59 results about "Cloud particle" patented technology

Techniques for analysis and prediction of cloud particle distribution and solar radiation are provided. In one aspect, a method for analyzing cloud particle characteristics includes the steps of: (a) collecting meteorological data; (b) calculating solar radiation values using a radiative transfer model based on the meteorological data and blended guess functions of a cloud particle distribution (c) optimizing the cloud particle distribution by optimizing the weight coefficients used for the blended guess functions of the cloud particle distribution based on the solar radiation values calculated in step (b) and measured solar radiation values; (d) training a machine-learning process using the meteorological data collected in step (a) and the cloud particle distribution optimized in step (c) as training samples; and (e) predicting future solar radiation values using forecasted meteorological data and the machine-learning process trained in step (d).

The invention discloses a cloud particle spectrum distribution measuring method and system. The measuring system comprises a disc-shaped polarization laser beam generating system, a grain scattered light detection system and a computer system. The measuring method provided by the invention comprises the steps of irradiating cloud grains by polarized light, dividing scattered signals into two ways by a beam splitter prism, carrying out detection of an out-of-focus interference pattern on one way of scattered signals directly by a photoelectric image detector while carrying out detection on a depolarization out-of-focus interference pattern on the other way of scattered signals by a depolarizer and a photoelectric image detector, distinguishing a cloud particle phase state by comparing the out-of-focus interference pattern with the depolarization out-of-focus interference pattern, and inverting according to out-of-focus interference fringe pattern information to obtain a liquid phase cloud particle size and an ice phase cloud particle equivalent size. The cloud particle distribution measuring method provided by the invention serves as a new diagnostic method for atmosphere particle detection, can be used for onboard cloud micro physic detection, and is capable of implementing on-line measurement of the phase state, size, distribution and water content of cloud particles so as to provide the powerful basis for meteorology forecast and manual intervention.

The invention discloses a ground terahertz radar system for detecting a cloud. The system comprises a terahertz transmitting module, a terahertz receiving module, a terahertz transmitting-and-receiving antenna module, a terahertz signal processing module and an upper computer module; the center frequency of a terahertz signal transmitted by the terahertz transmitting module is 220 GHz, the work bandwidth is 5 GHz, the transmitting power is 200 mW, the pulse width is adjustable ranging from 100ns to 3mus and the adjusted step length is 100ns, and the pulse repletion frequency is adjustable ranging from 1KHz to 10KHz and the adjusted step length is 1KHz. Compared with a laser radar and a millimeter wave radar, the ground terahertz radar system for detecting the cloud utilizes a set of parameters applicable to the cloud detection and is capable of penetrating into a thin cloud and an extremely thin cloud to carry out the three-dimensional structure detection for the cloud, and therefore not only a macrostructure such as the cloud thickness, the cloud height, the number of cloud layers, the vertical section variance of the cloud can be obtained, but also a microstructure such as the size, the shape, and the ice water content of a cloud particle can be obtained.

Techniques for analysis and prediction of cloud particle distribution and solar radiation are provided. In one aspect, a method for analyzing cloud particle characteristics includes the steps of: (a) collecting meteorological data; (b) calculating solar radiation values using a radiative transfer model based on the meteorological data and blended guess functions of a cloud particle distribution (c) optimizing the cloud particle distribution by optimizing the weight coefficients used for the blended guess functions of the cloud particle distribution based on the solar radiation values calculated in step (b) and measured solar radiation values; (d) training a machine-learning process using the meteorological data collected in step (a) and the cloud particle distribution optimized in step (c) as training samples; and (e) predicting future solar radiation values using forecasted meteorological data and the machine-learning process trained in step (d).

The invention discloses a scattering multi-angle receiving optical system of a scattering-type cloud particle detector based on a single-mode fiber coupling output semi-conductor laser. The optical system of the scattering-type cloud particle detector comprises a transmitting optical unit, a forwards scattering detection unit and a side backward scattering detection unit and uses the single-mode fiber coupling output semi-conductor laser, an aspherical collimating mirror, a square-hole diaphragm and a 4f transformation system so as to not only generate the uniform illumination of needed laser, but also solve the diffraction problem in a beam-cutting process and improve the purity of received scattered light. The cloud particle detector of the invention has two receiving angles and can deduce the phase states of cloud particles according to a ratio of the two electric signals output at the two angles.

