18 results about "Precipitation types" patented technology

The invention relates to the technical field of fan blade deicing, and discloses an intelligent temperature control type fan blade electric heating deicing control system and method, and the system comprises a meteorological sensing module which is used for collecting the environment temperature, humidity, wind speed and rainfall type; the blade state monitoring module is used for acquiring blade surface temperature distribution and ice layer thickness data; the dynamic decision-making module is used for generating a partition heating instruction based on the data of the weather sensing module and the blade state monitoring module; the temperature control execution module is used for converting the instruction into a gradient signal; the heating array module is used for executing electric heating deicing operation in the blade surface subareas; and the energy coordination module is used for dynamically constraining the total power of the system. The meteorological sensing module and the blade state monitoring module are integrated through the system, real-time collection and fusion of multi-source data of blade surrounding environment parameters and the thickness of an ice layer are achieved through the design, comprehensiveness and accuracy of icing monitoring are improved, a reliable basis is provided for dynamic decision making, and therefore the response capacity and early warning precision of the system to icing risks are improved.

The invention relates to a ground precipitation intensity estimation method based on phased array radar echoes and geographic factors, which belongs to the field of radio, and comprises the following steps of: mapping and interpolating polar coordinate multivariable radar echoes and a three-dimensional wind field to a unified three-dimensional grid to form a consistent spatio-temporal data basis; then, various rainfall type areas are automatically divided based on local density clustering, a time lag field is constructed according to rainfall types, and adaptive time alignment of radar echoes and ground station observation is achieved; a three-dimensional wind field and a raindrop terminal end velocity are introduced to calculate rainfall falling drift, the position of a grid point matched with a ground station point space is corrected, and accurate space matching of radar echoes and ground station observation is completed; a terrain uplift index is constructed by combining a stratum wind direction, a DEM (Digital Elevation Model), a gradient, a slope direction and a slope position type, and a radar nonlinear precipitation potential vector and a terrain feature are jointly modeled through a physical constraint coupling model, so that quantitative estimation of the ground precipitation intensity is realized, and the reliability and applicability of ground precipitation estimation in a complex environment are improved.

The invention relates to the technical field of meteorological monitoring, and discloses a rainfall early warning method and system based on a weather radar, and the method comprises the steps: obtaining weather radar body sweeping arrival base data and rainfall station observation data, carrying out the alignment, carrying out the meshing of the radar base data, and obtaining the grid echo data; constructing a quasi-vertical profile to determine the height range and uncertainty of the melting layer, and carrying out weighted bright band correction on echoes in the melting layer to obtain corrected echo data; determining rainfall type partitions and performing inversion to obtain a radar rainfall intensity field; according to the rainfall station data and the radar rainfall intensity field, station residual data is obtained, a space deviation field is obtained, and finally a calibration rainfall intensity field is obtained; determining an accumulated precipitation field of each member according to the calibrated rainfall field; and obtaining an over-threshold probability published by early warning according to the accumulated precipitation field of each member, and outputting precipitation early warning information when a probability threshold is continuously met. According to the invention, the rainfall intensity overestimation and false alarm jitter are reduced, and the accuracy and stability of short temporary rainfall early warning are improved.

The method and device for heavy rain early warning, the electronic device and the medium are provided, in at least one embodiment of the present disclosure, by obtaining the combined reflectivity data and the basic reflectivity data of the networking weather radar covering the target area, the precipitation type of each grid point in the target area can be determined based on the combined reflectivity data and the basic reflectivity data;Further, based on the precipitation type of each grid point in the target area, the extrapolation vector field is determined, and the combined reflectivity prediction data and the basic reflectivity prediction data are obtained based on the extrapolation vector field;Thus, based on the ground constraint condition and the combined reflectivity prediction data, the basic reflectivity prediction data is corrected, and heavy rain early warning is carried out based on the corrected reflectivity prediction data, which is suitable for the field of heavy rain short-term early warning.

