35 results about "Atmospheric visibility" patented technology

The invention discloses an unmanned aerial vehicle multi-mode mine inspection method and system, a medium and a program product, and the method comprises the steps: dividing an inspection target into a short-range object and a long-range object based on a preset inspection target classification list; constructing a three-dimensional grid inspection path according to the position information of the short-range object and the remote object, and setting a plurality of standby inspection entrance points in a detection area of the short-range object; acquiring real-time environment parameters, wherein the real-time environment parameters comprise illumination intensity, atmospheric visibility, electromagnetic field intensity and wind speed and wind direction; calculating the reachability score of each standby inspection entrance point based on the influence degree score of the real-time environment parameters on the unmanned aerial vehicle, and determining the standby inspection entrance point with the highest reachability score as the current inspection entrance point; and generating an inspection path according to the current inspection entrance point, and controlling the unmanned aerial vehicle to inspect according to the inspection path. According to the method, the integrity of the inspection data is improved, the accuracy of the safety evaluation data obtained based on the inspection data is improved, and the safety of a mine is further improved.

The invention discloses an atmospheric visibility prediction method based on a physical diagnosis model, which performs visibility analysis based on the in-fog physical diagnosis model, and can obtain a visibility prediction result based on various mainstream numerical model products such as GFS, ECMWF and the like. The method has the advantages of being high in calculation speed, small in storage occupation, free of a large number of samples and high in expansibility, and theoretical and technical supports are provided for the development of the refined forecasting and early warning technology of fog.

The invention discloses an atmospheric visibility and photovoltaic power forecasting method and device and a storage medium, and belongs to the field of photoelectric new energy, new-generation information technology and atmospheric environment, and the method comprises the steps: constructing an aerosol cluster model with fractal geometric characteristics based on a diffusion limitation condensation algorithm; calculating fractal dimensions of the aerosol cluster model by using a box counting method; according to the fractal dimension, calculating the optical equivalent radius of the aerosol cluster model of the fractal geometric features; coupling the optical equivalent radius into a mesoscale air quality mode, and calculating to obtain an atmospheric extinction coefficient considering the aerosol process; the atmospheric visibility and photovoltaic power forecast result is calculated by considering the atmospheric extinction coefficient of the aerosol process; according to the method, the physical simulation degree and the forecast simulation precision of the atmospheric aerosol optical characteristics by the atmospheric mode are improved, so that the simulation result of the mesoscale air quality mode on the atmospheric visibility and the photovoltaic power is remarkably improved.

The invention relates to the field of meteorological inversion, and provides a mountainous area surface atmospheric visibility inversion method and system and a computer device, through designing a fog zone visibility model, fog zone visibility is calculated based on an Attention attention mechanism and a BP neural network, identification accuracy of a fog zone is improved, interpolation calculation is carried out through an inverse distance weighted interpolation algorithm, and the accuracy of the fog zone visibility is improved. The method obtains the visibility of the target area, accurately reflects the distribution trend of the atmospheric visibility, further improves the recognition accuracy, carries out the weight calculation according to the meteorological elements and elevation data of the target area, considers the generation and maintenance conditions of the fog area to enhance the prediction of the change of the fog area, also considers the actual landform of the mountainous area, and improves the recognition accuracy. The influence of the complex terrain of the mountainous area is avoided, the weight fusion inversion is finally carried out, the final visibility inversion result is obtained, the inversion result is closer to the actual state of the mountainous area surface, and the accuracy and applicability of the mountainous area surface atmospheric visibility inversion method are improved.

The invention discloses an atmospheric visibility detection method and device based on a multi-modal model, and relates to the technical field of artificial intelligence, and the detection method comprises the steps: obtaining image data and meteorological data; generating a preset question based on the image data and the meteorological data; and inputting a preset question into the target multi-modal model, outputting reply information for the preset question, and determining the atmospheric visibility of the position where the target device is located based on the reply information. According to the invention, the technical problem of low accuracy of atmospheric visibility detection in the prior art is solved.

