46 results about "Cloud droplet" patented technology

The present application relates to the technical field of aviation meteorological support, and provides a meteorological display and alarm method, system, device and medium for aircraft navigation, which comprises receiving an aircraft route plan and collecting numerical weather forecasts of each place at the takeoff time of the aircraft; extracting wind speed, temperature, relative humidity, liquid water content and cloud droplet particle number density, and calculating the horizontal visibility, aircraft icing index, total cloud cover and aircraft turbulence index at the forecast time through adaptive attenuation interpolation based on feature perception; constructing an information box and a floating box of the route points on the aircraft route map; and performing meteorological display and alarm for aircraft navigation through the information box and the floating box according to the aircraft route plan. The present application uses regional meteorological forecast results to form meteorological forecast results for flight routes, can intuitively display the comprehensive meteorology on the route and form an alarm prompt, reduces the risk of information omission, increases the safety margin, and reduces the meteorological information processing workload of flight support personnel.

The invention relates to the technical field of hydraulic engineering safety monitoring and numerical analysis, and discloses a multi-dimensional cloud agent model assisted high-performance adaptive probability inversion system, which comprises a finite element modeling module, a sample generation module, a cloud agent model construction module, an adaptive inversion module and a dynamic updating module. The system constructs a multi-dimensional coupling cloud agent model for replacing finite element calculation by calculating cloud digital characteristics such as expectation, entropy and hyper entropy of input variables and generating a multi-layer virtual cloud droplet; performing parameter inversion by using a variable step Markov chain Monte Carlo algorithm based on local and global uncertainty indexes; and processing time sequence monitoring data by combining a state space model and a Bayesian recursion strategy to realize continuous correction of parameter posterior distribution. According to the method, the problems of long time consumption, low convergence efficiency and difficulty in processing time-varying characteristics of traditional inversion calculation are effectively solved, and efficient dynamic inversion and safety state accurate evaluation of dam full life cycle parameters are realized.

The invention provides an industrial multi-axis servo motor discrete temperature health assessment method based on a cloud model. The method comprises the following steps: acquiring a temperature discrete sample sequence of each servo motor; performing preprocessing operation on the temperature discrete sample sequence to obtain a preprocessed temperature sample sequence; when the temperature change rate of the pre-processing temperature sample sequence is lower than a set threshold value and lasts for a preset time length, dividing the pre-processing temperature sample sequence into heat balance windows corresponding to the servo motors, and respectively calculating an expected value, an entropy value and a super entropy value by taking the heat balance windows as input and adopting a reverse cloud generator; inputting the expected value, the entropy value and the hyper-entropy value obtained for each servo motor into a forward cloud generator to generate a cloud droplet set corresponding to the servo motor; and calculating a cloud droplet condensation degree based on the cloud droplet set, and generating a temperature health assessment level corresponding to each servo motor according to a preset judgment rule. According to the invention, the uncertainty of the discrete temperature data of the servo motor can be quantified in a unified manner, and the multi-axis temperature health level is generated.

1. The name of the design product: front scattering cloud droplet spectrometer. 2. The use of the design product: the design product is used for measuring the concentration of cloud particles in the atmosphere. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

This invention discloses a small-sample Bayesian optimization sampling method and system based on cloud droplet data augmentation, belonging to the field of transportation engineering material design. Addressing the problems of limited initial samples and poor fit of the Bayesian optimization surrogate model in modified asphalt formulation design, this invention acquires initial small-sample data; constructs a clustering cloud model to obtain expectation, entropy estimates, and hyperentropy estimates; generates cloud droplet virtual samples using a forward cloud generator and merges them with the original samples to expand the dataset; trains a Gaussian process regression surrogate model based on the expanded data; constructs an expectation-improved acquisition function to optimize and solve candidate formulations; updates the data after physical testing verification; and iterates repeatedly until the termination condition is met to output the optimal formulation. This invention mines the distribution information of small-sample data through cloud droplet data augmentation, improves the accuracy and sampling efficiency of the surrogate model, significantly reduces the number of expensive physical tests, and lowers the cost of formulation design. It can be widely applied to the formulation optimization of modified asphalt and similar high-cost experimental materials.