The present invention discloses a cloud particle detection method and a cloud particle detector. According to the cloud particle detection method, the backscattering signals of the cloud particles are received to detect the depolarization condition of the cloud particles on laser so as to obtain the phase state of the cloud particles; and the forward scattering signals of the cloud particles are received to detect the equivalent optical particle size of the cloud particles. According to the present invention, with the cloud particle detection method and the cloud particle detector, the small ice crystal (less than 50 [mu]m) in the mixing phase state cloud can be effectively detected.

The invention discloses an inversion method for microphysical parameters of liquid cloud. The inversion method mainly includes the following process: according to radar reflectivity factors provided by a millimeter waves cloud radar, based on the optimal estimation theory, adopting an empirical formula calculation value as a prior value, assuming that particle spectrum submits to logarithmic normal distribution, a function relationship of radar reflectivity factors and liquid cloud physical parameters is established, and the inversion optimal solution is obtained in a condition when the difference value weighing of to-be-inverted parameters, the prior value, the radar reflectivity factors and function calculation value achieves the minimum value. Besides, according to an error transmission theory, uncertainty of liquid cloud microphysical parameters is calculated. The invention can make up a shortcoming of poor adaptability of a traditional empirical formula. Also, besides, common cloud particle diameter and cloud water content, particle concentration and distribution width can also be obtained; the inversion result is more comprehensive. Since the radar reflectivity factor in real time monitoring is adopted for prior value calculation, the inversion result accuracy is improved.

A novel methodology for detecting cloud particles is disclosed herein. This methodology exploits the optical glory phenomenon. According to one embodiment, a method for detecting clouds includes receiving data from a sensor which is configured to measure polarization of scattered light in a direction substantially opposite to the direction of incident light, and identifying, from the received sensor data, a cloud based on the polarization of the scattered light.

The invention discloses a multi-field polarization lidar detection system and a method for detecting an ice cloud, wherein the multi-field polarization lidar detection system comprises a transmittingmodule, a receiving module and a main control module. The transmitting module comprises a laser, a beam expander and a first reflector. The receiving module comprises a telescope, a second reflector,an electric aperture, a convex lens, an optical filter, a polarizer, an attenuator, a polarization beam splitter, a first to second photodetectors and a signal acquisition module; the laser, the electric aperture and the signal acquisition module are respectively connected with the main control module; and the first photodetector and the second photodetector are respectively connected with the signal acquisition module. The detection method utilizes a laser to generate laser radiation of a wavelength of 532 nm; parallel polarized light and vertical polarized light are respectively detected through two optical receiving passages of a parallel detection passage and a vertical detection passage; a depolarization ratio is calculated through the two detection passages; and the depolarization ratio and a T-Matrix method are used for calculating the content of ice water and effective particle radius of cloud particles.

The invention discloses a wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm. The wind power system reactive power planning method comprises the steps that a reactive power planning mathematic model is built, and a target function is determined; original data of a wind power system is input, and therefore an initial population is formed; all particles are generated randomly, a golden section judging criterion is used for dividing a particle swarm into three parts according to the self-fitness value of the particle swarm, and different inertia weight is set for each part of particles; new positions and speeds of the particles are obtained through the particle swarm optimization algorithm, the particles are divided into three parts and iterated repeatedly according to the method before an the end condition is met, an optimal solution is searched, and therefore reactive power planning of the wind power system is achieved. According to the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm, the node voltage level of the wind power system is effectively improved, network loss of a power network is reduced, the diversity of the particles is kept according to the algorithm, the prematurity phenomenon which easily occurs during optimization searching is avoided, and convergence rate in the optimization searching process is improved. In addition, the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm is small in calculated amount, and higher in operability.

The invention discloses a cloud particle measuring system and method. The cloud particle measuring system provided by the invention comprise a probe part and an upper computer part, wherein the probe part comprises a cloud particle acquiring module, a cloud particle signal analysis module, a cloud particle image compression module and a framing uploading module; and the upper computer part comprises a cloud particle image receiving module, a cloud particle image decompression module, a cloud particle image storage module, a cloud particle signal analysis module and a binary image display module. The cloud particle measuring system provided by the invention detects the cloud particles by using a one-dimensional linear array photodetector composed of 128 photoelectric diodes, effectively and rapidly acquires, records, stores, analyzes and displays an immense amount of cloud particle data through a series of specific processing technologies, and realizes the cloud microphysics detection of large particles in 50-6400 microns range, thereby providing an important scientific proof for weather modification.