The invention relates to a marine environment information measuring system and method based on multi-source data fusion. The system is characterized in that a seawater monitoring system is used for monitoring and collecting seawater pressure, temperature, salinity, sound velocity and seawater transparency data; the hydrological monitoring subsystem is used for detecting and collecting flow velocity and flow direction data of seawater; the atmospheric monitoring system is used for monitoring atmospheric visibility data in real time, measuring and recording air temperature, humidity, air pressure, wind speed, wind direction and rainfall data of monitoring points of the monitoring platform in real time, acquiring influences of the monitoring points on sea surface atmospheric meteorological data and acquiring position data of observation points; the data transmission and processing system performs marine surveying and mapping data inspection on the monitoring data through a robust M estimation inspection method, and accurately locates and eliminates abnormal values in the data; and data parameters are corrected to obtain hydrological monitoring data correctly reflecting the measuring points. According to the invention, marine environment monitoring information can be comprehensively presented from different dimensions.

An all-day laser far-field light spot testing device and a use thereof, relating to laser light spot measurement technologies. A photoelectric detection unit (5) detects a far-field laser echo to obtain a time distribution of an intense laser pulse, and a control unit (7) controls an exposure time of a short-wave infrared camera (3) and a detection time of the photoelectric detection unit (5), so as to better capture a pulse light spot. The short-wave infrared camera (3) performs imaging detection on a far-field light spot to obtain spatial distribution information of the light spot, a long-wave infrared camera (4) performs all-day imaging detection on a far-field background, and when the far-field background is superposed with an image of the short-wave infrared camera (3), all-day light spot image imaging can be performed. A data processing unit (6) processes a laser echo pulse waveform of the photoelectric detection unit (5) and the image of the short-wave infrared camera (3), and when necessary, fuses the image of the short-wave infrared camera (3) with the far-field background. By means of comparative analysis on a final image, all-day evaluation of a laser far-field light spot, atmospheric visibility, and target reflectivity can be achieved.

The application discloses an atmospheric visibility prediction method considering cloud droplet concentration, wherein when a physical relation model in fog is constructed, the influence of cloud droplet concentration on visibility under different pollution conditions is additionally considered, and a diagnostic calculation formula of the visibility is derived; after reasonable cloud droplet concentration values are set, the formula is applied to main numerical prediction products such as GFS, ECMWF, CMA-MESO, etc., and is substituted into basic meteorological quantities, so that the diagnostic prediction result of the visibility can be obtained. The method is suitable for the visibility prediction under different pollution conditions, has very fast calculation speed, does not additionally occupy storage, does not need a large number of sample training, and has strong expansibility, thereby providing theoretical and technical support for the development of fine prediction and early warning technology of fog.

The invention discloses a low-altitude target intelligent identification method and system based on large model fusion, and relates to the field of image identification, and the method comprises a capturing module which is used for shooting preset multi-spectral image data of an airplane takeoff and landing low-altitude flight region, and synchronously capturing the environment illumination, atmospheric visibility and fog concentration parameters of the airplane takeoff and landing low-altitude flight region; the preprocessing module is used for receiving the multispectral image and the environmental parameters shot and captured by the capturing module, and forwarding the multispectral image and the environmental parameters to the extraction module after performing registration fusion and adaptive denoising enhancement processing; the method combines multispectral image accurate registration fusion and adaptive denoising enhancement, effectively improves the image quality in a complex environment, deeply excavates and strengthens target key features and improves the feature discrimination by means of double-attention fusion and multi-scale feature level interaction, and improves the image quality through multi-dimensional feature matching and accurate coordinate solution reasoning. And target category rapid identification and space coordinate accurate locking are realized.

This invention discloses a visibility estimation method and apparatus based on binocular vision. The method includes: simultaneously acquiring left and right views using a calibrated binocular camera; inputting the image pairs into a stereo matching deep neural network to obtain a disparity map and converting it into a depth map; inputting the left view and depth map into a dual-branch deep convolutional neural network to extract multi-scale features; fusing RGB features and depth features through a cross-modal feature fusion module; and finally outputting a visibility estimate through a feature aggregation and regression module. The apparatus includes a binocular image acquisition unit, a data processing and visibility estimation unit, and a result output unit. This invention solves the depth ambiguity problem of monocular vision by fusing binocular depth information and image appearance information, achieving high-precision, non-contact visibility surface measurement. It has the advantages of low cost and flexible deployment, and is suitable for visibility monitoring in traffic scenarios such as highways.