The invention discloses a precipitation enhancement system and method based on electroacoustic low-frequency sound waves of an unmanned aerial vehicle, and is applied to the technical field of sound wave precipitation enhancement. Comprising an unmanned aerial vehicle flying platform, an airborne power supply module and an electroacoustic low-frequency sound wave generation subsystem, the airborne power supply module supplies power to the electroacoustic low-frequency sound wave generation subsystem, the electroacoustic low-frequency sound wave generation subsystem converts electric energy into strong sound waves in a specific frequency band, cloud droplet collision, combination and growth are promoted, and finally rainfall is formed; the electro-acoustic low-frequency sound wave generation subsystem comprises an electro-acoustic conversion unit used for converting electric energy into low-frequency strong sound waves; the sound wave modulation unit is used for regulating and controlling sound wave parameters; and the damping integrated unit is used for isolating vibration generated when the electro-acoustic conversion unit works. The unmanned aerial vehicle is used as an aerial maneuvering platform, electric energy is efficiently converted into strong sound waves in a specific low-frequency band, the strong sound waves directly act on water vapor particles in a cloud layer, collision, merging and growth are promoted through sound wave vibration, and precipitation increasing operation is achieved.

The invention relates to the technical field of safety protection equipment performance evaluation, in particular to an integrated performance comprehensive evaluation method for fire-fighting chemical protective clothing, which comprises the following steps of: firstly, constructing a primary evaluation index system containing protective performance, environmental adaptability and human body efficiency and a secondary evaluation index system corresponding to the primary evaluation index system; secondly, a DEMATEL method and an entropy weight method are adopted to calculate a subjective weight and an objective weight respectively, and an optimal combination weight is obtained through fusion of an improved game theory model; then, a cloud model is introduced to convert the qualitative indexes into quantitative cloud droplets, and a comprehensive evaluation cloud is generated; and finally, fusing multi-source information by using a DS evidence theory, processing index conflicts, and outputting comprehensive evaluation grades and adaptive disaster scene suggestions. By fusing expert experience and experimental data, the problems of fuzziness and randomness in evaluation are effectively solved, and accurate evaluation of the performance of the chemical protection equipment and actual combat type selection guidance are realized.

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 provides a satellite communication attenuation prediction method and device for electric power communication in a remote area, electronic equipment and a non-transient computer readable storage medium, and the method comprises the steps: calculating a prediction attenuation value under the single influence of snowy weather, and obtaining a first prediction value; calculating a prediction attenuation value under the single influence of cloudy and foggy weather to obtain a second prediction value; based on the communication channel frequency of satellite communication, the snowing intensity of the current weather, the cloud liquid water content in the cloud and mist and the weather temperature, a prediction attenuation value additionally increased due to electromagnetic interaction between the snow crystal and the cloud droplet is determined, and a third prediction value is obtained; and obtaining a total attenuation prediction value of satellite communication based on the first prediction value, the second prediction value and the third prediction value. According to the satellite communication attenuation prediction method and device for remote region power communication, the electronic equipment and the non-transient computer readable storage medium provided by the invention, the signal attenuation condition of a satellite-ground link in satellite communication in a complex meteorological environment can be accurately predicted.

The present application belongs to the technical field of aerosol measurement, and particularly relates to a method and system for measuring the surface tension of cloud droplets in the process of aerosol activation into clouds. The method comprises: building a system for measuring the surface tension of cloud droplets, including a cloud condensation nucleus counter, electrode plates, a high-voltage power supply, a condensation nucleus particle counter, and a differential mobility analyzer; applying a high-voltage electric field to cause positive and negative ions in the droplets to split under the traction of the electric field; aerosol samples are converted into droplets by absorbing water vapor in a cloud chamber, and the droplets split under the traction of the high-voltage electric field; the number concentration of the droplets in the outflow sample is measured by the condensation nucleus particle counter; the critical voltage at which the droplets split is obtained by fitting the graph of the number concentration of the droplets versus the voltage intensity; and the surface tension of the droplets is calculated according to the quantitative relationship between the critical voltage and the surface tension of the droplets. The present application can be used in atmospheric chemical transport simulation and climate models to evaluate the influence of the surface tension of cloud droplets on the number concentration and particle size of the cloud droplets.