The invention discloses a method for drawing three-dimensional entity cloud. The method comprises a step (1) of creating a multithread processing frame which comprises a rendering main thread, a batch data generating thread and a cloudscape sub-thread, executing the rendering main thread and the batch data generating thread through a graphics processing unit (GPU), and executing the cloudscape sub-thread through a central processing unit (CPU); a step (2) of causing the cloudscape sub-thread to simulate dynamic cloud; a step (3) of causing the cloudscape sub-thread to calculate scattering color of cloud particle when light penetrates a cloud density space; and a step (4) of causing the rendering main thread to render final three-dimensional entity cloud according to computed results of the cloudscape sub-thread. According to the method, by construction of the reasonable processing frame, cloud data calculation and processing are separated from cloud graphics output, the burden on three-dimensional programs is relieved, and real-time dynamic simulation and illumination calculation of the three-dimensional entity cloud are achieved.

The invention provides cloud detection experimental device and method based on a terahertz active cloud-detection radar. The device comprises an emission box body, an emission antenna, a receiving box body, a receiving antenna, a system experimental platform structure, an inversion computer and a power supply system; the system experimental platform structure comprises a left mounting flat plate, a right mounting flat plate, a separating and locking mechanism, a 90-degre overturning mechanism for a mounted flat plate, an up-down moving mechanism for the mounted flat plate, two box body 90-degree rotating mechanisms and a control mechanism; the emission box body is used for generating a terahertz detection signal with the frequency of 220GHz and power of 100mW, and the emission antenna emits the detection signal; the receiving box body is used for acquiring an echo signal received by the receiving antenna and processing the received echo signal; the inversion computer is used for performing cloud parameter inversion for the signal processed by the receiving box body, so as to acquire cloud particle size and cloud and mist concentration information. With the adoption of the device and method, the cloud detection experiment under different polarizing modes can be achieved.

The invention relates to an optimal configuration method and device for the hybrid energy storage capacity of a microgrid energy storage power station, and belongs to the technical field of configuration optimization for a microgrid energy storage system. The optimal configuration method comprises the steps of determining the structure of a pre-installed microgrid energy storage power station andpower supply reliability indexes, determining to take the minimum whole life cycle cost of hybrid energy storage equipment as an objective function and constraint conditions, and solving an optimal configuration model by adopting a chaotic cloud particle swarm algorithm integrating an AEA algorithm. The optimal configuration method overcomes the dependence on the initial value, improves the optimization performance of the algorithm and finds the optimal solution. In addition, the capacity and quantity, which are displayed by the optimal solution, of storage batteries and supercapacitors are reasonable in configuration, the whole lift cycle cost of the hybrid energy storage equipment is enabled to be the lowest on the basis of meeting safe, reliable and stable operation of the system, and the economy of the hybrid energy storage equipment in the microgrid is greatly 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 discloses a surface solar radiation calculation method based on deep learning which solves the problems that an existing method is long in calculation time and poor in universality and cannot be applied to cloud conditions. The method comprises the following steps of constructing an earth surface solar short wave radiation data set based on an atmospheric radiation transmission model; taking the surface solar short-wave radiation data set as a training sample; training through the neural networks to obtain a deep learning model, wherein the solar zenith angle, the aerosol opticalthickness, the atmospheric water vapor content, the cloud phase state, the cloud optical thickness, the cloud particle effective radius and the surface albedo are used as the neural network input layers, and the surface albedo, the surface downlink total solar radiation, the surface downlink direct solar radiation, the surface downlink diffused solar radiation and the atmospheric layer top upwardradiation are used as the neural network output layers. According to the method, the comprehensive, rapid and accurate calculation of the surface solar radiation is realized.

The invention discloses a method for simulating light scattering property of ice crystal particle. By the method, the problem that bubbles and impurity in the ice crystal particle in the prior art arenot considered to cause insufficient inversion accuracy. The method comprises the steps of building an ice crystal particle model; randomly adding a bubble and / or impurity model in the model, and adjusting conductivity and refractive index of the bubble and impurity model; calculating a scattering function and a scattering matrix by an approximate optical approximation method scattering program;calculating radiation values of an absorption channel and a non-absorption channel of a satellite sensor, cloud optical thickness and ice cloud particle effective radius by a RSTAR radiation transmission mode; building a lookup table according to the radiation values of the absorption channel and the non-absorption channel, the cloud optical thickness, the ice cloud particle effective radius and the ice cloud particle effective radius; and calculating the cloud optical thickness and cloud particle effective radius according to the radiation values observed by satellite and according to the lookup table. By the method, the inversion accuracy of the cloud particle effective particle and the cloud optical thickness is remarkably improved.

