15 results about "Dust storm" patented technology

The application discloses a spatiotemporal dust storm event AI prediction method fusing satellite remote sensing and meteorological data, and relates to the technical fields of atmospheric pollution prediction and artificial intelligence. In view of the problem that existing methods are difficult to efficiently model multi-source spatiotemporal dust data, the method proposed in the application designs a dust storm prediction model DustMamba based on a multi-task architecture, aiming to jointly predict future PM10 concentration and dust storm occurrence through satellite remote sensing and meteorological data. The DustMamba is composed of a spatiotemporal encoder, a feature aggregation layer and a task-specific layer. The spatiotemporal encoder combines a visual Mamba and a three-dimensional convolutional network, and can efficiently extract spatiotemporal dependence information in multi-source data. The feature aggregation layer adopts a global attention module, and enhances the ability of the model in cross-dimension feature interaction. The task-specific layer is based on an independent two-dimensional convolutional predictor, so as to realize accurate prediction of different dust tasks.

The utility model relates to a kind of soft material package block quick loading and unloading clamping and embracing device.The technical scheme is: between upper main girder and lower main girder, through double vice beam and connecting pipe connection fixed, and in the middle part of double vice beam fixed installation reel, steel wire rope is wound in reel, and the output end of reversible motor is connected fixed with the side of reel;The lower end of lower main girder is fixedly connected with fixed frame, one end of upper main girder and lower main girder is movably connected with first retractable wall frame, the other end is movably connected with second retractable wall frame, and the side formed by first retractable wall frame, second retractable wall frame and upper main girder, double vice beam and lower main girder is used for clamping and embracing soft material package block.Affirmative effect is: the utility model reduces the probability of goods falling from high place to ground, avoids rock wool, glass wool loading and unloading dust storm phenomenon, eliminates the health threat of operating personnel, saves the labor and machinery cost of goods storage and transportation link, and operation is safer.

This invention belongs to the field of computer vision and intelligent environmental perception technology, specifically relating to a method for anomaly detection and intensity estimation of sandstorms based on event cameras. It includes constructing and training an estimation model based on a multi-stream regression framework, and using the trained estimation model to predict sandstorm concentration. The estimation model includes an encoding module, a temporal distillation module, a cross-channel interaction module, and a regression prediction module. The encoding module includes three parallel color spectral encoders for red, blue, and green. This invention effectively overcomes the technical limitations of traditional air quality prediction methods based on RGB images, such as insufficient temporal resolution, limited dynamic information expression capabilities, and insufficient utilization of information from a single data source. It achieves high-precision estimation of air particulate matter concentration and maintains good robustness and adaptability even under complex environmental conditions.

This specification provides a method, computer device, and readable storage medium for identifying dust storms. The method includes: generating an inter-city path attribute table, including the starting city, ending city, distance, and azimuth; identifying cities whose air quality data meets a preset air quality threshold as experiencing dust storm events; using the city where the dust storm event occurred earliest as the starting city, obtaining the distances to adjacent cities based on the path attribute table, estimating the dust movement speed, and calculating the dust arrival time window for adjacent cities based on the distances and dust movement speed; if the time of a dust storm event in an adjacent city falls within the time window, it is determined to be the same dust storm event, and this process is recursively extended to its adjacent cities, and so on, until no more cities experiencing dust storm events are identified; and outputting a dust storm event table. This method solves the problem in existing technologies that cannot identify the changing trends of dust storms.

This invention discloses a method for predicting dust storm trajectories based on an SSA-EDLSTM fusion network, relating to the field of dust storm trajectory prediction. The method includes the following steps: acquiring historical wind field data, topographic elevation data, and historical aerosol optical thickness data of the target area; calculating slope and aspect based on the topographic elevation data, and constructing topographic and wind field interaction features with wind speed and wind direction respectively; inputting the topographic and wind field interaction features and historical wind field data into an SSA-MSED network to predict future wind field data; inputting future wind field data and historical aerosol optical thickness data into an ED-ConvLSTM network to generate future aerosol trajectories; and using a dust storm area detection algorithm to detect dust storm areas, generating dust storm trajectories and a visualization report. This method integrates SSA-MSED and ED-ConvLSTM networks, accurately capturing the influence of topography and the temporal characteristics of dust storms, significantly improving the long-term prediction accuracy and regional detection accuracy of dust storm trajectories.

