76 results about "Cloud droplet" patented technology

The invention discloses a comprehensive evaluation method of water quality based on a water pollution index method and cloud models, and relates to an improvement on the water pollution index method by using the cloud models based on the water pollution index method. The cloud models are combined with WPI values in the water pollution index method, a WPI value evaluation cloud model is obtained by a cloud parameter determination method, a single factor WPI value cloud model is obtained by a backward cloud generator, a normal cloud generator is used to generate a WPI value evaluation cloud picture and a single factor WPI value cloud picture to intuitively see the pollution status of each single factor; weights are combined, a comprehensive WPI value cloud model is obtained through a comprehensive cloud algorithm, and comprehensive evaluation grades of the water quality are intuitively displayed by a form of cloud droplets and determined, so that the problems that contributions of all pollution factors in comprehensive evaluation of the water quality are not considered in the water pollution index method and comparisons among different sections are difficultly realized are effectively solved.

The invention relates to an electric return circuit fault probability forecasting method which includes the following steps: (1) counting health indexes of electric transmission and transformation equipment in the past ten years; (2) defining a cloud drop (x,u(x)) by using a statistical value of the health indexes in the past years; (3) establishing a device fault probability forecasting cloud model through a backward cloud generator; (4) producing a needed number of specific cloud drops through a forward cloud generator; (5) detecting whether the cloud drops are placed in a confidence interval; (6) forecasting fault probability of a transformer device in the next year; and (7) defining a fault probability forecasting value of a return circuit where a computing device is placed according to partition of an electric return circuit. On the basis of the cloud model, influences of the service life and self health state of the electric return circuit on fault probability of the electric return circuit, and forecasting computation conducted on the fault probability of the electric return circuit, data support is provided for evaluating reliability of the electric return circuit and computing fault risks of the electric return circuit, and the electric return circuit fault probability forecasting method is good in popularization value and application prospect.

The invention relates to a three-dimensional cloud field generating method based on airborne weather radar simulation. The method is used for external environment simulation of an airborne weather radar. The method comprises the steps that 1) dynamic satellite cloud image data are acquired and are used as the information source of a simulation three-dimensional cloud field; 2) according to the dynamic satellite cloud image data, a cellular automata iteration method is used to generate cloud droplet density in a simulation three-dimensional cloud field; 3) a dual two-dimensional grid local iteration method is used to carry out data updating on a space related to test in the generated simulation three-dimensional cloud field; and 4) according to the three-dimensional cloud field after data updating and a state query interface, a simulation test is carried out on the external environment of the airborne weather radar. Compared with the prior art, the method provided by the invention has the advantages of less memory, less calculation data, high accuracy, flexible application and the like.

The invention relates to a miniature onboard reverse plug flow cloud droplet sampling device, which comprises an air inlet cavity and a collection cavity, wherein the collection cavity is formed in the air inlet cavity; the front end of the air inlet cavity is connected with the outer edge of the sampling end of the collection cavity; an air inlet pipe is arranged on the tail part of the air inlet cavity; the collection cavity comprises the tubular sampling end, a preheating cavity body and a tubular capturing end, which are sequentially connected; a through micropore is formed on the tube wall of the tubular sampling end; a heating device is arranged on the outer wall of the preheating cavity body in a surrounding way; and an extraction pipe is arranged on the tail part of the preheating cavity body. The sampling device can be special for collecting aerosol particles or cloud droplets with large particle sizes. The sampling device and the working method thereof are widely usable, less in investment, convenient to use and practically significant, and the feasibility and practicability of an aviation sampling technology are improved.

The invention discloses a cloud particle detecting system and method based on polarization detection. The system comprises a laser transmitting optical unit for generating polarized light, a forward scattering detecting unit and a backward scattering detecting unit, wherein the laser transmitting optical unit generates the polarized light by using a laser diode, a polaroid and a half wave plate; the forward scattering detecting unit is used for judging whether particles are recorded and sizes of cloud particles are obtained; and the depolarization ratio of the scattered light is obtained through the backward scattering detecting unit to determine a phase state of the particles. According to the method, information such as the size and the phase state of the particles is determined by the forward scattering detecting unit and the backward scattering detecting unit jointly, particle size spectrum distribution of cloud droplets and ice crystals is obtained, and then, solid water content and liquid water content in cloud are obtained.

The invention belongs to the technical field of wind power generation, and especially relates to a doubly-fed wind farm group aggregating method and a doubly-fed wind farm group aggregating system based on the dynamic characteristics of rotor current. The method comprises the following steps: building a doubly-fed wind farm model, and obtaining the rotor current peaks of each fan under different wind conditions and fault conditions as cloud droplet sample data through random combination of random wind speed and random voltage drop degree; according to the obtained cloud droplet sample data, using a reverse cloud generator to get three digital characteristics of a rotor current peak cloud model of each fan, namely, expectation, entropy and hyper entropy; and taking the three digital characteristics of each fan as wind farm grouping indexes, and using a clustering algorithm to group and aggregate large wind farms. The wind farm group aggregating method of the invention can accurately reflect the transient fault characteristics of wind farms under random wind speed and random voltage drop degree and provide model support for short-circuit current calculation and relay protection setting of wind farms.

