93 results about "Thermal mapping" patented technology

The invention discloses a fire condition information processing and transmission method based on a wireless communication network, and relates to the technical field of fire condition information processing and transmission, and the method specifically comprises the following steps: generating a first draft of a fire situation map based on uploaded fire sensing information, and judging the spatial distribution state of sensing nodes, if it is judged that the sensing nodes are distributed unevenly, identifying all abnormal gathering areas in the first draft of the fire situation map and marking the abnormal gathering areas as focusing candidate areas; and identifying all abnormal points in each focusing candidate area, extracting spatial anomaly perception information of each abnormal point, analyzing and evaluating the distribution focusing degree of each focusing candidate area after extraction, and classifying each focusing candidate area according to an evaluation result. According to the method, the problem of heat map deviation caused by non-uniform distribution of sensing nodes in fire map construction is solved, and dynamic adjustment of a regional map strategy and real restoration of fire distribution are realized.

The invention relates to the technical field of electronic device thermal management, in particular to a circuit board device thermal analysis system based on target detection, which comprises a thermal processor, and the thermal processor is in communication connection with a thermal map generation module, a thermal model construction analysis module, an improved evaluation module and a thermal response module. An image acquisition unit and an image processing unit are arranged in the heat map generation module; according to the method, the device on the PCB is accurately identified and positioned through image processing and target detection technologies, and the thermal infrared image is accurately associated with the device, so that thermal analysis more accurately reflects the actual heat production condition of the PCB, a more targeted basis is provided for thermal management through model construction and analysis, and the thermal management efficiency is improved. Meanwhile, the thermal analysis label is obtained based on information feedback, targeted management on the PCB based on the thermal analysis label is facilitated, simulation evaluation is conducted on improvement of the improvement scheme, whether the improvement scheme of the PCB reaches the standard or not is judged, and the improvement effect and feasibility of the improvement scheme are visually known.

The invention belongs to the technical field of equipment detection, and particularly relates to a multi-modal fusion-based inspection method, a six-degree-of-freedom mechanical arm, a terminal and a storage medium, and the method comprises the steps: constructing a multi-modal sensing tail end module integrated with a visual sensor, an infrared thermal imaging sensor and a touch sensor on the six-degree-of-freedom mechanical arm; performing space-time alignment and fusion processing on the acquired image data, heat map data and tactile data; judging the operation state of the equipment based on the fused comprehensive feature data; the visual sensor provides equipment surface appearance and identification information, the infrared thermal imaging sensor captures temperature distribution and thermal gradient change, the touch sensor detects mechanical vibration, surface texture and contact pressure, a three-dimensional sensing system is formed, and the problem of one-sidedness of single-mode data is solved.

The invention provides an intelligent wafer thermodynamic diagram analysis and abnormal region positioning system, and relates to the technical field of intelligent manufacturing, and the system comprises a principal system which comprises a data collection subsystem, a data analysis subsystem, a thermodynamic diagram generation subsystem, an anomaly detection and positioning subsystem, a process optimization subsystem and an output subsystem. According to the invention, the temperature distribution, current density and material stress data of the wafer are collected in real time through the data collection subsystem by using an infrared sensor and optical imaging equipment, and the central control unit coordinates the subsystems to operate in sequence, so that the whole process automation from data collection to abnormal positioning is realized. Compared with traditional manual detection, the system does not need to depend on experience of technicians, large-scale and real-time monitoring can be carried out on wafers, the detection efficiency is remarkably improved, potential anomalies are found in time, defects are prevented from being generated, and an abnormal area is recognized through the anomaly detection and positioning subsystem by adopting a deep learning model.

The invention relates to the technical field of image processing, in particular to a device and method for fish behavior monitoring, and the device comprises a fish body grid construction module, a vertex optical flow tracking module, a compression potential energy calculation module, an energy field thermodynamic mapping module and a swimming mode identification module. According to the method, a triangular topological grid covering the surface of an organism is constructed, a time sequence vertex light flow track is tracked, an affine transformation matrix is used for analyzing the area scaling ratio of a local grid unit in the movement process, and geometric deformation of a visual layer is mapped into a physical potential energy index representing muscle contraction strength; a micro deformation difference is amplified in combination with nonlinear exponential operation, a visual energy distribution thermodynamic map is generated through Gaussian smoothing processing, conduction characteristics of a body high-energy connected region in a space-time dimension are identified, and crossing from pure track observation to biomechanical function evaluation is realized. And the energy consumption efficiency and explosion starting characteristics in different tail swinging modes can be accurately identified.