The invention discloses a method for improving sand and dust numerical forecasting through assimilation-aerosol-cloud-radiation, and the method comprises the steps: building a sand and dust storm forecasting mode, calculating sand and dust optical parameters based on a spherical particle extinction theory, and achieving the bidirectional feedback of sand and dust to weather; a sand and dust aerosol-cloud interaction ice nucleus nucleation mechanism is given, a sand and dust CCN type aerosol homogeneous freezing process is realized, a radiation variable temperature rate is calculated and fed back to a weather mode power process, and bidirectional feedback of weather-driven sand and dust and influence of sand and dust on weather is formed; constructing an ensemble forecasting module, performing time and space related disturbance on a meteorological initial field, a boundary condition and an aerosol initial concentration, and performing ensemble forecasting after a mode is input; and establishing an ensemble assimilation analysis correction module, constructing a background error covariance matrix by utilizing mode ensemble forecasting, disturbing observation at an analysis moment, and assimilating and correcting the initial concentration of the mode aerosol based on a localized ensemble Kalman filtering method to obtain a forecasting result.

This invention discloses a method for identifying dust storms in remote sensing images based on CTFusionNet, belonging to the field of remote sensing image processing. The method includes the following steps: inputting the remote sensing image to be identified into a trained CTFusionNet to obtain the dust storm identification result of the remote sensing image; wherein, CTFusionNet includes a CNN branch, a downsampling layer, an embedding layer, a Transformer branch, an upsampling layer, and a feature overlay fusion layer connected sequentially from input to output; a first classifier connected to the output of the CNN branch; and a second classifier connected to the output of the feature overlay fusion layer. This invention can improve the accuracy of dust storm identification in remote sensing images.

This application relates to methods, apparatus, equipment, and media for identifying dust storm areas based on satellite data, belonging to the field of environmental monitoring technology. The method includes: collecting satellite image data of the target area, and a pixel database including dust, cloud, and clear-sky surface labels; extracting the spectral values ​​of pixels in each channel that spatiotemporally match the pixel data of each label in the satellite image, and calculating spectral feature vectors; constructing a training set using the spectral feature vectors and corresponding labels, training a classification model, calculating the spectral feature vectors of the satellite image, inputting them into the classification model, and outputting preliminary classification results; performing superpixel segmentation processing on the satellite image; identifying clear-sky dust storm areas and cloud-covered areas for each superpixel based on the preliminary classification results; calculating the optical thickness of dust storms under clouds in cloud-covered areas, and combining this with ground monitoring data and meteorological data for fusion judgment to identify dust storm areas under clouds; and predicting the potential probability of dust storm occurrence based on meteorological and surface factors of the target area.

The system that transmits the road information to the driver wirelessly distinguished by a central transmitting device, a traffic signal device in each traffic signal, and a car device in each car, the car device and the traffic signal device receives the data from the central transmitting device. The car device displays and broadcast the warning and the guidance messages, the traffic signal device controls the lamps of the signal and display the remaining times. The transmission is carried out by satellite, it transmits periodically, once it finished the sending it again resends. The data of the device is updated whenever needed, it transmits the status of the traffic signals and their remaining times accompanied by its locations, and the data of the road signs accompanied by its locations, crowding places, accidents, work zones, and the maximum speed for each road or street, the name of the road and its degree of priority, and whether it is double or single way, and if it is single, is it one direction or two directions?, If it is one direction, what is its direction?, does it have intersections or not?, are pedestrians allowed to cross it, and to walk in it?. Device also sends the locations of the important places of the road, such as intersections, traffic signals squares, exits, bridges and tunnels, turns, and sends the locations of the important services located on the street or close to it, such as: ambulance, police, civil defense, fuel station, rest area, and maintenance workshop. Besides, it sends the warning messages with the locations of the thing being warned about and the parking places. It also sends information about the temperature, time, date, rain, fog, wind and dust storms.

This invention discloses a dust collection device, including a collection box with an air duct opening at the top and a lower ventilation pipe at the top, the bottom of which connects to the air duct opening. An upper ventilation pipe is detachably connected to the top of the lower ventilation pipe, and a bearing is mounted on the top of the upper ventilation pipe, on which a collection head is installed. Both the upper and lower ventilation pipes are equipped with fixing cables. A settling chamber is located inside the collection box, with the air duct opening corresponding to the settling chamber. A dust collection mechanism is also located inside the collection box, corresponding to the settling chamber. This invention can collect dust data above PM2.5, filling the gap in existing sand collection equipment that can collect sand but not dust during dust storms. It can also compensate for the shortcomings of TSP (Total Sedimentary Particle Storage) in terms of low dust collection volume and short observation time, thus improving dust collection efficiency.