1. The name of the design product: Holographic cloud droplet spectrometer (LA24605). 2. The use of the design product: The design product is used for observing and analyzing the particle size distribution of cloud particles. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses a cloud droplet condensation process scale self-adaption method in a micro-physical parameterization scheme, and relates to the technical field of meteorology, and the method comprises the steps: S1, simulating to obtain cloud droplet condensation conversion rates under each scale of 0.5 km, 1 km and 3 km, and the temperature and water vapor before condensation under the scale of 0.5 km; s2, fitting normal distribution of 0.5 km supersaturation under a 3km scale; s3, dividing the normal distribution into M intervals; s4, analyzing the weighted cloud droplet condensation amount of each interval; s5, accumulating the weighted cloud droplet condensation amount of each interval to obtain the total cloud droplet condensation amount of the corresponding supersaturation degree under the 3km scale; s6, repeating the steps S2-S5, and analyzing to obtain the total cloud droplet condensation amount of the corresponding supersaturation degree under the scale of 1km; s7, constructing a scale-adaptive cloud droplet condensation parameterization scheme by using an extrapolation method, and realizing the self-adaption of the cloud droplet condensation process; according to the method, the deviation of the cloud droplet condensation process under different spatial scales is effectively weakened, the requirement of a variable grid mode is met, and the simulation accuracy and the short-time strong weather forecast accuracy are improved.

The invention discloses an airplane icing intensity and supercooled large drop forecasting method, which comprises the following steps of: acquiring weather forecasting data including temperature, cloud drop specific mass, cloud drop number concentration, raindrop specific mass and raindrop number concentration of each height layer; recognizing the supercooled cloud drops and the supercooled raindrops according to the temperature, and respectively determining the icing growth rates of the supercooled cloud drops and the supercooled raindrops based on the particle collision efficiency, the specific mass, the number concentration and the flight speed; determining the total icing growth rate by using the icing growth rates of the supercooled cloud drops and the supercooled raindrops; obtaining an icing intensity forecast result through the icing intensity threshold value; and identifying the supercooled large drop according to the diameters of the supercooled cloud drop and the supercooled raindrop. According to the method, cloud microscopic data and the flight speed are combined, so that the precision of airplane ice accretion identification is remarkably improved, and the method has relatively good interpretability and can be directly applied to a flight safety guarantee system.

1. The name of the design product: Holographic cloud droplet spectrometer (LA24605, LA24606 combination). 2. The use of the design product: The design product is used for observing and analyzing the particle size distribution of cloud droplets. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

1. The name of the design product: holographic cloud droplet measuring instrument. 2. The use of the design product: used in the field of cloud and fog physics, artificial weather influence, atmospheric environment, ecology, etc. to measure the size distribution and liquid droplet concentration of fog droplets and cloud droplets. 3. The design points of the design product: in the stereogram. 4. The picture or photo that best indicates the design points: stereogram 1.

The invention discloses a flood disaster risk assessment method based on a combined weight and a connection cloud model. The method comprises the following steps: determining a plurality of evaluation indexes of flood disaster risk assessment; calculating subjective weights of the evaluation indexes by adopting an improved analytic hierarchy process, calculating objective weights of the evaluation indexes by adopting a grey correlation analysis method, and obtaining a combined weight of each evaluation index based on a consistent zero modulus operator of a bounded lattice; constructing a connection cloud model, determining a digital characteristic value of the evaluation index through a reverse cloud generator, and generating cloud droplets according to the digital characteristic value to draw a connection cloud picture; calculating the connectivity of each evaluation sample of the research area for different preset risk levels based on the combined weight of the connection cloud atlas and the evaluation indexes, and judging the risk level of each evaluation sample according to the maximum membership principle; and generating a flood risk level spatial distribution map based on the risk levels of all the evaluation samples, and performing precision verification on the flood risk level spatial distribution map by using actual disaster situation data.

