1687 results about "Thermal radiation" patented technology

The invention provides an improved YOLOv11s safety helmet wearing detection model and an optimization method thereof, and relates to the technical field of computer vision target detection. According to the improved YOLOv11s safety helmet wearing detection model and the optimization method thereof, the improved YOLOv11s safety helmet wearing detection model comprises the following modules: a multi-modal fusion module, a space-time analysis module, a domain adaptation module, a topological optimization module and a dynamic architecture module; and the multi-modal fusion module is used for realizing feature decoupling by adopting channel separation convolution based on input RGB and near-infrared images, fusing visible light and thermal radiation features through a dynamic weight distribution algorithm, implementing affine transformation alignment on multi-scale features by utilizing a spatial transformation network, and generating a multi-modal feature graph. Through fusion of visible light and near infrared spectrum features and implementation of dynamic weight distribution, complementarity of target texture and thermal radiation features under a complex illumination condition is enhanced, and the problem of feature distortion of single-mode data in a strong backlight or low-illumination scene is solved.

The invention relates to the technical field of EPP (foamed polypropylene) production and manufacturing, and discloses an EPP foaming process parameter optimization method which comprises the following steps: monitoring temperature field and pressure changes in real time, and judging whether a thermodynamic state deviates from a preset window or not; during deviation, constructing a multi-physics field coupling model to evaluate a bubble growth dynamic unbalance risk, and identifying micro-pore non-uniform distribution characteristics through multi-source sensing data fusion and frequency domain analysis; and judging whether the technological parameters are globally coordinated and regulated based on risks and characteristics, analyzing the heat transfer and heat radiation influence of the temperature control unit, quantifying the parameter regulation sensitivity and determining the regulation priority. The system comprises a thermodynamic monitoring module, a dynamic coupling analysis module and the like. According to the invention, real-time monitoring, accurate analysis and intelligent regulation and control of the EPP foaming process are realized, the process stability and the product quality are improved, and the method is suitable for the field of EPP production and manufacturing.

The invention belongs to the technical field of construction crack detection, and particularly discloses a crack detection method and system for expressway construction, and the method comprises the steps: synchronously collecting multiband data through a multispectral thermal imaging sensor, and integrating the surface morphology, material reflection and deep thermal radiation characteristics through a multisource registration fusion technology; the crack identification capability in a complex environment is enhanced, the crack edge continuity and thermal radiation fluctuation characteristics are further analyzed through dynamic correlation, transient interference is accurately stripped, the problem of high false alarm is solved, meanwhile, a scoring model is constructed in combination with geometric and thermodynamic parameters, the damage degree and the expansion trend are quantified, and the accuracy of crack identification is improved. And finally, the crack expansion risk is pre-judged through the dynamic change trend of the thermodynamic parameters, a hierarchical early warning signal is triggered to form a sensing-anti-interference-assessment-decision closed loop chain, the whole process optimization from data fusion and interference suppression to risk assessment and maintenance response is realized, and the accuracy of road crack detection is guaranteed.

The embodiment of the invention provides an intelligent ward digital management method and system based on digital twinning. A ward digital twinborn body is constructed, a sensor array is used for collecting sickbed area heat radiation distribution, operation area airflow mode and medical equipment energy pulse data in real time, and field intensity superposition is carried out on airflow data in combination with a nursing track to form a dynamic airflow model. An energy pulse phase abrupt change point and a thermal radiation attenuation curve are analyzed by establishing an energy interference spectrum, and a negentropy compensation strategy is generated. When a medical equipment start-stop event is detected, topological distortion caused by a space overlapping area of dynamic airflow and a transfer path is predicted, vortex density distribution is reconstructed, a dynamic balance threshold value of an entropy increase gradient and a negentropy shunting rate is calculated based on updated parameters, and finally an intelligent regulation and control instruction set of a thermal stability coefficient and airflow purification efficiency is output. According to the technical scheme provided by the embodiment of the invention, the ward environment regulation and control precision and response speed are remarkably improved.

