432 results about "Lightning" patented technology

The invention discloses a thunder and lightning early warning method based on atmospheric electric field networking monitoring. The method comprises the following steps: collecting multi-point electric field intensity data in a region in real time through a high-density electric field sensor network, and constructing an electric field intensity distribution matrix; for the constructed electric field intensity distribution matrix, space-time evolution characteristics of lightning activities are extracted, and lightning occurrence probability distribution is generated; acquiring temperature, humidity and air pressure parameters from multi-source meteorological data, performing data fusion with the generated thunder and lightning occurrence probability distribution, and constructing a comprehensive environment characteristic data set; and for the constructed comprehensive environment characteristic data set, calculating a comprehensive risk index, and if the index exceeds a preset thunder and lightning triggering threshold, etc. According to the lightning early warning method, the distribution matrix is constructed through the high-density electric field network, the spatial-temporal characteristics are extracted to generate the initial probability, and the physical rationality and the environment false alarm resistance of early risk identification are remarkably improved through fusion with the multi-source meteorological data.

The invention provides a lightning proximity prediction method based on a space-time separation convolutional neural network. The method comprises the following steps: S1, acquiring satellite infrared brightness temperature observation data and lightning positioning data; s2, performing spatial resolution adjustment and standardization processing on the satellite infrared brightness temperature observation data; gridding and de-noising processing is carried out on the lightning positioning data; s3, defining a prediction task; s4, establishing a space-time sequence prediction model; based on the processed data, storing the processed data in a numpy file format according to a time point sequence, dividing the processed data into a training set, a verification set and a test set, and loading the training set, the verification set and the test set to a space-time sequence prediction model for model training to obtain an optimization model; and based on the prediction task, using the optimization model to carry out lightning approaching prediction to obtain lightning prediction data. According to the method, the development of cumulus cloud is captured by using satellite infrared brightness temperature observation data and brightness temperature difference data, so that the problem that thunder and lightning inception cannot be effectively predicted is solved.

The invention discloses a tower disaster situation sensing and early warning system based on wireless communication, and relates to the technical field of tower disaster monitoring and early warning. The tower top monitoring module is integrated with a multi-dimensional sensor, adopts a wind-solar complementary power supply and self-calibration mechanism, and intelligently adjusts data acquisition; the timed inspection module optimizes an inspection path and identifies 10 types of defects by using an unmanned aerial vehicle carried laser radar and an AI model; the meteorological early warning module combines a micrometeorological model and a random forest algorithm to dynamically correct a threshold value, and associates multi-source data to trigger early warning; the self-protection module integrates lightning protection and block chain technologies to guarantee data security; according to the invention, the monitoring precision and the communication reliability are obviously improved, the early warning response time is shortened to be within 30 seconds, and the power grid disaster prevention capability is enhanced.

The invention relates to a lightning potential forecasting method and system based on a random forest. The method comprises the following steps: (1) collecting and preprocessing multi-source meteorological data; (2) feature extraction: cloud picture texture and shape features are extracted from satellite data, and echo intensity, top height and vertical development speed features are extracted from radar data; (3) constructing and optimizing a model; and (4) early warning thunder and lightning. The method has the advantages that the random forest serves as a typical representation of the ensemble learning algorithm, and the core of the random forest is to integrate prediction results of a plurality of decision trees. According to the integration mode based on Bagging, multi-dimensional feature information can be fully integrated, and the overfitting problem which is likely to happen to a single decision tree is effectively restrained. In a thunder and lightning potential forecasting scene, the algorithm can accurately capture a complex nonlinear relationship between meteorological elements and thunder and lightning potential by adaptively learning association between a large amount of historical meteorological data and thunder and lightning events, so that the forecasting accuracy is remarkably improved.