The application provides a ship collision arc gate failure risk method, system, device and medium, and relates to the field of water conservancy engineering safety evaluation. The method comprises the following steps: constructing an index system for evaluating the failure risk of the arc gate; simulating the dynamic response of the arc gate after being hit by ships under different ship tonnages and ship speeds according to a finite element model, so as to extract actual values of various evaluation indexes; sending the actual values of the various evaluation indexes into a forward cloud generator model to generate corresponding cloud droplets, so as to calculate the membership degrees of the various evaluation indexes under different risk levels; calculating the combined weight values of the various evaluation indexes by using an entropy weight method and a variation coefficient method, and combining the membership degrees to obtain corresponding basic probability assignment functions; and fusing the basic probability assignment functions of the different evaluation indexes according to a Dempster combination rule, so as to determine the final failure risk evaluation grade of the arc gate under the ship collision. The technical scheme can accurately measure the failure risk of the gate under the dynamic load.

The application discloses a flood disaster risk assessment method based on a combination weight and a connection cloud model, and comprises the following steps: determining a plurality of evaluation indexes of the flood disaster risk assessment; calculating subjective weights of the evaluation indexes by using an improved analytic hierarchy process, calculating objective weights of the evaluation indexes by using a grey correlation analysis method, and obtaining a combination weight of each evaluation index based on a consistent zero module operator of a bounded lattice; constructing a connection cloud model, determining a digital characteristic value of the evaluation index through a reverse cloud generator, and generating cloud droplets to draw a connection cloud diagram according to the digital characteristic value; based on the connection cloud diagram and the combination weight of the evaluation index, calculating a connection degree of each evaluation sample of a research region to different preset risk grades, and determining a risk grade of each evaluation sample according to a maximum membership degree principle; generating a flood risk grade spatial distribution diagram based on the risk grades of all the evaluation samples, and verifying the accuracy of the flood risk grade spatial distribution diagram by using actual disaster data.

The invention discloses a rainfall prediction method based on dynamic downscaling, which relates to the field of meteorological numerical weather forecast, and comprises the following steps: acquiring an initial field of regional forecast, accessing real-time rainfall data, radar reflectivity data and digital elevation model data of a ground meteorological station, and performing quality control and spatial interpolation processing to obtain a rainfall prediction result; generating an initial field with continuous space; based on the spatial continuous initial field, obtaining cloud-water conversion by adopting fractional calculus, and dynamically adjusting the cloud drop collision efficiency according to the terrain gradient field to obtain a cloud microphysical variable; and based on the cloud micro-physical variables, performing regional space encryption calculation by using a WRF model power framework. According to the method, a power frame of a triple nested grid and a Thompson / WSM6 / Morrison multi-scheme probability matching fusion technology are adopted, so that the rainfall forecast error of a complex terrain area is reduced, the strong rainfall forecast accuracy is improved in a mountain area with the gradient larger than 15 degrees, and an innovative technical system from initial field downscaling processing to final high-precision rainfall forecast generation is achieved.

The present application relates to the technical field of unmanned aerial vehicle flight path optimization, in particular to a rain enhancement environment detection path optimization method based on unmanned aerial vehicle. The method comprises: obtaining a target airspace three-dimensional grid set and initial atmospheric background field data; the unmanned aerial vehicle collects real-time data of supercooled water content, vertical air flow velocity and cloud droplet number concentration; based on the initial background field, the Gaussian process regression prior parameters are configured and the joint prediction distribution is updated with real-time data; the joint prediction distribution is transformed into a rain enhancement catalyst potential prediction mean and information entropy variance through a nonlinear activation function probability density; a collection function is constructed by fusing potential benefits and path energy consumption costs, and the maximum value of the collection function is used as the next target point iteration detection until the best catalyst area is locked. The present application realizes efficient and low-energy dynamic path optimization under the constraint of limited on-board fuel, significantly improves the cloud seeding window positioning accuracy and operation success rate.