The invention provides an intelligent control method for a floodlight illumination system, and the method comprises the steps: obtaining an environment surface roughness coefficient, spectral reflection distribution and spatial geometric change data, determining the wall surface material absorptivity and shielding region coordinates, and obtaining environment reflection characteristics and shielding distribution data; analyzing shielding boundary sharpness and shielding angle distribution according to the spatial geometric change and the coordinates of the shielding area, calculating a luminous flux distribution curve of a local dark area, and judging whether the influence range of the dark area exceeds a preset threshold range or not; calculating the illumination coverage integrity according to the updated light field distribution and polarization reflection characteristics, determining the boundary sharpness of a light beam, and obtaining a light field uniformity parameter; and according to the light field uniformity parameter and the shielding thermal radiation effect, calculating and optimizing light field parameters.

The invention relates to the technical field of acetylene cracking furnace production monitoring, and particularly discloses a CO laser detection system based on a thermal radiation background, which is used for solving the problem that an existing monitoring system is difficult to accurately distinguish CO and water vapor signals because thermal radiation and water vapor generated by high temperature in an existing ethylene cracking furnace interfere infrared absorption measurement of CO. Comprising a quantum cascade laser, a pyroelectric detector, a data processing unit and a signal analysis module, a reference light intensity adjusting module utilizes temperature, humidity and pressure data obtained by an environment parameter sensing module in real time to adjust the CO absorption coefficient through an environment correction factor, the reference light intensity is dynamically calculated and corrected according to the reference light intensity, and the signal analysis module analyzes the signal. The data processing unit is used for dynamic correction of CO concentration monitoring; a CO signal is effectively extracted under a thermal radiation background through a quantum cascade laser and a light beam modulation technology, environment correction and real-time monitoring are combined, CO concentration abnormity is accurately recognized, early warning is given out, and the monitoring sensitivity and reliability are improved.

The invention provides a multi-target automatic tracking method and system based on an unmanned intelligent turntable. According to the method, electromagnetic echoes and environment depth data are synchronously collected through a detector, and an observation data set is constructed; separating thermal radiation, surface texture and motion features, establishing a four-dimensional feature space containing space-time coordinates, and identifying a shielding area; dynamically adjusting signal parameters to enhance the characteristics of the shielding area and feeding back an optimization record; calculating an optimal scanning path based on the parameter optimization value, and driving the sensor array to perform multi-angle scanning to generate a weighted data set; in combination with historical trajectory data, a trajectory prediction model is optimized in parallel through distributed calculation, turntable parameter synchronization and decision making are coordinated, and finally efficient reconstruction of a multi-target continuous trajectory in a shielded environment is realized. According to the technical scheme provided by the invention, through multi-dimensional feature fusion and dynamic parameter optimization, reconstruction of a multi-target trajectory in a shielding environment is realized, and the environmental adaptability and tracking efficiency of an unmanned system are improved.

The invention discloses a three-dimensional AI direction sensing method and system based on an unmanned aerial vehicle, and the method comprises the steps: sensing the visible light, thermal radiation, spatial distance and motion state of the surrounding environment of the unmanned aerial vehicle in real time through integrating a plurality of sensors, constructing a comprehensive and accurate three-dimensional environment map, carrying out the semantic segmentation through deep learning, recognizing an object, endowing a semantic tag, and carrying out the recognition of a target object. The environment understanding capability of the unmanned aerial vehicle is improved, dynamic object behaviors are predicted based on a machine learning prediction model, and the adaptability and safety of the unmanned aerial vehicle in a complex environment are enhanced. The self-adaptive decision tree is dynamically constructed, the path planning and flight instruction is generated according to the task demand and the prediction result, the environment change is flexibly coped, the task execution efficiency and success rate are improved, the unmanned aerial vehicle autonomously adjusts the flight, the task is completed according to the planning path, the efficient autonomous flight is realized, and the manual operation burden is reduced.

The invention provides a method and equipment for predicting the heat exchange performance of a buried pipe ground source heat pump thermal camouflage system. The method comprises the steps that S1, a multi-physics field coupling heat exchange mathematical model of a buried pipe heat exchange system is established; s2, based on the multi-physics field coupling heat exchange mathematical model, a control equation and boundary conditions are constructed; s3, on the basis of the control equation and the boundary conditions, a multi-physics field numerical model is constructed, and simulation and calibration are carried out; and S4, based on the calibrated numerical model, designing a simulation test and carrying out main control factor analysis to obtain a prediction effect of the heat exchange performance. By establishing a rock-soil body-fluid multi-physical field coupling model, the interaction mechanism of underground heat conduction, working medium flow and ground surface heat radiation is completely represented, and the hiding efficiency of the thermal camouflage system is remarkably improved.

