6 results about "Dust storm" patented technology

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 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.

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.