The invention discloses a full-polarization laser radar system used for detecting shapes of particles. The laser radar system comprises a polarization light generation system, a receiving system, a polarization analysis system and a data acquisition processor. The invention also discloses a detection method of the full-polarization laser radar system used for detecting shapes of particles. The detection method is characterized in that by use of the full polarization laser radar system to carry out detection, an atmosphere back scattering Miller matrix is obtained; and then the atmosphere backscattering Miller matrix carries out detection on atmosphere particle shapes. According to the invention, by use of all-directional linear polarization laser and circular polarization laser to detectaerosol particles, fine discrimination and detection are performed on the shapes of atmosphere particles; fine measurement is performed on cloud particles in the atmosphere; and the method is used foranalyzing ice water phase states of the cloud particles and particle guidance in cirrus cloud.

The invention discloses a terahertz and millimeter wave cloud radar data joint inversion method. The method comprises the following steps of: establishing a relationship among terahertz radar reflectivity factors, a millimeter wave radar reflectivity factors and cloud attenuation; establishing a relationship between the radar reflectivity factors of a terahertz frequency band and a millimeter wavefrequency band and cloud physical parameters, establishing a probability formula based on a Bayesian theory, iteratively operating the cloud physical parameters, and taking an error between a physical model value and an observed value as a criterion of iterative convergence to obtain an optimal solution; and iteratively calculating the backscattering cross section and attenuation cross section ofcloud particles according to the cloud physical parameters obtained by inversion, updating the function relationship between the radar reflectivity factors and the cloud attenuation to obtain a new inversion value, and taking the change of the cloud attenuation coefficient in iterative operation as a convergence condition to obtain a dual optimal solution of the cloud physical parameters. Data support is provided for climate prediction, weather forecast and atmospheric science research, and effective application of terahertz cloud radar and millimeter wave cloud radar in a meteorological observation system is promoted.

The invention relates to a method and a device for recognizing supercooled water. The method comprises steps: a membership function is built, and multiple measurement parameters in need of measurement are determined; the multiple measurement parameters are measured respectively through a millimeter-wave cloud radar, and multiple measurement values are obtained; the multiple measurement values serve as input parameters for the membership function respectively, multiple memberships are calculated and obtained, the phase state of a cloud particle is determined according to the multiple memberships, and the phase state membership in each phase state is calculated and obtained; the sizes of obtained phase state memberships in all phase states are compared, and a judgment result is obtained; and the judgment result is processed according to the supercooled water definition, and a supercooled water recognition result is obtained. According to the method and the device for recognizing the supercooled water, the recognition process is simple, convenient and easy to realize and is not limited by an observation condition, the recognition speed is quick, and the practicability is strong.

The invention discloses an airborne backscattering cloud particle detecting instrument, a meteorological detecting device and a cloud particle detecting method. The airborne backscattering cloud particle detecting instrument comprises a laser emitting module, a backscattered light detecting module and a signal detecting and processing module, wherein a laser light beam of the laser emitting moduleis changed into circularly polarized light through a circular polarizer, and is converged to a to-be-detected cloud particle via a first focusing lens; scattered light is changed into parallel lightthrough an optical 4f system, is split into two beams of linearly polarized light S and P via a quarter-wave plate, then is beam-split into the mutually perpendicular light S and P through a polarization beam splitting prism, and then is converged to the signal detecting and processing module by respective corresponding light S focusing lens and light P focusing lens; detected signals are sent bythe signal detecting and processing module to a signal amplification circuit respectively to be amplified, and then is subjected to sampling analysis by a signal collecting and processing circuit to determine the phase state and size which are corresponding to the to-be-detected cloud particle. The airborne backscattering cloud particle detecting instrument is used for solving the disadvantage that the phase state and size of a cloud particle cannot be accurately distinguished in a high-concentration circumstance.