The invention relates to the technical field of steel rail repair, and provides a steel rail laser additive defect detection method and system.The method comprises the steps that before laser additive repair is conducted on a steel rail damage area, a local area of a steel rail base body is instantly heated, so that an instant hot spot is formed in the corresponding local area; collecting thermal radiation attenuation information of the instantaneous hot spot; according to the thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot is calculated so as to achieve detection of the steel rail damage area; according to the actual heat dissipation rate, repairing process parameters used for laser additive repairing are selected from a pre-stored process parameter combination; and carrying out laser additive repair on the damaged region of the steel rail by adopting the repair process parameters. The method has the effect of improving the quality and reliability of steel rail laser additive repair.

The invention provides a target tracking method, electronic equipment and a readable storage medium. According to the target tracking method provided by the invention, by combining generation and updating of the static template and the dynamic template, the problems of time-varying characteristics and background noise in infrared small target tracking can be effectively solved. Firstly, a generated static target image template is cut by multiple scales, so that the adaptability to different scales of a target is improved; and the generation of the dynamic target image template is combined with the dynamic template of the previous frame and the temporary template of the current frame, and updating is carried out through a fusion strategy, so that the morphological change and the thermal radiation fluctuation of the target can be reflected in time, and the problem of response lag caused by the time-varying characteristic of the target is solved. And finally, inputting the static and dynamic templates into a pre-trained target tracking model for processing, thereby effectively suppressing interference of complex background noise, and accurately positioning the target.

The invention relates to the technical field of power converters, in particular to a power converter real-time fault diagnosis method and system based on edge calculation. According to the method, operation data, including electrical parameters, thermal parameters and the like, of the power converter are obtained firstly, aging and quality are ensured through synchronous filtering, limitation of a traditional single parameter is broken through, tiny abnormity and instantaneous fluctuation can be captured, and redundancy is avoided; according to the equipment structure, edge computing nodes are deployed near a data source, the transmission distance is shortened, delay is reduced, electromagnetic interference is avoided, accuracy is improved, resources with excellent computing power are matched, and local real-time monitoring is supported. Next, an edge computing node lightweight algorithm is used for localization analysis, normal data and abnormal data are quickly distinguished, identification time consumption does not need to be reduced by transmitting to a cloud end, it is ensured that abnormality is found immediately according to misjudgment and sensitivity improvement of a dynamic baseline, and finally, thermal radiation information is obtained in combination with abnormal data, and a fault is accurately positioned by associating a device structure and parameters. And refining to an element level to shorten the troubleshooting time, and analyzing the trend to realize predictive maintenance.

The invention discloses a wild animal target detection method based on improved YOLO11. According to the invention, double-dynamic convolution is designed to improve the feature extraction and nonlinear expression capability of the feature extraction module on the wild animal image so as to flexibly adapt to the feature difference between visible light and infrared images; a multi-scale expansion attention mechanism is introduced to improve the multi-scale target detection precision; unified-IoU loss is introduced to solve the problem of unbalanced quality of a prediction frame; and a DySample dynamic up-sampling operator is introduced, so that the detail recovery capability is improved, and the feature distortion is reduced. The problems that a traditional YOLO feature extraction module cannot effectively process an image shot by a field infrared camera, and an infrared image depends on thermal radiation, is low in contrast, weak in texture, large in environmental thermal noise and large in feature difference with a visible light image and is difficult to adapt are solved, and traditional CIoU loss easily pays attention to and fits a low-quality prediction frame. And a sampling module cannot effectively reconstruct low-resolution infrared image features.