The application relates to the technical field of vehicles and discloses a wiper control method and device and a vehicle. The wiper control method comprises the following steps: acquiring point cloud data in front of a driving direction of the vehicle, and acquiring a driving intention of a driver; based on the point cloud data, a real-time precipitation type in front of the driving direction of the vehicle is recognized; based on the real-time precipitation type and the driving intention, a wiper control instruction is generated; and according to the control instruction, the wiper performs corresponding wiping actions. The application can enhance the active safety performance of the vehicle and provide more reliable visual field protection for the driver.

The present application relates to the technical field of vehicles and discloses a wiper control method, a wiper control device and a vehicle.The wiper control method comprises the following steps: acquiring visual form features and impact pulse features of precipitation particles in a front windshield area of a vehicle, wherein the visual form features are used to represent the overall form and distribution law of the precipitation particles in the spatial and motion levels, and the impact pulse features are used to reflect the vibration change trend caused by the impact of the precipitation particles on the front windshield; determining a precipitation type based on the visual form features, the impact pulse features and real-time temperature features, wherein the real-time temperature features are used to describe the temperature influence of a driving environment on the front windshield area; and controlling the vehicle to execute a corresponding wiper control strategy based on the precipitation type.The present application can reduce the situation of over-frequent or untimely wiping, improve the visual clarity of the front windshield in bad weather, and thus enhance the driving safety and driving comfort.

The invention relates to the technical field of raindrop spectrum inversion, in particular to a method for inverting an aerial raindrop spectrum by using characteristic parameters of a dual-polarization radar, and the method comprises the steps of data collection, quality control, calculation and fusion. Modeling and counting; the statistics specifically comprises the statistics of a radar and rainfall type relationship and the statistics of a typing and raindrop spectrum type fitting relationship; and the business application process comprises a four-dimensional raindrop spectrum product and a rainfall estimation product. The research of the invention can bring significant improvements in three aspects: in the aspect of monitoring capability, a radar secondary product system can be enriched, and visual visualization of spatial precipitation particle distribution characteristics is realized; in the aspect of early warning and forecasting, the heavy rainfall falling area can be researched and judged in advance through the distribution characteristics of particles in the air, and the disastrous weather early warning timeliness is effectively prolonged; in the aspect of artificial influence weather, refined rainfall micro-physical structure information is provided, and reliable technical support is provided for operation condition identification and effect evaluation.

The present application relates to the method for estimating ground precipitation intensity based on phased array radar echo and geographic factors, belongs to the field of radio, first polar coordinate multivariate radar echo is mapped with three-dimensional wind field and is interpolated to unified three-dimensional grid, forms consistent space-time data foundation, then based on local density clustering, a variety of rainfall type regions are automatically divided, and time lag field is constructed according to precipitation type, adaptive time alignment of radar echo and ground station observation is realized, three-dimensional wind field and raindrop terminal speed are introduced to calculate precipitation falling drift, the position of the grid point matched with the ground station is corrected, and accurate spatial matching of radar echo and ground station observation is completed, terrain lifting index is constructed by fusing into ground layer wind direction, DEM, slope, aspect and slope position type, radar nonlinear precipitation potential vector and terrain characteristics are coupled through physical constraint coupling model, quantitative estimation of ground precipitation intensity is realized, and the reliability and applicability of ground precipitation estimation under complex environment are improved.

The present invention provides a fully automatic precipitation measurement system using microwave radar, comprising a microwave radar transceiver module for real-time monitoring of precipitation echo signals; an echo high-gain amplification module that amplifies the precipitation echo signals, performs analog-to-digital conversion, and transmits the signals to a precipitation analysis and statistics module; an automatic gain control module connected to the precipitation analysis and statistics module and the echo high-gain amplification module; a temperature and humidity monitoring module for monitoring ambient temperature and humidity and the real-time temperature of a circuit board and transmitting the results to a precipitation subsystem and module; and a precipitation analysis and statistics module that sends real-time energy monitoring values ​​to the automatic gain control module and performs energy detection and Doppler analysis on the amplified echo signals after automatic gain control. The former is used to calibrate precipitation intensity, and the latter is used to detect precipitation type. The present invention is no longer affected by vertical wind speed interference, eliminates the measurement instability of conventional Doppler precipitation radars, and improves measurement accuracy.