The invention discloses an on-site catalyst evaluation system and method based on surface detection, and belongs to the technical field of flue gas treatment. According to the technical scheme, the field catalyst evaluation system based on surface detection comprises a gas inlet atmosphere modulation module, a reactor module, a gas detection module and a tail gas treatment module which are connected in sequence; the gas inlet atmosphere modulation module comprises a gas inlet flue, a gas inlet stop valve, a gas inlet adjusting valve, a flue gas mixer, a modulation gas pipeline, a modulation gas stop valve and a modulation gas mass flow meter; the high-density sensor array and the optical imaging unit are combined with a spatial interpolation algorithm to generate an efficiency distribution heat map, real-time monitoring of surface activity distribution of the catalyst is achieved, through parallel testing of multiple reactor components and machine learning life prediction, the evaluation precision and research and development efficiency of the catalyst are remarkably improved, and the research and development cost is lowered. The method has the advantages that the catalyst surface efficiency heterogeneity is captured in real time, multi-channel accelerated testing is supported, and the service life is accurately predicted.

The invention discloses an air tightness detection tool and method based on multi-sensor fusion, and the tool comprises a detection platform, a nylon imitation block, microphones, pressure sensors and an infrared camera, and the microphones and the pressure sensors are installed and distributed through an installation position array preset on the nylon imitation block. An infrared camera collects a heat map of a nylon imitation block area from the outside, a multi-sensor fusion framework is formed to obtain pressure gradient change, sound wave data and temperature data, and leakage points are analyzed and deduced based on the pressure gradient change, the sound wave data and the temperature data. The microphone and the pressure sensor are installed on the nylon imitation block in a pre-embedded mode, matrix structures are formed respectively to monitor internal sound wave data and pressure gradient change in the airtightness detection process of the to-be-detected workpiece, the infrared camera is adopted outside to collect temperature data, the sound wave data, the pressure gradient change and the temperature data are combined, and the airtightness detection accuracy of the to-be-detected workpiece is improved. And the three-dimensional coordinate of the leakage point is quickly determined.

Provided are intelligent temperature control method and system for die-casting die. Method includes setting target number of groups of temperature control regions and configuring initial temperature determination rule and initial temperature control strategy for each temperature control region; obtaining front-side thermal image of die using infrared camera mounted on both sides of spraying manipulator, and matching the same with CAD drawing of the die to obtain CAD thermal map of die; determining monitoring region on surface of die, and classifying monitoring regions into target number of groups of temperature control regions based on expected temperature requirement of die; calculating temperature value and determining temperature state of each monitoring region based on initial temperature determination rule of each temperature control region and temperature value of each monitoring region, and adjusting temperature of each monitoring region based on initial temperature control strategy of each temperature control region.

A heating, ventilation, and air conditioning (HVAC) system includes a network of wireless remote climate sensors to develop a complete heat map of an enclosed space. The remote climate sensor is configured to collect temperature and humidity data on a zone of the enclosed space. The HVAC system uses a network of these sensors to obtain data points across the enclosed space. The resulting heat map is used by the HVAC system to determine where to direct air in the enclosed space. By comparing the temperature and humidity at a specific remote climate sensor with the user's desired temperature and humidity, the HVAC system can decide whether to increase or decrease the air flow through a variable damper that is located near the remote climate sensor. The disclosed HVAC system provides even comfort to the user along with reduced energy consumption.

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 invention relates to a rebound-acoustics-based rebound apparatus and a strength detection method thereof.Firstly, a force sensor and an audio acquisition device are integrated in the rebound apparatus, when a rebound test is carried out, the force sensor measures the stress change before and after a spring is impacted, and then the rebound value reading is calculated by calculating the relationship between the spring elongation and the stress; after the test is finished, the magnetic attraction device automatically retracts the spring to ensure that the device can be used for the next test, then the audio acquisition device records a sound signal in each test process, the sound signal is preprocessed through a WaveNet algorithm to remove noise, then features are extracted from the collected sound signal, and the features are extracted from the collected sound signal. And combining the extracted sound features into a feature matrix, analyzing and screening out features highly related to the strength of the building material by using a correlation heat map, and finally inputting a rebound value and the screened sound features into an XGBoost regression model to predict the strength of the building material. The method supports off-line operation and is suitable for rapid detection and evaluation of various hard building materials.