This invention relates to the technical field of air purification and discloses a pre-filter for high dust storm environments that is resistant to clogging and easy to maintain. The filter includes an installation mechanism comprising a main frame with side slots on both sides and a strip groove at the bottom. A magnetic sealing strip is located within the strip groove, and a positioning docking block is located within the main frame. The filter also includes a composite gradient filter layer mechanism, comprising an inner frame containing a coarse interception and flow guiding layer, a high dust-holding adhesive adsorption layer, and a strength-supporting flow equalization layer, stacked sequentially. The inner frame has a folding handle, a positioning docking groove, a reverse installation groove, and a limiting groove. The advantages of this invention are: by setting up a modular quick-installation structure for the installation mechanism and the composite gradient filter layer mechanism, precise positioning is achieved using the side slots, positioning docking block, and positioning docking groove. Combined with the tight seal between the magnetic sealing strip and the inner frame, the installation efficiency and sealing reliability of the filter are effectively improved.

The present application relates to the field of meteorological remote sensing, and specifically discloses a sandstorm source area susceptibility spatial prediction method based on an sp-GSH-EL model; including sandstorm source point extraction, non-sandstorm source point extraction, obtaining a covariant, defining a response variable, integrated learning model training, and sandstorm source area susceptibility prediction; by combining aerosol optical depth (AOD) threshold method and hourly AOD change rate, the dynamic change of dust source point can be more accurately captured, and the timeliness and accuracy of sandstorm source area monitoring can be improved. At the same time, it has the ability to capture spatial heterogeneity: the sp-GSH-EL model combines different spatial proximities to optimize the description ability of local heterogeneity, global similarity and non-linear relationship, and improve the modeling accuracy of multi-scale spatial data.

This invention relates to a method, apparatus, device, and storage medium for predicting the movement path of dust storms. The method involves: acquiring an aerosol optical thickness dataset and geographic background information of a dust storm event; generating a binarized labeled dust storm image sequence based on the aerosol optical thickness dataset; selecting key features from the geographic background information using a random forest feature importance method; concatenating the dust storm image sequence with the key features to obtain an input dataset; constructing an initial mixture model for predicting the dust storm's movement path; training the initial mixture model using the input dataset to obtain a target mixture model; and using the target mixture model to predict the future movement path of the dust storm. This approach achieves efficient and accurate prediction of dust storm movement paths.

The application discloses a sandstorm identification method based on stationary satellite remote sensing data and ground-based cloud images, and relates to the technical field of meteorological monitoring. The method comprises the following steps: step S10, spatial distortion correction is performed on a stationary satellite cloud image, multi-channel remote sensing data of a specified area is acquired, and standardization processing is performed; step S20, the cloud coverage area and the sandstorm area are identified by using the processed multi-channel satellite remote sensing data; and step S30, according to the identification results of the cloud coverage area and the sandstorm area, the satellite cloud image row and column numbers of the cloud coverage area are acquired, and the sandstorm area under the cloud condition is identified by using the all-sky ground-based cloud image. The application identifies the sandstorm weather of the sandstorm and the sandstorm under the cloud based on the deep learning method, and by fusing the channel data features and the time sequence features, the correlation between the fused features and the sandstorm weather is mined, so that the sandstorm identification precision of the cloud layer and the sand-dust layer boundary area based on the multi-channel satellite remote sensing data is improved.

The invention discloses a device for sealing a spark sample, which is characterized in that a sealing tank body of the device adopts a double-layer design, a main space is used for loading a surface soil sample, and an interlayer space is used for storing a spark surface atmosphere sample and is sealed by electromagnetic valves connected in series; after work is completed, the sealed tank is automatically separated from the fixing frame and the driving mechanism, the detector only needs to carry the sample tank to return, and the return weight is reduced to the maximum extent; the driving mechanism drives the cover body assembly to complete lifting / descending and rotating movement to achieve opening and closing of the sealed tank body. The device for sealing the spark sample has the advantages of being small in size, light in weight, high in reliability, resistant to mechanics, space radiation and surface dust storm, wide in storage and working temperature range and capable of being used under the spark surface environment condition; the device is applied to loading and sealing of soil and atmosphere samples on the surface of Mars in a sampling and packaging subsystem of a Tianzhou No.3 detector.