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 invention provides an unmanned precipitation increase airplane. The unmanned precipitation increase airplane is provided with a cloud particle detection system and a cloud macroscopic imaging system, detected images and data are transmitted by an air-ground data transmission system to a ground control center in real time, atmospheric conditions are analyzed, and the meteorological detection function is achieved. The data and images detected by the unmanned precipitation increase airplane are analyzed, if the cloud layer has the artificial precipitation increase condition, an artificial precipitation increase command can be sent to the unmanned precipitation increase airplane, and finally the artificial precipitation increase function is achieved through a flame strip scattering deviceand a flame bomb scattering device.

The invention discloses a method for determining spectral distribution of large cloud particles of a water cloud, and solves the problems of poor inversion accuracy and low calculation efficiency. The method comprises the following steps: calculating a polarization reflectance look-up table, wherein the polarization reflectance look-up table contains polarization reflectance theoretical vectors; calculating a scattering angle of a pixel and a corresponding polarization reflectance observation value from satellite observation data; setting a space inversion resolution, and drawing the polarization reflectance values of which the corresponding scattering angles are within the range of 130-150 degrees to form observation vectors; with respect to effective radii of different cloud particles and effective variance discrete values of the cloud particles, performing curve fitting on the theoretical vectors to obtain a plurality of theoretical curves; performing curve fitting on the observation vectors to obtain an observation curve; and comparing the theoretical curves with the observation curve to obtain the theoretical curve most similar to the observation curve. The method disclosed by the invention has the advantages of high calculation efficiency, high calculation accuracy and small inversion unit area.

The invention discloses a three-dimensional cloud motion evolution method based on physics, belongs to the field of computer graphics, and can realize automatic evolution from an initial three-dimensional cloud shape motion to a target shape by taking two natural cloud images as input. The method comprises the following steps: firstly, respectively reconstructing a three-dimensional cumulative cloud model from two given cumulative cloud natural images, and carrying out particle sampling on a first three-dimensional cumulative cloud model to obtain cloud particle data; secondly, solving a thermodynamic equation, a state change equation and a motion equation of the cumulative cloud in an atmospheric motion process to realize a physical motion process of the cumulative cloud; thirdly, adopting the PBF method to keep the density of cloud particles unchanged in the movement process, and to guarantee incompressibility of the accumulated cloud in the movement process; then, performing surfaceparticle sampling on the target shape, and achieving coupling of cloud particles and the target shape in combination with a fluid-solid interaction strategy; and finally, adjusting an external forceapplied to the cloud in the movement process according to the movement states of the time frames before and after the cloud, and driving the physical movement process of the cloud until the final shape is consistent with the target shape.

Techniques for analysis and prediction of cloud particle distribution and solar radiation are provided. In one aspect, a method for analyzing cloud particle characteristics includes the steps of: (a) collecting meteorological data; (b) calculating solar radiation values using a radiative transfer model based on the meteorological data and blended guess functions of a cloud particle distribution (c) optimizing the cloud particle distribution by optimizing the weight coefficients used for the blended guess functions of the cloud particle distribution based on the solar radiation values calculated in step (b) and measured solar radiation values; (d) training a machine-learning process using the meteorological data collected in step (a) and the cloud particle distribution optimized in step (c) as training samples; and (e) predicting future solar radiation values using forecasted meteorological data and the machine-learning process trained in step (d).

The invention discloses a method for calibrating non-spherical particles by a polarization cloud particle detection system. The method performs calibration work on non-spherical particles (mainly icecrystals) in the atmosphere to confirm response curves and depolarization ratios of different non-spherical particles. The method for calibrating non-spherical particles by the polarization cloud particle detection system generates different ice crystals by using a split 20L hybrid cloud chamber, transports to a detection system by a continuous flow of nitrogen, obtains shapes and sizes of the icecrystals through the inkjet droplet observation system, further obtains the depolarization ratio of different non-spherical particles and the pulse amplitude of a detection channel signal, and establishes a database of different non-spherical particles, which can be used for subsequent detection of actual ice crystal particles.

The invention discloses a cloud particle signal acquisition and data transmission apparatus based on FPGA and a method thereof. The apparatus comprises an analog quantity acquisition unit, a FPGA processing unit, a serial port communication module, a clock generation module, and a power supply module; the FPGA processing unit is connected with the analog quantity acquisition unit and the serial port communication module; and the analog quantity acquisition unit comprises a light electric signal transition module, a signal processing module and a high speed AD transition module which are connected in order. The high speed AD transition chip and FPGA programming control increase the data acquisition speed, and the high speed acquisition requirement on cloud micro physical parameters under airborne condition.