AI-Driven UAV Seeding System for Enhanced Atmospheric Visibility

The utility model relates to the technical field of visibility meters, in particular to an atmospheric visibility meter with insect-preventing and bird-repelling functions, which comprises a device body, the device body comprises a support frame, and a detector is arranged on the surface of the support frame; an assembly structure is arranged on the surface of the back of the detector, the assembly structure comprises a rubber pad, and the outer wall of the rubber pad is sleeved with a positioning frame. The positioning frame is connected to the outer surface of the fixing screw in a sleeved mode, then the positioning frame is connected to the outer wall of the supporting frame in a sleeved mode, one end of the limiting screw penetrates through the through groove formed in the positioning frame to be rotationally connected into the threaded groove formed in the supporting frame, and the positioning frame and the supporting frame are connected. And then the nut is rotationally connected to the outer surface of one end of the limiting screw rod, so that the positioning frame is limited, the effect of quickly assembling the supporting frame and the detector is achieved, and the problem that independent maintenance cannot be conducted due to the fact that the supporting frame and the detector cannot be disassembled is solved.

The present application relates to the technical field of atmospheric visibility detection, and more particularly to a self-correcting visibility measurement method based on visual-scattering spectrum dual-mode fusion, dual-mode data synchronous acquisition and preprocessing; visual-based scene classification; scattering spectrum-based visibility inversion; dual-mode dynamic gating fusion distributed model continuous optimization based on cloud-edge collaborative architecture. The present application can improve the accuracy of atmospheric visibility detection through inversion operation, and can also improve the explainability of model behavior and the compliance with physical laws by introducing physical priors; through fusion operation, visual information and scattering spectrum information are deeply and dynamically interacted and fused within the model, fully utilizing the macro scene understanding ability of vision and the microscopic physical detection ability of scattering spectrum to overcome the limitations of single sensor and improve the accuracy of atmospheric visibility detection.

This invention discloses a method and device for monitoring patchy fog based on a visible light image sensor and a point laser, belonging to the field of atmospheric visibility monitoring technology. The device includes a linearly calibrated visible light image sensor, a point laser emitter mounted parallel to the sensor's optical axis, and a synchronization control and data processing unit. The core of the method lies in: synchronously controlling and alternately acquiring image pairs of the laser being on and off, performing differential analysis to eliminate background interference, and obtaining a pure laser atmospheric scattering signal; integrating along the laser spot normal direction to obtain an initial brightness profile curve; based on the fixed spatial pose relationship between the sensor and the laser, mapping the brightness curve in image coordinates to a corrected brightness curve in real spatial distance coordinates through a geometric correction model; calculating the mean and variance of the corrected brightness curve, and calibrating it using standard instruments; and finally simultaneously obtaining the average path visibility value and the patchy fog intensity index. This invention is low-cost, has strong anti-interference capabilities, and can effectively achieve quantitative identification and spatial positioning of patchy fog, making it suitable for large-scale deployment in scenarios such as highways.

The invention discloses a simulation device for a laser atmospheric transmission attenuation effect. The simulation device comprises a rain and fog generation and control module (1), optical glass (2), an optical channel (3), a measuring instrument (4), a leveling device (5), an observation window (6) and an alarm (7), two optical channels (3) are symmetrically arranged on the left side wall and the right side wall of the rain and fog generation and control module (1), and optical glass (2) is arranged at ports of the optical channels (3). An observation window (6) is formed in the front side wall of the rain and fog generation and control module (1), an alarm (7) is arranged at the top, and a leveling assembly (5) is arranged at the bottom; a laser is arranged outside the left optical glass (2), and a measuring instrument (4) is arranged outside the right optical glass (2). The device can simulate different atmospheric visibility environments in a laboratory, can quantitatively adjust the visibility in the device, and is used for researching the transmission attenuation of laser in the atmospheric environments with different visibility.