The embodiment of the invention discloses a power transmission line infrared thermal hidden danger and fault identification method and system and a storage medium, and the method comprises the steps: synchronously collecting an infrared thermal image, a visible light image, environment condition data and operation parameters of a typical part in a power transmission line, and carrying out the alignment of the infrared thermal image and the visible light image; obtaining thermal radiation data of typical parts in the aligned infrared thermal image through a target detection model; fusing the thermal radiation data of each typical component with the environmental condition data to generate a first comprehensive feature vector; constructing a thermal radiation intensity and temperature model according to the first comprehensive feature vector, and identifying an infrared thermal hidden danger area of a typical part in the power transmission line through the thermal radiation intensity and temperature model; and fusing the thermal radiation data of each typical component with the operation parameters to generate a second comprehensive feature vector, thereby identifying potential fault points of the typical components in the power transmission line, discovering equipment fault signs in advance, and improving the operation safety and reliability of the power system.

The invention relates to the technical field of fire coal control, and discloses a thermal power plant fly ash floating black online detection control method and system, and the method comprises the steps: 1, employing microwave, infrared and laser sensors for cooperative work, detecting carbon dielectric characteristics through microwave dust interference resistance, identifying thermal radiation difference through infrared, and analyzing particle distribution through laser; 2, on the basis of the detection requirements in the step 1, triple protection of air curtain barrier, ultrasonic cleaning and hydrophobic coating is designed, dust condensation is blocked, and it is ensured that the light transmittance of the sensor is larger than 90%; the invention provides a multi-mode sensing fusion-anti-interference current stabilization-closed loop optimization full-link solution for the industrial problem of signal distortion caused by optical window dew formation and dust deposition, airflow disturbance and environmental interference in fly ash floating black online detection. The light transmittance of the optical window is greater than 93% by combining triple protection of air curtain barrier, ultrasonic cavitation stripping and nano hydrophobic coating.

The invention provides an unmanned aerial vehicle fire monitor fire source positioning system based on infrared thermal imaging, and the system comprises a fire scene situation collection module which obtains thermal image data and high-precision point cloud data; the fire diffusion model building module is used for generating a radiation intensity distribution diagram; the thermal image processing module is used for generating a structured fire source risk feature image; the LSTM time sequence model processing module is used for generating a smooth diffusion thermodynamic diagram to predict the spreading direction and speed; the combat map generation module is used for realizing data visualization; and the unmanned aerial vehicle flight path planning module realizes comprehensive coverage of a fire monitor striking path. Aiming at the problem that the prior art depends on static fire source data and is difficult to capture time-space dynamic evolution of a fire behavior, the method comprises the following steps: constructing a multi-dimensional fire behavior diffusion model, and fusing fire scene air flow vector projection analysis, thermal radiation background concentration dynamic superposition and LSTM time sequence modeling modes; accurate prediction of the diffusion path of the fire from the low-risk area to the high-risk area is realized, and instant support is provided for fire extinguishing action.

The invention discloses a multi-modal imaging method and system based on acoustic-thermal coupling, and relates to the field of artificial intelligence, and the method comprises the steps: firstly obtaining thermal radiation data and ultrasonic reflection data of a target equipment region, and obtaining thermal radiation embedded features and ultrasonic embedded features through feature representation learning; performing multi-stage compensation on the thermal radiation embedding characteristic to generate a thermal field compensation reference characteristic of each stage; synchronously carrying out equal-stage multi-stage compensation on the ultrasonic embedded features, coupling the ultrasonic compensation result of the previous stage with the thermal field reference features of the corresponding stage between every two continuous stages of compensation, and combining the ultrasonic embedded features and coupling output in the later stage of compensation; and finally, performing imaging by using the acoustic-thermal coupling characteristics after multi-stage compensation to obtain an acoustic-thermal coupling imaging result fusing the thermal distribution characteristics of the target equipment region and the ultrasonic reflection spectrum characteristics. According to the method, deep fusion of acoustic and thermal information is realized through multi-stage feature compensation and dynamic cross-modal coupling, and the comprehensiveness and accuracy of equipment area detection are improved.