This application relates to the field of weather radar precipitation estimation, and more particularly to a quantitative precipitation estimation method, device, and medium based on dual-polarization radar. The method comprises: classifying raindrop spectrum data according to preset climatological precipitation types to obtain multiple raindrop spectrum datasets corresponding to different climatological precipitation types; inverting and fitting each raindrop spectrum dataset to obtain a dual-polarization radar precipitation relationship corresponding to each climatological precipitation type; and estimating precipitation in the target area based on each precipitation relationship and radar data. This application improves the accuracy of quantitative precipitation estimation based on radar, enhances meteorological monitoring and early warning capabilities, and reduces losses.

The application provides a moving obstacle adaptive warning method in driving process and a vehicle. The method can determine the current precipitation intensity and precipitation type according to precipitation scene data; the cut-off frequency and the threshold value of filtering are determined according to the precipitation intensity and the precipitation type, wherein the cut-off frequency is negatively related to the single-particle precipitation diameter corresponding to the precipitation intensity and the precipitation type, the threshold value is negatively related to the single-particle precipitation diameter corresponding to the precipitation type, the threshold value is positively related to the precipitation intensity, and the echo data is filtered according to the cut-off frequency and the threshold value; whether there is a moving obstacle in front is identified according to the filtered echo data, the reliability of the distance between the moving obstacle and the vehicle is high if there is a moving obstacle, and the vehicle body warning module is controlled to perform a light warning operation under the condition that the distance between the moving obstacle and the vehicle is less than a set distance threshold, so that the reliability of the warning is high and the probability of false alarm is greatly reduced.

The present application relates to a kind of radioactive aerosol plume wet precipitation calculation method of rainfall weather condition, solve the problem that existing simulation does not have the wet precipitation diffusion transport influence calculation method of radioactive plume under the condition of complex flow field large scale considering the influence of precipitation situation;Including 1: based on (x0, y0, z0), establish two-dimensional coordinate system, determine the region to be calculated and grid division to it;2: based on precipitation type, precipitation intensity calculation wet precipitation removal coefficient Λ;3: based on Λ, calculate and record after time Δt, the ground deposition amount s1 of plume and after time Δt, the center position (x1, y1, z1) of plume, space distribution σ1;4: based on (x1,y1), σ1 and s1 calculate the plume particle deposition amount p1 (x,y) at any point (x,y) position in the region to be calculated;5: repeat step 2-step 4, until aerosol plume completely settles ground or escapes the boundary of the region to be calculated;6: after calculation, output record ground deposition result on grid point.

The invention discloses a double-weighing precipitation measurement sensor and a precipitation measurement method, wherein the measurement sensor comprises a base, a bracket, a water collection hopper, an automatic flow guide mechanism, an automatic weighing module, an automatic drainage module and a controller, and the bracket is arranged on the base; a liquid inlet of the automatic flow guide mechanism corresponds to a liquid outlet of the water collecting hopper; the number of the automatic weighing modules is multiple, the multiple automatic weighing modules are all located below the automatic flow guide mechanism, the automatic flow guide mechanism is provided with multiple liquid distribution openings, the liquid distribution openings and liquid inlets of the automatic weighing modules are arranged in a one-to-one correspondence mode, and each automatic weighing module is provided with one automatic drainage module. The method has the technical effects that the rainfall amount is converted by directly and continuously measuring the collected rainfall mass, the measured mass is the real cumulant of rainfall, and meanwhile, the rainfall intensity at an instant time period or a certain time period can be calculated; the method is not influenced by rainfall intensity and rainfall type changes, and a foundation is provided for high-precision and full-type rainfall measurement.