The present disclosure relates to a system, method, and apparatus for mapping the fallout of atmospheric sounding devices such as radiosondes. This technology provides a mechanism for receiving launch data, plotting launch sites, and displaying trajectory heatmaps through a graphical user interface. The system includes features for overlaying concentric range circles, offering interactive timelines, and distinguishing between radiosonde altitudes using color indicators. Additional functionalities enable the display of detailed fallout data, calculation of Circle Error Probable (CEP) for estimating landing sites, and generation of fallout density heatmaps. These capabilities facilitate a comprehensive understanding and management of radiosonde deployment and environmental impact, enhancing the efficiency of meteorological data collection and analysis.

The application discloses a kind of spine segmentation methods, comprising the following steps: step 1: data pre-processing, generate spine heat map and windowing to image, the window width and window width of lumbar bone tissue are respectively set to 400 and 1800;Step 2: using U-Net structure roughly locates lumbar vertebra;Step 3: calculate image bounding box, obtain the range of selected lumbar vertebra using 4 neighborhood, and select the voxel with HU value greater than 0.3 times of the maximum HU value of image as possible lumbar vertebra, then the obtained bounding box is extended in each dimension 0.05-0.2 times of the corresponding image size;Step 4: network segmentation based on XUnet network, XUnet uses Inception block to extract features;Through the implementation of the application, while deepening the network width and depth, improving the network expression ability, further reduces the redundant parameters in the network, realizes the deep learning and automatic efficient vertebral automatic segmentation effect, the positioning segmentation effect is good, plays a prominent progress, has certain use value and popularization value.

Method for configuring the manufacturing of a part using a machine for additive manufacturing, by means of a production strategy indicating at least one manufacturing trajectory followed by the machine, comprising steps of: - determining (310) a thermal map for at least one layer of the part, associating a local temperature rise with the points of the trajectory; - determining (314) critical thermal thresholds as a function of a correlation between the local temperature rise and a measurement relating to a defect representative of the quality of the part; - adapting (316) the production strategy as a function of the thermal thresholds and the thermal map. Figure for the abstract: Fig. 3

The application discloses a multi-peak decomposition time-resolved Raman spectrum thermal map interactive analysis method and system, and belongs to the field of spectrum analysis. The method comprises the following steps: continuously or time-divisionally collecting a to-be-measured sample to obtain Raman spectrum data corresponding to different time points; preprocessing the original Raman spectrum data; extracting spectral characteristic peaks by using an adaptive peak value recognition algorithm, and performing characteristic peak integral calculation; obtaining time contribution coefficients of different chemical components or characteristic signals in the time dimension by using a multi-peak decomposition algorithm; generating a Raman thermal map in the time dimension according to the characteristic peak intensity and / or the time contribution coefficients; establishing an index mapping relationship between the position of the Raman thermal map and the corresponding time Raman spectrum data; and responding to the interactive operation of the user on the thermal map and displaying the Raman spectrum curve at the corresponding time point in real time. The application can realize visual display, dynamic monitoring and interactive analysis of time sequence data of Raman spectrum, and improves the efficiency and accuracy of Raman signal analysis of dynamic samples.

A kind of power equipment image processing method based on optical fiber bundle imaging, storage medium and system, method is: signal output by infrared fiber bundle is collected by infrared camera pixel matrix, unit in matrix is divided into effective unit and invalid unit, and generate unit division binary matrix data file;Again processing obtains temperature correction matrix data file, temperature segmented point corresponding response value matrix data file, and establish the correction value of response value matrix under different radiation scene;Through numerical fitting and interpolation compensation method, the video stream of optical fiber bundle transmission image is carried out real-time restoration and optimization, completes the inversion from thermal map to temperature field distribution;The present application also includes the storage medium and system of storing the power equipment image processing method based on optical fiber bundle imaging of running this, the present application carries out real-time restoration and optimization to the video stream of optical fiber bundle transmission image by numerical fitting and interpolation compensation method, completes the inversion from thermal map to temperature field distribution.

A catheter is disclosed comprising a catheter shaft including a proximal end and a distal end. A flexible framework can be connected to the distal end of the catheter shaft, wherein the flexible framework includes a plurality of heating electrodes and a temperature sensor. The plurality of heating electrodes can be configured to be heated to a first temperature, the first temperature being lower than which radio frequency ablation is performed. The plurality of heating electrodes can be configured to be heated to a second temperature, the second temperature being a temperature at which radio frequency ablation is performed.