The application discloses a flexible job shop scheduling optimization method, system, device and medium, and relates to the technical field of shop scheduling. The method comprises the following steps: constructing a flexible job shop scheduling mathematical model according to a flexible job processing time problem model and constraint conditions thereof; determining initial particle groups of a particle swarm algorithm for to-be-processed workpiece processes, and taking minimum processing time as a target function; taking a comprehensive prospect-regret value as an adaptability evaluation value of a particle in the particle swarm algorithm; adjusting an inertia weight by using an inertia weight power function and introducing a random number of chaotic behavior; generating a plurality of cloud droplets according to a one-dimensional normal cloud model, that is, a group of potential scheduling schemes near a current optimal solution; selecting a cloud droplet optimal value by setting a threshold value, comparing the cloud droplet optimal value with the current optimal solution, and performing more detailed search on a neighborhood of the current optimal solution to find a better solution that may exist, so that the method is more in line with complex decision-making conditions in actual production scheduling, and is helpful to find a better scheduling scheme.

1. The name of the design product: holographic cloud droplet spectrometer. 2. The use of the design product: the design product is used for the extraction and measurement of cloud droplet spectrum particles through digital holographic technology. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The application relates to the technical field of safety monitoring and numerical analysis of hydraulic engineering, and discloses a high-performance self-adaptive probabilistic inversion system assisted by a multi-dimensional cloud agent model, which comprises finite element modeling, sample generation, cloud agent model construction, self-adaptive inversion and dynamic updating modules. The system calculates cloud digital features such as the expectation, entropy and hyper-entropy of input variables, generates multiple layers of virtual cloud droplets, and constructs a multi-dimensional coupled cloud agent model to replace finite element calculation; a variable step Markov chain Monte Carlo algorithm based on local and global uncertainty indexes is used to perform parameter inversion; time-series monitoring data are processed by combining a state space model and a Bayesian recursive strategy, and continuous correction of the parameter posterior distribution is realized. The application effectively solves the problems of long calculation time, low convergence efficiency and difficulty in processing time-varying characteristics in traditional inversion, and realizes efficient dynamic inversion of dam life cycle parameters and accurate safety state evaluation.

1. The name of the design product: Holographic cloud droplet spectrometer (LA24641A). 2. The use of the design product: For observing and analyzing the particle size distribution of cloud and fog particles. 3. The design points of the design product: In shape. 4. The picture or photo that best indicates the design points: Perspective view.

This invention discloses a chemical weather model forecasting method and system based on atmosphere-chemistry bidirectional coupling. The method includes full-process variable registration, writing grid pointer variables to obtain grid static ground data, extracting key physical parameters, calculating the dynamic transport of the tracer array in the main integration program and transmitting it to the CHEM driver, calling the CHEM driver in the main integration program, and simultaneously transmitting the CMAMeso meteorological field, the tracer array, the physical parameters, and the grid static ground data to CUACE for atmospheric chemical process calculation. The atmospheric chemical process calculation results are then transmitted back to the main integration program to achieve online atmosphere-chemistry coupling. The method establishes real-time calculation of key aerosol radiation parameters, performs real-time cloud droplet activation to obtain cloud droplet number and concentration, establishes an aerosol-cloud interaction mechanism to output cloud parameters, updates the radiation transport scheme, and performs numerical forecasts of environmental meteorological and weather elements. This method can improve the accuracy of chemical weather model forecasts and also has good physical interpretability.