The invention belongs to the technical field of weather forecasting, and discloses a method used for improving the weather forecasting accuracy based on an aerosol physicochemical property and a cloud formation mechanism. The method comprises the steps that aerosol physicochemical property analyzing, aerosol and cloud droplet vertical feature analyzing, CCN and warm cloud micro-physical structure analyzing of the Sichuan Basin are carried out; aerosol-CCN-cloud droplet parameterization relational expressions under different pollution backgrounds, different seasons and different weather backgrounds are provided; and the parameterization relationship between CCN and cloud droplet at different vertical heights is establishment. According to the invention, the influence mechanism of the aerosol on the warm cloud micro-physical process in the Sichuan Basin is disclosed, so as to improve the weather forecasting accuracy in the Sichuan Basin; the vertical change features of the aerosol-CCN-cloud parameterization relationship under the high concentration aerosol background of the Sichuan Basin are acquired; the parameterization result is applied to a mesoscale weather forecasting model; and the regional weather forecasting accuracy is improved.

The invention provides a method for analyzing the networked transaction data collection and transaction completion degree. Collected networked transaction evaluation data are calculated based on the reverse credit cloud algorithm to obtain numerical characteristics reflecting various credit evaluation index qualitative concepts; the virtual cloud comprehensive algorithm is adopted to obtain the comprehensive credit cloud of a main body; the numerical characteristics of the comprehensive credit cloud are calculated based on the forward direction credit cloud algorithm, the credit evaluation situation is restored, a series of credit cloud droplet data is generated, a credit evaluation cloud picture can be drawn, and the credit is an important measurement index of the networked transaction completion degree. By means of the method, randomness and fuzziness produced in the networked transaction credit evaluation process are well solved, an evaluation model put forward based on the credit cloud can reflect the evaluation index from multiple angles and multiple levels, and comprehensiveness, objectivity and authenticity of the evaluation result can be guaranteed. The transaction completion degree analyzing is carried out according to the evaluation result, and a reliable reference basis can be provided for the networked transaction platform operation and the network resource allocation.

A method for optimize dispatch of charge and discharge of multi-objective electric vehicle based on cloud self-adaptive particle swarm feature that information transmission among birds is used to guide swarm to move in that direction of possible solution, and better solution is found in iterative solution. Each bird in the swarm is abstracted as a particle without mass and volume. The particles cooperate with each other and share information with each other. The velocity of the particles is affected by their own and the historical state of the swarm. The influence of the historical optimal position of the particle and the swarm on the direction and velocity of the current particle movement can better coordinate the relationship between the particle and the whole, which is conducive to theswarm optimization operation in complex space. Adaptive particle swarm optimization algorithm can not reflect the actual search optimization process in many cases. Cloud theory introduces adaptive particle swarm optimization algorithm using cloud droplet randomness and stability tendencies to maintain the diversity of the population to improve the convergence rate of the algorithm.

The invention discloses a driving risk control method, a driving risk control device and a computer storage medium, relates to the technical field of risk early warning, and aims to solve the problemsthat the risk probability of driving participants cannot be accurately provided and the driving safety of vehicles cannot be ensured. The driving risk control method comprises the steps of receivingmotion information of at least two driving participants; determining that the risk degrees of the at least two driving participants are the same, and analyzing the motion information by utilizing a risk cloud model to obtain a distribution proportion of the risk probability of each driving participant in a preset distribution area, wherein the risk cloud model comprises at least one Gaussian clouddroplet model one of the risk degree, the mean value function of each Gaussian cloud droplet model is a potential energy field model function associated with the motion information, and the variancefunction is an uncertainty function associated with the motion information; and displaying the driving early warning information according to the distribution proportion of each driving participant inthe preset distribution area. The driving risk control device provided by the invention is used for executing the driving risk control method.

The present invention discloses an error calculating method and system. The method comprises: determining influencing factors of an electric transformer, wherein the influencing factor comprises an operating temperature and residual magnetism of the electric transformer, and a combination of one or more of an electric field, a magnetic field, a high voltage leakage current and a frequency measured by the electric transformer at a time; separately acquiring a monitoring value xAr corresponding to each influencing factor; separately according to the monitoring value xAr corresponding to the influencing factor and a cloud model, acquiring a total number L of cloud droplets, and separately according to the monitoring value xAr and the total number L of cloud droplets, calculating to acquire a running variation FA corresponding to the influencing factor; separately acquiring an MDTW distance of the influencing factor, performing weighted integration processing on the MDTW distances of all the influencing factors and the running variations FA corresponding to all the influencing factors to obtain an integration running variation delta F; and, according to the integration running variation delta F and an extrapolation error of the electric transformer, obtaining a dynamic error of the electric transformer. According to the error calculating method and system, the dynamic change of errors can be completely characterized and measured, so that the accuracy of calculating dynamic errors of the electric transformer is improved.

