave radar and the high-definition optical camera; s2, infrared thermal imaging data are optimized, radar point cloud clustering is optimized through a DBSCAN algorithm, and target tracking is achieved based on UKF. The system can cover the whole temperature range of-30 DEG C to 85 DEG C and severe weather such as rain, snow and haze, effectively reduces the false alarm rate of infrared thermal imaging and the missed detection rate of a millimeter wave radar static target, avoids the loss of accident key evidence caused by environmental factors, greatly improves the evidence obtaining reliability at night and in severe weather, and reduces traffic accident disputes.

The invention discloses a processing method and device for heating and rolling a composite board, and relates to the technical field of board processing, and the processing method comprises the following steps: synchronously conveying and feeding a raw material board and a modified POE (Polyolefin Elastomer) rubber material to obtain a to-be-processed composite blank; the to-be-processed composite blank is conveyed to an electric heating assembly, the real-time temperature rise rate of the to-be-processed composite blank is detected and calculated in real time through a temperature sensor, the glue material is fused and preliminarily attached to the raw material plate through temperature adjustment, and a preliminary composite plate is obtained; a thermal imaging detection device is adopted to obtain a distribution area where an adhesive layer of the preliminary composite board is heated unevenly, the heat preservation temperature of a heat preservation hot pressing assembly is adjusted according to the temperature difference condition of the area heated unevenly, and the preliminary composite board is subjected to even hot pressing; and cooling in a finished product cooling area to obtain a finished product composite board. By arranging stepped heating fusion and combining with the thermal imaging detection device, the accuracy of processing temperature control of the composite board is improved, so that the rolling processing quality of the composite board is improved.

The utility model provides a portable infrared thermography thermodetector which comprises a shell, an infrared thermography thermodetector body arranged in the shell and a handle assembly detachably installed at the bottom of the shell, a display screen is installed at the tail end of the shell, a base is arranged at the bottom of the shell, a sliding groove is formed in the bottom end of the base, and the handle assembly is detachably installed at the bottom of the shell. The inner walls of the two sides of the sliding groove are each provided with a first conducting strip, the size of the infrared thermal imaging thermodetector can be effectively reduced by folding the handle assembly, and after the handle assembly and the shell are detached, the infrared thermal imaging thermodetector is more convenient to carry. In addition, a worker can insert a hand into the protective belt to use the infrared thermal imaging thermodetector in a posture of holding the shell, so that the infrared thermal imaging thermodetector can be used in a narrow space, and if the space is narrower, the infrared thermal imaging thermodetector body can be detached from the shell and then is externally connected with a display screen through a data line, so that the infrared thermal imaging thermodetector is convenient to use. Therefore, the infrared thermal imaging thermodetector body can be used in a narrower space.

The application discloses an intelligent AI detection method based on infrared thermal images and automobile diagnosis, and the technical scheme of the application significantly improves the electric vehicle fire safety detection efficiency through multi-modal data fusion and intelligent analysis, the synchronous collection of double-band infrared and vehicle operation parameters constructs a multi-dimensional data basis, ensures the space-time consistency of thermal radiation characteristics and electrical state, secondly, the dynamic correlation model realizes the accurate triggering of abnormal current to thermal image enhancement, the partition gradient processing combined with dynamic threshold adjustment optimizes the detection sensitivity according to the thermal characteristics of different components, the three-dimensional thermal field reconstruction breaks through the limitation of surface detection, and can identify internal potential hot spots, finally, the closed-loop diagnosis is formed through the intelligent matching of the case library, so that the fault positioning accuracy reaches the component level, and the overall scheme solves the problem that the existing technology only relies on thermal infrared images for electric vehicle fire safety detection, and the contrast of the infrared thermal image is low and the detail resolution is poor.

The embodiment of the utility model provides thermal imaging equipment, and relates to the technical field of optical instruments. The thermal imaging equipment comprises a supporting piece, a visible light imaging assembly, an illumination assembly and a thermal imaging assembly, the visible light imaging assembly, the illumination assembly and the thermal imaging assembly are arranged on the supporting piece, and the illumination assembly and the thermal imaging assembly are located on the two opposite sides of the visible light imaging assembly in the first direction respectively. The first and second electrodes are respectively located at two ends of the support member in a first direction, and the first direction is parallel to the support member. The thermal imaging equipment is used for imaging a target.