The invention relates to the technical field of multi-sensor identification, in particular to a coal gangue detection and classification method and system based on multi-sensor fusion discrimination, and the method comprises the following steps: obtaining visible light and infrared images, calculating brightness and intensity judgment feature conditions, executing edge detection to extract gray segments, and fusing textures and a thermal field to generate a vector set. And performing clustering analysis to finish classification judgment, and outputting a coal gangue detection classification result. According to the method, a precise trigger mechanism is established through brightness and thermal radiation double-feature screening, boundary recognition sensitivity is enhanced through gray abrupt change point division, salient region extraction capacity is enhanced through weighted fusion of texture energy and gray gradient, and a cross-modal consistency feature group is constructed through combination of two-dimensional vector construction and similarity screening. The recognition expression integrity is improved, static threshold classification is replaced by vector distribution clustering, accurate mapping and classification decision making of material attributes in a complex scene are achieved, and the stability and the recognition rate of a coal gangue detection result are guaranteed.

The invention relates to the technical field of temperature control, in particular to a nanocrystalline glass annealing treatment temperature dynamic monitoring control method and system, and the method specifically comprises the steps: capturing an unsteady thermal radiation signal in a glass internal microcrystalline phase change process in real time, and synchronously obtaining three-dimensional residual stress distribution data; dividing the annealing process into gradient crystallization control units according to the time-temperature transition characteristic of the glass; constructing a crystal phase evolution model, and dynamically analyzing the coupling relationship between the microcrystal nucleation rate and the residual stress of each gradient crystallization control unit; and a multi-target particle swarm optimization algorithm is adopted, and temperature field gradient distribution is corrected in real time in combination with grain boundary migration kinetic parameters. According to the invention, the problem of residual stress accumulation and grain size mismatch in a nanocrystalline glass annealing process in the prior art is solved.

The invention discloses a forestry fireproof early warning method and system based on the Internet of Things, and relates to the technical field of forestry monitoring, prevention and control, a heterogeneous sensing network is constructed through millimeter wave radar and multispectral imaging, and omnibearing monitoring in a complex environment is realized by combining terrain shielding coefficient Dmxs and signal coverage intensity Xgql analysis. The thermal radiation intensity Rsqd, the combustible drying index Gzzs and the airflow disturbance coefficient Qlys are fused to improve the hidden fire source identification precision; a LoRa relay and a Mesh network are adopted to ensure communication stability of a weak signal area, data transmission is optimized through edge calculation, and high-risk area resources are preferentially scheduled based on hierarchical response of a joint early warning index Lyzb; the risk assessment module calculates a fire danger index Hxzs in real time to predict fire spreading, the intelligent decision-making module comprehensively assesses hidden fire source probability Yhgl and a positioning error Wcsp to generate an early warning strategy, and the emergency linkage module automatically executes hierarchical response to form an intelligent monitoring-early warning-disposal closed-loop management system.

The invention discloses infrared welding forming equipment for a plastic inner container of a hydrogen storage cylinder. The infrared welding forming equipment is characterized by comprising a base, a first translation assembly, a second translation assembly, a first welding press-fit air cylinder, a second welding press-fit air cylinder, a first clamping assembly, a second clamping assembly, an infrared heating assembly, an upper side panel and a supporting roller assembly. According to the equipment disclosed by the invention, the circumferential array infrared lamp tubes can dynamically rotate during heating, and the required stroke for placing and withdrawing the lamp tubes is shortened, so that the heating uniformity of the end surface during welding can be improved, and the switching time of heating and pressure applying can be shortened; due to the fact that the stroke of the opening and closing control air cylinder can be adjusted, the radial heat source irradiation area of the infrared lamp tube is adjusted, welding of liners of different sizes or with size deviation can be rapidly adapted, the equipment cost is reduced, and the production efficiency is improved. Due to the elasticity of the clamp spring in the clamping assembly, the clamp spring rubber pad is in close contact with the plastic inner container, stable clamping of the plastic inner container can be achieved, welding pressure is evenly transmitted to the welding end face, and the welding quality is improved.