The invention discloses a fatigue test crack detection method based on thermal imaging. In the periodic fatigue loading process, the surface temperature change of a sample is detected in real time through infrared thermal imaging, and an amplitude diagram and a phase diagram of weak temperature fluctuation are obtained through calculation; segmenting the sample through local phase consistency, prefabricating a gap and a background, and only performing subsequent analysis on a sample area so as to eliminate background interference; after the amplitude diagram is binarized, the boundary displacement influence is eliminated through a simple boundary displacement review strategy and by means of the boundary displacement direction and stress concentration point position relation, complex feature point matching and displacement estimation between images do not need to be conducted through the algorithm, the calculated amount is small, and reliability is high; the crack length is calculated according to the detected movement track of the crack tip feature point, the method does not depend on static crack features, the basic assumption that sample changes inevitably come from damage generation and development is utilized, and crack length evaluation is not affected even if wrong feature points are extracted through single-frame heat map analysis.

In the endoscopic examination support apparatus, the image acquisition means acquires an endoscopic video captured by an endoscope. The lesion detection means detects a lesion candidate from the endoscopic video. The heat map generation means generates a heat map indicating a possibility of lesion of the lesion candidate in the endoscopic video by a color. The display control means displays a position of a lesion on a frame of the endoscopic video based on the lesion candidate and the heat map.

The invention provides a building outer wall hollowing identification method and system based on pulsed eddy current thermal imaging, and the method comprises the steps: enabling a pulsed eddy current excitation device to act on the surface of a building outer wall, applying transient pulsed magnetic field excitation to a metal component in a wall body, and enabling the metal component to sense eddy current and serve as an internal heat source to generate Joule heat; synchronously acquiring the transient pulsed magnetic field excitation by using an infrared thermal imager to obtain a heat map sequence formed by internal heat conduction on the surface of the outer wall of the building, and preprocessing the heat map sequence; and on the basis of the preprocessed heat map sequence, solving a heat conduction inverse problem to reconstruct a wall internal thermal attribute feature map, and on the basis of the wall internal thermal attribute feature map, completing the identification of the building external wall hollowing. According to the invention, deep, accurate, quantitative and automatic detection of building outer wall hollowing is realized, and reliability, efficiency and applicability are obviously better than those of the prior art.

The present invention discloses a method for quickly detecting the fault risk of a solar heat collection field, which includes the following steps; Step 1: By setting an infrared thermal imaging camera for real-time monitoring, an overall temperature distribution thermal map of the solar heat collection field is obtained through shooting; Step 2: Establish communication between the infrared thermal imaging camera and the computer to collect temperature images of the temperature state of the heat collection field; Step 3: Preprocess and regionally divide the overall temperature distribution thermal map of the heat collection field, and perform feature extraction to obtain a scatter plot of the fault temperature field of the collectors in each region; Step 4: Import the extracted feature information of the temperature field distribution and related characteristic parameters in each region into the feature library of the solar collector fault model, and perform two matching analyses of the feature library of the fault model in sequence, so as to improve the fault detection efficiency of the heat collection field, reduce the false alarm rate and the missed alarm rate, and ensure the safe operation of the solar heat collection system. The present invention has the characteristics of simple operation and no need to upgrade the system and add new sensors.

This invention provides a method, system, and vehicle for cabin temperature control. The method specifically includes: (1) receiving a temperature distribution thermal map and images of drivers and passengers sent by an infrared imaging device and a camera; (2) acquiring the actual body surface temperature of all drivers and passengers in the cabin; and (3) controlling the air volume and / or air temperature of the air outlets in the temperature control zone so that the actual body surface temperature of the drivers and passengers in the temperature control zone reaches the set target body surface temperature. This invention controls the air volume and air temperature of the air outlets in the temperature control zone based on the actual body surface temperature of the drivers and passengers and their set target body surface temperature, thereby achieving zoned temperature control in the cabin and better meeting the personalized needs of users.

The invention relates to the technical field of infrared thermal wave nondestructive testing, and discloses a method, a system, equipment and a medium for improving an infrared thermal wave nondestructive testing effect. Inputting into a physical information neural network model which takes a physical constraint comprehensive model as a constraint and is trained by adopting a multi-task loss function based on a self-adaptive weight adjustment mechanism to carry out atmospheric error correction, and outputting an infrared correction heat map; inputting the correction result into a pre-trained target detection network model for defect identification, and outputting a defect identification result; by optimizing the excitation mode, the image correction algorithm and the defect recognition algorithm, the influence of atmospheric factors on the accuracy of an infrared thermal wave detection result under a long-distance detection condition is reduced, automatic defect recognition is realized, and technical support is provided for engineering application of an infrared thermal wave technology.