The invention discloses a complex rainfall type accurate identification method, system and device and a storage medium, and relates to the technical field of meteorological detection. The method comprises the following steps: acquiring an original data set; the data set comprises a crowdsourcing data set and an ERA5 reanalysis data set; a PI-SwinT model is constructed; the PI-SwinT model is composed of a physical information neural network constraint and a Swinin-Transform framework; the physical information neural network constraints comprise static balance constraints, barometric gradient constraints and temperature vertical declining rate constraints; and training the PI-SwinT model by using the original data set, and performing complex rainfall type identification on to-be-detected data by using the trained PI-SwinT model. According to the method, identification difficulty caused by rainfall phase state complexity and limitation of a traditional identification method can be solved, and the accuracy of rainfall type identification is further improved.

The invention discloses a flow quality scoring and screening method for a data management platform, relates to the technical field of flow quality, is used for solving the problems that the flow resource utilization efficiency is reduced and the flow resource waste rate is increased, and aims to improve the flow quality through setting flow monitoring time for newly published to-be-detected content, collecting recommended exposure data and calculating a recommended display coefficient. Monitoring flow diffusion data and carrying out ripple layering processing to obtain a reference propagation layer coefficient, calculating a flow quality level in combination with a recommendation display coefficient, correcting a default page view based on the flow quality level, monitoring comment data in real time in a flow distribution process, and analyzing the depth of the comment level, meanwhile, historical knowledge data is called to evaluate novel features of topics, whether the content is marked as high-quality precipitation content or not is comprehensively judged, conversion judgment from surface layer clicking to high-quality content precipitation is achieved, short-term virtual high flow and natural propagation precipitation type flow caused by algorithm centralized recommendation are distinguished, and the flow resource utilization efficiency is improved.

The invention discloses a radar echo intelligent extrapolation and evolution identification system for short-term and imminent forecasting in the technical field of meteorological monitoring. The radar echo intelligent extrapolation and evolution identification system comprises a data acquisition module used for generating an echo image covering the whole domain; the feature extraction module is used for extracting space-time evolution features in the echo image; the terrain power correction module is used for generating a terrain weight factor; the urban heat island correction module is used for generating a heat island weight factor; the prediction module is used for identifying potential severe convection weather and predicting the influence range and duration of the weather; the dynamic data module is used for feeding back the updated data to the prediction module; the optimization module is used for adjusting algorithm parameters for different rainfall types; the early warning module is used for generating early warning information. According to the invention, environmental factors are dynamically coupled through the terrain and heat island correction module, the influence of complex terrain retardation and urban heat island disturbance on radar echoes is solved, the physical consistency and intensity evolution precision of an extrapolation path are improved, and adaptive correction of sudden weather is realized in combination with dynamic data assimilation.

The invention relates to the technical field of data acquisition, in particular to a rainfall data intelligent acquisition and processing method based on a phased array radar. The method comprises the steps of obtaining a reliability coefficient of precipitation collection of a target precipitation type by each precipitation collection method and an adaptation coefficient of each precipitation collection method for a collected area, and obtaining a confidence factor of collection of the collected area by each precipitation collection method according to the reliability coefficient and the adaptation coefficient, carrying out weighted fusion on the collected precipitation amount corresponding to each precipitation amount collection method by using a confidence factor to obtain a target precipitation amount of the collected area; and the results acquired by all the precipitation acquisition methods are fused based on the confidence factors of acquisition of the acquired areas by all the precipitation acquisition methods, so that the accuracy and credibility of precipitation acquisition of the acquired areas can be improved.

The invention discloses a rainfall analysis method and system based on micro-rain radar data, and belongs to the field of meteorological radar signal processing, and the method comprises the steps: carrying out the vertical detection of a target airspace through a micro-rain radar, and obtaining a radar echo signal; performing noise filtering on the original Doppler power spectrum density matrix to obtain a cleaned observation Doppler power spectrum; performing feature extraction on the observation Doppler power spectrum by using a pre-trained neural network model, and outputting prior probability distribution about rainfall types; constructing and solving a precipitation state unified inversion model to obtain a globally optimal unified precipitation state vector; and based on the unified rainfall state vector, calculating rainfall particle number density distribution of each height layer, and carrying out integration to obtain an instantaneous rainfall rate of each height layer. According to the method, the problem of attenuation correction error accumulation in a traditional method is solved, and accurate early warning of rainfall dynamic risks is realized.