The invention provides a forest disaster detection method and device, and belongs to the field of forest disaster monitoring, and the method comprises the steps: collecting an infrared image, a stereoscopic vision image and positioning data of a target forest region in real time; an ASSA module is introduced in the feature extraction stage of the YOLOv11, and an infrared image is input into the improved YOLOv11 for flame target recognition; recognizing the stereoscopic vision image through a smoke and fire recognition algorithm, and detecting flame and smoke targets; determining a fire detection result by combining the identification results of the flame target and the smoke target; under the condition that the fire disaster is determined to occur, an HITNet algorithm is adopted to carry out ignition point positioning through a stereoscopic vision image, and the geographic coordinates of a fire disaster point are determined based on positioning data; and sending alarm information based on the fire point geographic coordinates. Therefore, the capability of extracting the flame heat radiation characteristics of the tiny fire points is effectively enhanced, and the detection result of the forest fire is improved.

The invention relates to the technical field of recycled asphalt mixture recovery, in particular to a mixing uniformity monitoring method adaptive to a recycled asphalt mixture, which comprises the following steps: S101, performing time-space fusion on infrared thermal radiation field dynamic capture and microwave dielectric property synchronous monitoring bimodal sensing to jointly perform mixing defect alarm; s102, based on the dynamic sequence of the infrared thermal radiation field, judging the particle motion consistency through the standard deviation of the motion direction angle, integrating the infrared temperature field and microwave dielectric data, constructing a three-dimensional feature vector, comprehensively evaluating the uniformity through a weighting function, judging defects according to the maximum contribution term, and generating an optimization instruction; and S103, setting a grading standard based on the multi-modal features, and feeding back and adjusting the process according to a grading result. According to the invention, infrared thermal radiation and microwave dielectric characteristics are combined, temperature uniformity and material component distribution are evaluated synchronously, and the problem of monitoring that the thermal uniformity of the recycled asphalt is not equal to the component uniformity is solved.

The invention discloses an intelligent security and protection video monitoring system for preventing animal attack behaviors, and relates to the technical field of intelligent security and protection, and the system comprises the steps: synchronously collecting a thermal radiation image sequence and an RGB image sequence, and generating a cross-modal video stream data packet; performing multispectral feature extraction on the cross-modal video stream data packet to generate a visible light enhancement feature and an infrared specific feature; cross-modal shared features are extracted from the visible light enhancement features and the infrared specific features through a shared weight convolution layer, and a mixed feature tensor is formed through splicing; horizontally dividing the mixed feature tensor into equal-width regions, calculating region pseudo anchor points, generating a multi-scale candidate frame by improving a YOLOv7 detection head, guiding similar aggregation and heterogeneous rejection loss by the pseudo anchor points, and outputting a high-confidence candidate frame set; and converting bounding box parameters of each candidate box in the high-confidence candidate box set into a state vector. According to the method, the alignment of the time stamps of the cross-modal data is ensured by dynamically adjusting the primary and secondary data streams.

The invention relates to the technical field of fusion devices, and discloses a flange structure of a cold shield sector of a nuclear fusion device, the cold shield device and the nuclear fusion device, and the flange structure of the cold shield sector of the nuclear fusion device comprises a first panel; the second panel and the first panel are arranged at an interval; the flanging assembly is arranged between the first panel and the second panel and comprises a first flanging and a second flanging, the first flanging is connected with the first panel, the second flanging comprises a main body part and a flat plate part which are connected, the main body part is connected with the second panel, and the flat plate part is arranged at the ends, away from the second panel, of the main body part and the first flanging; the surface, opposite to the second panel, of the flat plate part is a polished surface; the connecting piece is connected with the first flange and the second flange in a fastening manner; and the first insulating part is arranged between the first flange and the second flange in an insulating manner. According to the flange structure of the cold shield sector of the nuclear fusion device, the heat shielding effect can be improved, and the heat radiation influence on low-temperature components is reduced.

The invention belongs to the technical field of aerospace engineering, and discloses a flexible radiator which comprises a radiation assembly, the radiation assembly comprises a plurality of radiation plates which are rotationally connected in sequence, each radiation plate comprises a liquid cooling pipe set and a radiation film arranged on the liquid cooling pipe set, and cooling liquid circulates in the liquid cooling pipe set. The material density is low, the structural mass is effectively reduced, a plurality of radiant panels are rotationally connected in sequence, the radiant panels are in a folded state during emission, then a radiator with enough radiation area can be emitted under the condition that the size of a spacecraft is limited, and the heat dissipation requirement of high-power electronic equipment is met.