The invention discloses a risk assessment and evaluation method for an adjacent bridge damage caused by subway construction. The method comprises: step one, carrying out discretization on index continuity attribute data by using a cloud model and constructing a five state zones of an index based on risk zone identification and division; step two, establishing an inference rule base piece formed by a plurality of IF-THEN rules by combining a rough set; (3), converting a practical observation index attribute value and then inputting the converted value into a corresponding first piece cloud generator, thereby generating an attribute cloud droplet; (4), after synthesis of a plurality of inference rules, carrying out step-by-step inference processing on the attribute cloud droplet by using a membership degree of a minimum inference engine as a weight of an inference result so as to obtain a final output value and a membership degree cloud droplet; and (5), setting a variable coefficient of the attribute value of the practical observation index, carrying out inference processing to obtain a plurality of cloud droplets, inputting the plurality of cloud droplets into a backward cloud generator, and outputting an expectation value used as a final risk value.

The invention relates to a method for evaluating the similarity between technical index cloud models of an expressway, and the method comprises the following stages: an expert evaluation cloud generation stage based on the cloud models, a standard evaluation cloud generation stage based on the cloud models, and a calculation stage of the similarity between two types of clouds. Compared with a conventional similarity evaluation method, the method provided by the invention irons out the defect that a conventional similarity comparison method based on vectors has to carry out the strict matching of the attributes of objects, optimizes an algorithm, and improves the calculation precision. Meanwhile, the method reduces the time in selecting, ordering and combining the cloud droplets, and improves the calculation efficiency of the similarity between the cloud models.

The invention relates to a laser forward scattering cloud droplet spectrum detection system. The system utilizes mie forward scattering signals, which are generated by irradiating micro water steam particles in the air by laser beams, to measure the spectral distribution of water steam and water steam content of atmosphere. A red light semiconductor laser with uniform strength is adopted as the irradiation source, and through laser beam alignment and focusing, a sampling area with a certain size is formed in the space. Scattering signals can be generated by irradiating particles in the sampling area by laser beams, and the distribution of cloud particles with a size of 2 to 50 [mu]m can be measured through forward scattering signal measurement, deep field inner particle judgment, and double channel weak signal detection. The provided system has the characteristics of small volume, compact structure, realtime measurement, and high measurement precision, and is widely used in fields such as realtime artificial rainfall enhancement, cloud particle distribution determination, cloud physical research, and the like.

The present invention provides a calibration apparatus for a scattering type cloud droplet particle detector, and belongs to the technical field of meteorology analysis. The calibration apparatus comprises a three-dimensional translation table, a glass bottle for placing standard particles, a constant gas flow pump and an optical fiber core, wherein the table surface of the three-dimensional translation table is fixedly connected with the glass bottle, the bottle opening of the glass bottle is connected with a glass bottle cover, the glass bottle cover is provided with a gas inlet pipe and a gas outlet pipe, one end of the gas inlet pipe extends into the bottom of the glass bottle, the other end of the gas inlet pipe is connected with the constant gas flow pump through a pipeline, one end of the gas outlet pipe extends into the upper portion of the glass bottle, and other end of the gas outlet pipe is fixed with the optical fiber core. The present invention further provides a calibration method for a scattering type cloud droplet particle detector. The calibration method comprises determining a center position, calculating a sensitivity area, drawing an amplitude and frequency distribution map, and drawing a cloud droplet particle detector characteristic response curve. With the present invention, problems of different speeds, internal superposition of sensitivity areas, and the like during a calibration process are avoided, it is ensured that particles pass through the sensitivity area, and use efficiency of particles is increased.

The invention discloses a method for detecting supercooled water clouds. The problem is solved that existing methods cannot be used for accurately identifying the distribution range of the supercooledwater clouds in an ice-water mixed cloud phase state. The method includes the steps of downloading historical cloud parameter data and setting up historical sample data for an area to be studied; distinguishing historical supercooled water cloud regions and historical non-supercooled water cloud regions according to images, carrying out statistics on the occurrence frequency of various cloud phase states of the historical cloud parameter data, and determining a cloud phase state criterion, a cloud top temperature criterion and a cloud droplet effective radius criterion; obtaining current cloud parameter data for the area to be studied and setting up current sample data; according to the cloud phase state criterion, distinguishing supercooled water cloud regions in the cloud phase states and non-supercooled water cloud regions in the cloud phase states; according to the cloud top temperature criterion, distinguishing the supercooled water cloud regions with cloud top temperatures; according to the cloud droplet effective radius criterion, distinguishing the supercooled water cloud regions. According to the method, the rapid and stable detection of the supercooled water clouds is achieved, the calculation efficiency is high, and the application range is wide.