The application discloses a method for obtaining SO2 concentration image based on calibration coefficient and light dilution effect correction. The application comprises the following steps: collecting sky background and plume signal image by SO2 ultraviolet camera system, and calculating SO2 optical thickness; determining self-calibration coefficient by using sky background image, and converting optical thickness image into concentration image; and performing light dilution correction by combining distance and visibility information measured by distance measuring instrument and atmospheric visibility measuring instrument, so as to realize accurate inversion of SO2 concentration. Compared with the prior art, the application solves the defects that SO2 ultraviolet camera must rely on external equipment calibration and measurement error increases with the increase of detection distance. The application does not need additional calibration equipment, and self-calibration coefficient is combined with light dilution effect correction to obtain accurate SO2 concentration image. The application has the advantages of simple structure, convenient operation, high calibration precision and good real-time performance.

The present invention discloses a method for measuring the seeing of a layered atmosphere based on dual small telescopes, and the steps include: two small telescopes simultaneously point to the same guide star region and keep the optical path conjugate; use a direct imaging sensor to shoot the observation images of the two small telescopes; use the aperture diameter, aperture spacing and each guide star offset of the two telescopes as initial input to obtain the overall seeing; use the variance of the above parameters as initial input to obtain the seeing of each atmospheric height layer, and calculate the ground layer seeing, and then inversely calculate the atmospheric turbulence profile at each height. The two small telescopes used in the present invention have small apertures, small volumes, and light weights, and are easy to carry; a rigid tripod is used to limit the two telescopes, which can effectively avoid the influence of relative vibration errors and guide errors; no wavefront sensor is needed, and many defects such as relatively low resolution, limited dynamic range, and high difficulty in accurate calibration of the Shack-Hartmann wavefront sensor can be effectively eliminated.

A multi-mode mine inspection method, system, medium and program product for unmanned aerial vehicles, in which the inspection targets are divided into short-range objects and long-range objects based on a preset inspection target classification list; a three-dimensional grid inspection path is constructed according to the location information of the short-range objects and the long-range objects, and a number of spare inspection entry points are set in the detection area of ​​the short-range objects; real-time environmental parameters are obtained, and the real-time environmental parameters include light intensity, atmospheric visibility, electromagnetic field intensity, and wind speed and direction; the accessibility score of each spare inspection entry point is calculated based on the degree of influence of the real-time environmental parameters on the unmanned aerial vehicle, and the spare inspection entry point with the highest accessibility score is determined as the current inspection entry point; an inspection path is generated according to the current inspection entry point, and the unmanned aerial vehicle is controlled to perform inspections along the inspection path. This application improves the integrity of the inspection data, improves the accuracy of the safety assessment data obtained based on the inspection data, and thus improves the safety of the mine.

1. The name of the product of this design: Visibility Meter (Mini). 2. Purpose of the product of this design: an instrument for measuring atmospheric visibility distance. 3. The design key point of this appearance design product lies in the three-dimensional image. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The invention relates to the technical field of animal protection, and discloses a wild animal early-warning protection method based on migration data analysis, and the method comprises the following steps: 1, collecting the motion data of a target animal; 2, judging a high-energy intrusion risk and sending a wake-up signal; 3, extracting an atmospheric visibility factor and a rainfall interference factor; step 4, adaptively modulating output parameters according to the atmospheric visibility factor and the rainfall interference factor; 5, early warning intervention: constructing a multi-dimensional biological stress index, and guiding the target animal to migrate; and step 6, calling data to carry out iterative correction on the braking capability coefficient. According to the method, the dynamic trigger radius containing the physical inertia impulse and the motion trend compensation is calculated in real time through the projection component and the acceleration module value of the ground velocity vector in the boundary normal direction, so that the warning range can be dynamically adjusted according to the running speed and the acceleration trend of the animal; and the interception success rate of the sudden intrusion behavior is improved.