The invention discloses a tunnel structure full life cycle damage detection and safety evaluation method, and belongs to the technical field of damage detection and safety evaluation. The method comprises the following steps: completing installation configuration of a mobile detection platform along the axial direction of a tunnel; generating a moving track and a detection point location distribution scheme of the mobile detection platform; controlling the mobile detection platform to sequentially move to each detection section position according to the detection path, and synchronously starting each detection module to perform continuous data acquisition in the moving process; generating a tunnel three-dimensional mathematical model, a lining structure thickness distribution diagram, a heat radiation anomaly distribution diagram and a crack damage distribution diagram; equally dividing the tunnel three-dimensional model into N detection segments according to a preset interval, and counting the lining thickness mean value, the number of heat radiation abnormal points, the crack length density and the damage level of each segment as safety evaluation indexes; statistical analysis and trend judgment are conducted on the safety indexes of all the segments, abnormal segments exceeding a safety threshold value are recognized, and the risk level of the abnormal segments is determined.

The invention discloses an unmanned aerial vehicle and bird target identification method and system based on multiple modes, and belongs to the technical field of computer vision and target identification. The method comprises the steps of collecting an RGB image, an infrared image and a continuous frame image of a monitoring area, extracting visual features, thermal radiation features and motion features after preprocessing, fusing multi-modal features by adopting an adaptive weight fusion strategy, detecting a potential target through a multi-scale feature fusion detection head, and obtaining a target detection result. The multi-mode classification module judges the target category and triggers early warning; the system comprises a data acquisition module, a preprocessing module, a feature extraction and identification module, a decision and early warning module and a database management module. Through multi-modal fusion, a self-adaptive weight strategy, multi-scale detection and multi-branch classification, the method can effectively overcome the limitation of a single modal, improves the recognition accuracy, the small target detection capability and the environmental adaptability in a complex environment, and meets the requirements of real-time recognition and early warning.

The invention belongs to the technical field of nano porous materials, discloses a high-strength and low-thermal-conductivity SiC-TiO2 nanofiber aerogel and a preparation method thereof, and aims to solve the problems of insufficient structural stability, shear strength and high-temperature thermal conductivity of traditional ceramic aerogel. TiO2 nanorods are introduced onto a SiC nanofiber membrane by adopting an in-situ growth technology, and the high-strength and low-thermal-conductivity SiC-TiO2 nanofiber aerogel is prepared. And constructing the SiC nano composite fiber membrane into the layered porous ceramic nanofiber aerogel with a multilevel structure by combining a layer-by-layer stacking method with a directional freezing casting technology. TiO2 nanorods growing on the surface of the SiC fiber in situ serve as a secondary structure, so that the overall mechanical performance of the material is enhanced; the TiO2 nanorods have specific high infrared light reflection and scattering capabilities, so that the transmittance of the aerogel material to radiation is reduced, and the thermal radiation conduction in a high-temperature environment is effectively reduced. In addition, a silica sol binder is introduced between layers of the aerogel multilevel structure, stable bonding points are formed between fibers after calcination, and the mechanical stability is improved.

The invention discloses an intelligent laser testing method, which relates to the field of laser testing, and comprises the following steps: judging whether a laser has a fault or not by monitoring the fluctuation amplitude of optical power at the initial stage of starting a to-be-tested laser to emit a light beam; after the laser is not judged to have a fault, the influence of environment heat radiation or aerosol particles on the light beam is positioned by collecting temperature gradient distribution data of a light beam propagation path and combining with air particulate matter concentration data; and obtaining a light beam drift direction, a drift speed and energy uniformity on a light beam propagation path based on the light spot image, determining an abnormal position according to changes of the light beam drift direction, the drift speed and the energy uniformity, and associating the abnormal position with the temperature gradient and the particulate matter concentration in real time. The method effectively distinguishes the fault of the laser from the environmental interference, accurately locates the abnormal position on the beam propagation path, and determines the main environmental interference factors causing the dynamic quality degradation of the beam, thereby providing an accurate basis for the performance evaluation of the laser and the optimization of the application environment.