A vessel harvesting system removes a target vessel from a patient for use as a bypass. An elongated harvesting instrument inserts into a body along a path of a target vessel which includes at least one side branch. The harvesting instrument includes a cutter for applying thermal energy to sever and cauterize the side branch. An endoscopic camera captures visible-light images from a distal tip of the instrument within a dissected tunnel around the target vessel. A thermal camera captures thermograms coinciding with the visible-light images to characterize a temperature present at respective surfaces in the tunnel. An image processor (e.g., an electronic controller) renders a video stream including the visible-light images and an overlay depicting the temperatures present on at least some of the respective surfaces when applying the thermal energy. A display presenting the video stream and overlay to a user can be an augmented-reality display.

The application provides a linear multi-spectrum radar and vision integrated machine, and belongs to the technical field of radar equipment, which comprises a shell, a main radar, a thermal imaging camera, a first white light camera, a blind-filling radar and a control module; the main radar is installed on the front and back sides of the shell, the thermal imaging camera and the first white light camera are both located directly above the main radar, the blind-filling radar is located directly below the main radar, and the control module is electrically connected with the main radar, the thermal imaging camera, the first white light camera and the blind-filling radar respectively. The linear multi-spectrum radar and vision integrated machine provided by the application can detect the blind area above the main radar through the thermal imaging camera and the first white light camera, and can detect the blind area below the main radar through the blind-filling radar, so that the detection range of the whole linear multi-spectrum radar and vision integrated machine is larger, the blind area range is reduced, and the detection precision and all-weather adaptability of the linear multi-spectrum radar and vision integrated machine are improved.

The invention discloses a wide-area illumination control system based on a dynamic delay mechanism, which belongs to the technical field of intelligent illumination and comprises a visible light camera module, a thermal imaging sensor module, an ambient light sensor module, a central processing unit and an Internet of Things lamp group. The visible light camera module is used for monitoring and storing images, the thermal imaging sensor module is used for obtaining thermal imaging data, the environment sensor module is used for collecting environment information, the central processing unit is used for controlling all the modules, and the Internet of Things lamp group is used for illumination. When any sensor detects a moving / heat source target and outputs a high-level alarm signal, the system judges that intrusion is effective, and the central processing unit immediately issues an instruction to the Internet of Things lamp group to break and cover the previous low-illumination maintenance state based on ambient light, so that high-brightness illumination in the whole process is ensured; the non-inductive lighting experience that no vehicle arrives and light arrives at first is provided for scenes such as a long-distance garage lane, and extreme energy saving is achieved.

The invention discloses a method for detecting and measuring the distance of a person in front of an underground unmanned electric locomotive. The method comprises the following steps of: S1, synchronizing data time; s2, performing camera external parameter calibration through a multi-modal calibration device; s3, generating multi-modal data; s4, performing personnel detection on the multi-modal data; s5, track area segmentation; and S6, determining a longitudinal distance and a transverse distance. According to the method, the track line region can be segmented more accurately by fusing visible light and thermal imaging image information, so that the accuracy of distance measurement is improved. Through remote transmission of visible light and thermal imaging images and distance measurement data, a manager can know the condition in front of the unmanned electric locomotive in real time in a ground monitoring center and handle abnormal conditions in time, remote monitoring and management of underground operation are achieved, and the workload and risk of manual inspection are reduced.

This invention discloses a method for assessing the fire status of a submersible compartment based on multi-source heterogeneous data fusion, comprising the following steps: 1) acquiring monitoring video streams of the compartment under natural light conditions; 2) dividing a acquired video into K segments, randomly selecting a small segment from each segment; inputting the selected small segment into a spatiotemporal dual-stream convolutional neural network to obtain category scores for different small segments, then fusing them to locate fire and smoke areas in the video stream; 3) acquiring a heat map of the monitored compartment area, and assessing the fire status of the compartment based on the thermal imaging image; 4) combining multiple heterogeneous fire early warning signal data for collaborative analysis and information fusion to provide accurate early warning of fire hazards in the compartment. This invention acquires monitoring video streams of the compartment under natural light conditions and designs a convolutional neural network model based on a temporal attention mechanism to process the video stream and detect and locate fire and smoke areas in the video stream.