The application discloses a dam deformation anomaly identification method and device based on frost and ice optimization decomposition and probability sparse attention mechanism, and relates to the technical field of dam safety monitoring data processing. A frost and ice optimization algorithm is adopted, a global optimization is performed on a variational mode decomposition model by using a frost and ice search mechanism; a joint screening criterion of slope entropy and spectral energy is adopted to perform feature quantization and screening, and a pure residual component sequence is reconstructed; a reconstruction error sequence is determined based on an Informer deep time series prediction network; statistical analysis is performed by using a reverse cloud reasoning generator algorithm, a threshold interval is determined based on the statistical law of cloud droplet distribution; the reconstruction error sequence is mapped to the threshold interval point by point according to time, and if the amplitude of the reconstruction error jumps out of the interval boundary of the threshold interval at a time, it is determined that the dam deformation monitoring data corresponding to the time is abnormal, so as to complete the positioning of the abnormal value. The application aims to improve the intelligent and refined level of dam safety monitoring.

This invention discloses a scale-adaptive method for cloud droplet condensation processes in a microphysical parameterization scheme, relating to the field of meteorological technology. The method includes: S1, simulating the cloud droplet condensation conversion rate and the pre-condensation temperature and water vapor at each scale of 0.5 km, 1 km, and 3 km; S2, fitting a normal distribution of supersaturation at the 0.5 km scale at the 3 km scale; S3, dividing the normal distribution into M intervals; S4, analyzing the weighted cloud droplet condensation amount in each interval; S5, summing the weighted cloud droplet condensation amounts in each interval to obtain the total cloud droplet condensation amount corresponding to the supersaturation at the 3 km scale; S6, repeating S2-S5 to analyze the total cloud droplet condensation amount corresponding to the supersaturation at the 1 km scale; S7, using extrapolation to construct a scale-adaptive cloud droplet condensation parameterization scheme, achieving adaptation of the cloud droplet condensation process. This method effectively reduces the deviation of the cloud droplet condensation process at different spatial scales, meets the requirements of variable grid models, and improves the accuracy of simulations and short-term severe weather forecasts.

The invention relates to the field of marine traffic safety, in particular to a multi-ship collision avoidance method based on an extendable finite interval cloud model, which comprises the following steps: constructing a multi-ship collision risk index system based on hydrometeorological elements and multi-ship navigation characteristics; the collision avoidance decision weight of each index in the multi-ship collision risk index system is calculated, and the collision avoidance decision weight calculation process comprises the steps that the collision avoidance rule weight is calculated through an optimal and worst method, the environment perception weight is calculated through an extension correlation function, the collision avoidance rule weight and the environment perception weight are combined together through the game theory, and the collision avoidance decision weight is calculated; obtaining a collision avoidance decision weight; calculating a cloud model feature value of each index in the multi-ship collision risk index system, inputting the feature values into a forward finite interval cloud generator to obtain a cloud droplet distribution diagram, and calculating a cloud certainty degree vector corresponding to each index; and multiplying the collision avoidance decision weight by the cloud certainty degree vector to obtain a comprehensive cloud certainty degree, and avoiding multi-ship collision. The method provided by the invention has stronger distinguishing capability and evaluation precision in complex encounter.

1. The name of the design product: Holographic cloud droplet spectrometer (LA24641). 2. The use of the design product: For observing and analyzing the particle size distribution of cloud and fog particles. 3. The design points of the design product: In shape. 4. The picture or photo that best indicates the design points: Perspective view.

This invention discloses a fatigue state evaluation system and method for unmanned aerial vehicle (UAV) operators. It employs a strategy combining functional decomposition and task orientation to construct a hierarchical evaluation system encompassing four dimensions: eye-tracking perception, cognitive integration and attention allocation, task-related eye-tracking performance, and eye-tracking-fatigue iterative learning and adaptation. This system is quantitatively represented through 36 underlying indicators. A task-situation gating weighting model based on a normal cloud model and Shapley value game is constructed. Expert verbal ratings are converted into cloud drops to retain fuzziness and randomness. Shapley values ​​are used to eliminate redundant indicator coupling, and subjective and objective weights are dynamically integrated through task-situation gating factors. This invention can accurately quantify operator fatigue state in conjunction with task context, solving the problem that traditional static evaluation is difficult to adapt to dynamic environments and individual differences. It improves the robustness and accuracy of UAV inspection personnel status assessment and has strong applicability.