The invention relates to the technical field of atmospheric visibility detection, in particular to a self-correcting visibility measurement method based on vision-scattering spectrum bimodal fusion, which comprises the following steps of: synchronously acquiring and preprocessing bimodal data; performing scene classification based on vision; performing visibility inversion based on a scattering spectrum; and bimodal dynamic gating fusion is continuously optimized based on a distributed model of a cloud-edge collaborative architecture. According to the method, the accuracy of atmospheric visibility detection can be improved through inversion operation, and the interpretability of model behaviors and the following of physical laws can be improved by introducing physical priori; visual information and scattering spectrum information are subjected to deep and dynamic interactive fusion in the model through fusion operation, and the macroscopic scene understanding capability of vision and the microscopic physical detection capability of a scattering spectrum are fully utilized, so that the limitation of a single sensor is overcome, and the accuracy of atmospheric visibility detection is improved.

In order to solve the problem of insufficient evaluation ability of existing war game system or method for laser countermeasure against low, slow and small target, the present application provides a kind of laser countermeasure war game system and method.The laser countermeasure war game system is arranged for round war game simulation strategy, which includes: deduction map, which is used to deduce the environment scene of training or actual combat of laser system countermeasure against low, slow and small target, and the deduction map contains atmospheric visibility mark, deduction round record track and atmospheric turbulence record track corresponding to each deduction round; deduction operator, which is used to simulate the strength, equipment and countermeasure state of different countermeasure units in laser system countermeasure against low, slow and small target, including strength unit operator, equipment operator and mark operator, and the strength unit operator contains laser system unit.The present application highlights the particularity of war game in new laser countermeasure style and the difference from traditional direct fire countermeasure deduction through the above-mentioned war game system and corresponding war game method.

The invention relates to the technical field of image processing, in particular to a passive laser emission effect prediction method and device, and the method comprises the steps: obtaining an influence distribution field of turbulence on an image according to an obtained actual far-field image; transforming a light spot far-field distribution image output by the laser according to the influence distribution field to obtain a laser distribution function; and determining the light intensity distribution at any position of the target by using the total laser power and the laser distribution function at the target position. The method for predicting the passive laser emission effect aims at solving the problem that the real-time prediction of the atmospheric visibility condition is poor.

The invention discloses an atmospheric visibility prediction method considering cloud drop number concentration, which comprises the following steps of: when a physical relationship model in fog is constructed, additionally considering the influence of the cloud drop number concentration on visibility under different pollution conditions, and deducing a visibility diagnosis calculation formula; after a reasonable cloud drop number concentration value is set, the formula is applied to mainstream numerical forecasting products such as GFS, ECMWF, CMA-MESO and the like, and a visibility diagnosis forecasting result can be obtained by substituting the basic meteorological quantity into the mainstream numerical forecasting products. The method is suitable for visibility forecasting under different pollution conditions, is high in calculation speed, does not occupy extra storage, does not need a large amount of sample training, is high in expansibility, and provides theoretical and technical support for the development of a fine forecasting and early warning technology of fog.

The invention discloses an atmospheric visibility detection method and device, electronic equipment and a program product, and relates to the technical field of artificial intelligence, and the detection method comprises the steps: collecting meteorological data of meteorological equipment installed on a target communication device and image data of camera equipment; preprocessing the meteorological data and the image data to obtain a processed data set; and inputting the processed data set into a target visibility prediction model to obtain an atmospheric visibility value of the position where the target communication device is located, the target visibility prediction model being obtained by screening a plurality of preset visibility prediction models. According to the invention, the technical problem of low accuracy of atmospheric visibility detection in the prior art is solved.

The invention provides a high-precision visibility measurement method combining a mobile transilluminator and a laser radar, and belongs to the field of atmospheric visibility measurement, and the high-precision visibility measurement method comprises the mobile transilluminator and the laser radar, the mobile transilluminator comprises a laser emitting unit, a light receiving unit, a slide rail unit, a trolley unit and a control and data processing unit; the laser radar comprises a laser emitting unit, a light receiving unit and a signal detection and data acquisition unit; according to the invention, the laser radar is used as a main body of visibility measurement, and high-precision measurement of the mobile transilluminator is used for coupling and correction, so that light pollution caused by the atmospheric environment is inhibited, and the non-uniformity of the atmospheric environment within a certain range is measured.