The invention discloses steel plate high-precision bending machining equipment, and belongs to the technical field of metal machining equipment, the steel plate high-precision bending machining equipment comprises a base and a steel plate body, and the base is provided with a feeding assembly comprising a heat treatment assembly, a bending mechanism and a thermal imaging camera. A heating coil is integrated on an overturning rod of the feeding assembly, gradient preheating and synchronous overturning heating of two bending points of a steel plate body can be achieved in the sliding table conveying process, the continuous production efficiency is improved, and by arranging the offset rolling bending assembly, the mold core rolling downward combined lever principle is utilized, so that the production efficiency is improved. A steel plate body is subjected to progressive large-curvature-radius pre-bending in a bending groove, concentrated stress is dispersed, temperature field scanning is conducted on a bending area of the steel plate body in a waste heat state through the synergistic effect of a heat treatment assembly and a thermal imaging camera, and real-time crack recognition is conducted based on the characteristic that heat dissipation of a crack part is faster. And synchronization of processing and quality detection is realized.

1. Name of the product subject to this design: Thermal Imaging Camera and its Main Body. 2. Purpose of the product in this design: The overall purpose of the product in designs 1-3 is to be used as a thermal imaging camera, and the partial purpose of the product in design 1 is to be used as the main body of a thermal imaging camera. 3. The key design features of this product are: the shape shown by the solid line in Design 1, and the shapes in Design 2-3. 4. The image or photograph that best illustrates the key design points: Design 1 3D view. 5. Design 1 is designated as the basic design.

The application discloses a full-time bridge anti-ship collision warning method of visible light and thermal imaging camera, comprising a visible light and thermal imaging lens as a data acquisition device, a trajectory tracking and real-time data analysis and processing three parts. First, according to the real-time environmental conditions of the channel and the lens recognition accuracy, a double-lens adaptive decision system is used to switch the input source of the visible light and thermal imaging camera autonomously, then a multi-target ship identification and tracking algorithm based on deep learning is used to locate the ship in real time and display the trajectory, finally, according to a large number of historical trajectories of ships in the bridge area, a sound and light warning is given to the ship trajectory higher than the safety threshold. The application has the advantages of real-time convenience, all-weather monitoring, good robustness and non-contact, and overcomes the problem that the existing method is difficult to be applied to bridge anti-ship collision warning in poor illumination environment, and has good prospects for wide application in practical bridge safety monitoring.

The present invention discloses a display calibration mechanism for enabling a thermal imaging picture to be aligned with a low-light-level picture on a low-light-level night-vision device, including a base and an adjustment assembly, wherein the base is provided with an imaging member and a display, and the thermal imaging picture on the display and the low-light-level picture on the low-light-level night-vision device are simultaneously imagable on the imaging member, The present invention further discloses an externally-hung thermal imaging device. The adjustment of the relative positions of the thermal imaging picture and the low-light-level picture can be realized to ensure the imaging effect while improving the universality of the thermal imaging device itself.

The invention relates to a data processing device or control unit (123) for operating a forklift truck (120a) for transporting a plurality of goods (140) in a warehouse. The data processing device (123) comprises an interface (123b) configured to receive a plurality of sensor data from the forklift truck (120a) during its movement in the warehouse, wherein the plurality of sensor data includes a plurality of thermal imaging data of the forklift truck's (120a) surroundings. Furthermore, the data processing device (123) comprises a processor (123a) configured to create or update a temperature map of the warehouse based on the plurality of thermal imaging data, wherein the temperature map indicates a respective temperature value for a plurality of points in the warehouse. The data processing device or control unit (123)The control unit (123) can be part of the industrial truck (120a) or a stand-alone server.