The invention discloses a method for synthesizing human facial expressions based on a cloud model, comprising the steps of: 1. inputting a human face image to be synthesized, and reading the human face image to be synthesized into a data matrix; 2. taking the data matrix as input , using the reverse cloud generator to process the data matrix of each face image to be synthesized separately, so as to obtain the corresponding expected image, entropy image and super-entropy image of each face image to be synthesized; 3. Using the expected image, entropy image and super-entropy image As input, use the forward cloud generator to process the desired image, entropy image and super-entropy image, and obtain the cloud drops corresponding to each face image; 4. Assign weights to each cloud drop, and combine all cloud drops into one Dayundi; 5. Taking Dayundi as input, using the reverse cloud generator in the cloud generator to realize facial expression synthesis. The method of the invention can realize the synthesis of any expression at any ratio by adjusting the weight, so that more comprehensive and rich facial expression images can be synthesized.

The invention discloses a method for predicting the icing thickness of a wire in a complex mountain environment. The method comprises the following steps: acquiring meteorological elements monitored by a meteorological station near the wire to be predicted, and the environment temperature, altitude information and wind speed of the position of a tower pole; calculating the air pressure of the position of the tower pole according to the acquired meteorological elements and the environment temperature and altitude information of the position of the tower pole; calculating the liquid water content of the position where the tower pole is located by combining the environment temperature and air pressure of the position where the tower pole is located and meteorological factors monitored by a meteorological station; estimating the median volume diameter of the cloud droplet according to the liquid water content of the position of the tower pole; and estimating the raindrop falling end speedand the raindrop particle size according to precipitation data monitored by the meteorological station. According to the method, related monitoring data of the power transmission line in the miscellaneous mountainous region environment are obtained, and through a series of processing, the change characteristics of the conductor icing thickness in the complex mountainous region environment can be accurately predicted.

The invention relates to a miniature onboard cloud droplet sampling system. The system comprises a gas compression pump (15), a dryer (16), a filter (17), a mass flow controller (18), a miniature onboard cloud droplet sampling device (19), a flow division device (20), a sampling membrane (21), a dryer (22), a filter (23), a mass flow controller (24) and an extraction pump (25), which are sequentially connected according to an airflow sampling direction. The miniature onboard cloud droplet sampling device comprises an air inlet cavity and a collection cavity, wherein the collection cavity is formed in the air inlet cavity; the front end of the air inlet cavity is connected with the outer edge of the sampling end of the collection cavity; an air inlet pipe is arranged on the tail part of the air inlet cavity; the collection cavity comprises the tubular sampling end, a preheating cavity body and a tubular capturing end, which are sequentially connected; and a through micropore is formed on the tube wall of the tubular sampling end. The sampling system can be special for collecting aerosol particles or cloud droplets with large particle sizes.

Disclosed are a warm cloud catalyst, a preparation method and an application thereof. The warm cloud catalyst comprises the following components in parts by weight: plant powder/plant ash/plant carbon powder 80-120 parts; surfactant dry powder 0.5-5 parts or a surfactant solution 15-32 parts; and a thickening agent 2-10 parts. All the components of the catalyst are easily wettable. The plant powder/plant ash/plant carbon powder is used as a dispersing agent and a vapor condensation nucleus; the surfactant can reduce surface tension of some cloud droplets and facilitate combination of the cloud droplets with other cloud droplets upon collision, so as to expand the cloud droplet spectrum; the thickening agent can absorb water and continuously expand to become large droplets in cloud. The catalyst is non-corrosive, is not easily agglomerated, is easy to store, produce and process, and is safe and nontoxic, available in material, and convenient and simple in use.

The invention relates to an urban rail transit short-term passenger flow dynamic prediction method. Based on a traditional passenger flow prediction method and actual passenger flow data, the method includes generating a prediction error sequence of the prediction time interval; by means of a reverse cloud generator, establishing a prediction error cloud model, generating a prediction error normalcloud drop distribution diagram by adopting a normal cloud generator, calculating a cloud drop quantile under a given confidence level and a confidence range of possible fluctuation of the passengerflow volume corresponding to the cloud drop quantile by utilizing a quantile principle, and then predicting the passenger flow volume at the next moment according to the uncertainty interval. According to the urban rail transit short-term passenger flow dynamic prediction method provided by the invention, uncertainty analysis of urban rail transit short-term passenger flow prediction can be realized, the short-term passenger flow prediction precision is improved, and a more accurate basis is provided for safety management and operation organization decision of urban rail transit.