The invention relates to the field of wireless signal detection, in particular to a wireless signal detection method and system fused with thermal imaging. The method comprises the following steps: acquiring wireless signal data and a heat map image sequence, and executing alignment and synchronization processing to generate synchronization feature data; constructing a three-dimensional heat source distribution map and extracting regional features, fusing a heat map gray scale and a signal intensity function to construct a joint feature model, and identifying a suspected device type and a confidence level; and generating a threat score based on a matching result, forming an image auxiliary analysis result in combination with millimeter wave verification and boundary reconstruction, and finally generating a countering control instruction. According to the invention, type identification and accurate positioning of the silent equipment can be realized in a complex shielding environment; a topological graph and a flow structure of wireless equipment are hard-solved through a professional chip; a lazy loading interference mechanism and a white list elimination strategy are adopted, so that the interference efficiency and the system safety are improved; and a thermal imaging means is combined to solve the positioning problem of the last meter.

The invention relates to a sensorless high-precision thermal monitoring method and a sensorless high-precision thermal monitoring system for a silicon optical interconnection many-core chip. The method comprises the following steps: acquiring running state data acquired by multiplexing an inherent optical device of an ONoC and an equivalent thermal resistance-capacitance circuit obtained by physical structure analysis based on the ONoC; k-means sampling optimization is carried out according to the operation state data and the equivalent thermal resistance-capacitance circuit, non-communication nodes are selected as sampling points, and temperature data of the sampling points are acquired; and according to the power consumption data of the ONoC and the temperature data of the sampling points, constructing a full-chip dynamic thermal model based on an equivalent thermal resistance-capacitance circuit to carry out power-temperature correlation analysis, and outputting a layered temperature heat map and alarm information. The ONoC inherent optical device is multiplexed to obtain the operation state data, the real-time power consumption information of the chip is combined, the equivalent thermal resistance-capacitance circuit and the K-means sampling optimization are based, the rapid and accurate reconstruction of the heat distribution of the whole chip is realized on the basis of not additionally adding a thermal sensor, and the monitoring reliability is improved.

This invention relates to the field of computer heat dissipation and hardware reliability monitoring technology, specifically to an intelligent heat dissipation and monitoring system and method for chips, comprising: a state decision module, an action correction module, a deviation feedback module, and a closed-loop control module. The invention generates an initial state flow by collecting junction temperature, instruction throughput, and transient voltage drop, and infers a preliminary action flow using a thermal sensing decision engine. Junction temperature data and the preliminary action flow are fed to a cross-domain thermal mapping engine to calculate the thermal response step trajectory to generate a temperature rise trend flow. Based on the safety threshold calculated from the thermal fatigue characteristics of the chip material, over-limit actions are forcibly corrected, and a safe execution flow is output. The difference between the preliminary action flow and the safe execution flow is extracted as a negative penalty term and fed back to the engine reward function. A transient voltage drop calibration pulse modulation signal is acquired, and power supply fluctuations are compensated before driving the heat dissipation hardware. This invention achieves reliable heat dissipation management with self-learning capabilities while ensuring the physical safety of the hardware.

The invention discloses a weather adaptive three-dimensional target detection method based on multi-modal fusion. The method comprises the following steps: acquiring a multi-modal data set marked with a three-dimensional target true value frame under complex weather; a dual perception fusion detection model is constructed, feature extraction is performed on the laser radar point cloud and the 4D millimeter wave radar point cloud, the features are mapped to a BEV space, a BEV space target distribution heat map is generated through a target perception enhancement module, a 4D millimeter wave radar feature modulation coefficient is generated through a weather perception modulation module, and 4D millimeter wave radar features are modulated. After being spliced with the laser radar features, the laser radar features are input into a decoder, and a target detection result is output; and training the model and carrying out weather adaptive target detection by using the trained model. According to the invention, through dual mechanisms of target space sensing gating and weather condition sensing modulation, the precision of three-dimensional target detection is greatly improved, excellent performance is shown, and the detection robustness is improved in extreme weather such as heavy snow, dense fog, freezing rain and the like.

Sensor positioning device for the creation of thermal maps of cooking equipment. One aspect of the invention relates to a positioning device (1) for sensors (2), in which: the mold (3) has an opening (8) and an internal molding surface (6) where measurement points (7) are located, spaced apart from each other; the positioning device (1) comprises a rigid three-dimensional assembly (9) formed of a main conduit (10) and a plurality of cable paths (11) extending inside the mold (3), each cable path (11) having: a first end (11a) communicating with the main conduit (10), and a second end (11b) open; at least one of the measurement points (7) is located within a distance (D) of the second end (11b) of a cable tray (11), said distance (D) being such that 0.1 ≤ (D) ≤ 8 centimetres, preferably close to 2 centimetres.Figure to be published with the abbreviation: Figure 2.