The invention discloses an unmanned aerial vehicle dynamic target detection method in extreme weather based on deep learning. The method comprises the following steps: S1, collecting a video stream and atmospheric visibility to construct a continuous frame image sequence; s2, inputting a physical perception segmentation network based on SegFormer to generate a space-time attention mask; s3, performing weighted suppression on the original image features by using the mask, and outputting an enhanced feature image set; s4, inputting an improved SwinTransformerV2 model, and extracting target depth time sequence semantic features through space-time dual coding and an environment perception adaptive position coding mechanism; s5, calculating a spatial uncertainty score by using a Bayesian algorithm, calibrating confidence, and screening high-confidence features; and S6, performing multi-frame matching and track correction, and labeling a target bounding box and a motion track in real time. According to the invention, meteorological interference noise is effectively filtered out, the target sensing capability under low visibility is improved, and the robustness and accuracy of detection under a complex environment are ensured.

The invention discloses a transmissivity rapid valuation model based on atmospheric visibility, belongs to intelligent mobile terminal image sharpening processing content in the technical field of machine vision, and particularly relates to an image sharpening processing technology that an intelligent video image terminal arranged on a mobile device is in a moving state in a rain and fog environment. According to one content of the technology, the atmospheric transmissivity of an image sharpening processing model is required to be rapidly estimated, and a sharpening processing flow based on an atmospheric transmissivity rapid estimation model is constructed, so that the sharpening processing model can be applied to a mobile device carrying a video processing terminal in real time. The provided atmospheric transmissivity rapid valuation algorithm model is simple in form, simple in process, low in calculation complexity, good in real-time performance and good in image sharpening processing effect, and is not only suitable for vehicle traffic application scenes, but also suitable for vehicle traffic application scenes. And the method can also be applied to video image sharpening processing scenes of intelligent mobile terminals configured by ships, industrial intelligent trolleys, port loading and unloading vehicles, scenic spot tourist buses, airport passenger transfer vehicles, unmanned aerial vehicles, military mobile equipment and the like in a rain and fog environment.

The present invention relates to a method and system for measuring atmospheric visibility, belonging to the technical field of visibility measurement, and solves the problem of inaccurate visibility measurement accuracy in the prior art. Specifically, it includes: obtaining a first RGB image including the sky background; and performing dark channel extraction on the obtained first RGB image to obtain a first dark channel image; performing atmospheric light value normalization based on the first dark channel image to obtain a second RGB image after atmospheric light value normalization; performing dark image processing on the second RGB image to obtain a second dark channel image; calculating the transmittance of the object in the second dark channel image according to the atmospheric light value and the dark channel value of the second dark channel image; obtaining the visibility value of the second dark channel image based on the transmittance of the object in the second dark channel image and displaying it. It realizes that the calculation process of visibility is not affected by the change of atmospheric light, and improves the measurement accuracy and robustness.

The present invention discloses a method, device and storage medium for atmospheric visibility and photovoltaic power prediction, belonging to the fields of optoelectronic new energy, new generation information technology, and atmospheric environment. The method includes: constructing an aerosol cluster model with fractal geometric characteristics based on the diffusion-limited aggregation algorithm; calculating the fractal dimension of the aerosol cluster model using the box-counting method; calculating the optical equivalent radius of the aerosol cluster model with fractal geometric characteristics according to the fractal dimension; coupling the optical equivalent radius into a mesoscale air quality model to calculate the atmospheric extinction coefficient considering the aerosol process; calculating the atmospheric visibility and photovoltaic power prediction results through the atmospheric extinction coefficient considering the aerosol process; the present invention improves the physical simulation degree and prediction simulation accuracy of the atmospheric model for the optical characteristics of atmospheric aerosols, thereby significantly improving the simulation results of the mesoscale air quality model for atmospheric visibility and photovoltaic power.