The invention discloses a lightning arrester on-line monitoring method and device, and relates to the field of intelligent monitoring, and the method comprises the steps: firstly collecting original current and voltage waveform data, carrying out the frequency domain decomposition operation, then introducing an intelligent prediction mechanism, carrying out the intelligent prediction of a phase error based on the fundamental voltage phase, temperature change and harmonic characteristics, and finally, carrying out the calculation of the phase error. And performing phase angle correction operation and preliminary calculation of resistive current on the fundamental current and voltage by using the corrected phase information, and introducing a historical data smoothing algorithm to perform noise reduction optimization on a result. And finally, comparing the analyzed and processed resistive current with a preset threshold value, and judging whether an alarm prompt is generated or not. Therefore, real-time evaluation and abnormal alarm of the operation state of the lightning arrester are realized, so that a powerful guarantee is provided for safe operation of a power system.

The invention discloses a meteorological disaster early warning response method and system based on a meteorological early warning aircraft, and the system comprises a data collection module which is used for constructing a database containing the real-time meteorological data, the terrain data, the historical disaster data and the early warning aircraft operation data; the multi-disaster terrain adaptation analysis module is used for analyzing waterlogging and gale comprehensive risks by using a synchronous superposition model in plains and analyzing landslide and thunder-gale chain risks by using a time sequence chain model in mountainous areas through a double-branch fusion neural network; the early warning response strategy generation module is used for generating differentiation strategies according to regional risks and terrains; and the terminal interaction module pushes information and receives feedback. The system dynamically generates protection guidance for different geographic features such as a plain high-risk area and a mountainous area high-risk area through multi-source meteorological data integration and analysis, and improves the timeliness and coverage of early warning information.

The invention discloses a hail prediction method and device, a medium and a program product, and relates to the technical field of meteorology, and the method comprises the steps: obtaining a neural network model; acquiring historical lightning characteristic variable data and historical hail characteristic variable data; dividing the historical lightning characteristic variable data and the historical hail characteristic variable data into a training set and a verification set of corresponding characteristic variables; training the neural network model through the training set and the verification set of the corresponding feature variables, and taking the trained neural network model as a target neural network model; acquiring current lightning characteristic variable data; determining a dynamic weighting loss function according to the target neural network model; and predicting hail weather according to the current lightning characteristic variable data and the dynamic weighted loss function to obtain hail prediction parameters. According to the technology provided by the invention, misjudgment caused by forecasting the hail by independently using the radar reflectivity factor is reduced, and the hail forecasting precision is improved by indicating the factor through the lightning characteristic data.

The invention discloses a multi-source data fusion image sequence generation method and system based on space-time diffusion, and belongs to the technical field of image sequence generation, and the method comprises the steps: taking an existing satellite remote sensing image and an existing radar echo reflectivity image as input, taking an existing lightning drop point space distribution diagram as output, and training a synchronous mapping network; training a prediction network through the existing satellite remote sensing image and the existing radar echo reflectivity image to obtain a future satellite remote sensing image and a future radar echo reflectivity image; inputting a future satellite remote sensing image and a future radar echo reflectivity image into the trained synchronous mapping network to obtain a first prediction map of a future lightning drop point spatial distribution map; inputting the existing lightning drop point spatial distribution map into the space-time diffusion model to obtain a second prediction map of the future lightning drop point spatial distribution map; and the first prediction image and the second prediction image are spliced to obtain a final prediction image sequence of the future lightning drop point spatial distribution map, so that the prediction precision and robustness are remarkably improved.

The invention discloses a lightning disaster early warning method based on meteorological data. The method comprises the following steps: fusing meteorological data and topographic data, and generating a spatial-temporal distribution data set of atmospheric parameters and topographic features in a complex mountainous area environment through weighted stacking and spatial-temporal interpolation methods; analyzing an electromagnetic wave multi-path propagation effect according to the spatial-temporal distribution data set, calculating an attenuation coefficient with a high-frequency component greater than 1 gigahertz and a propagation loss with a low-frequency component less than 1 gigahertz, and generating a spectrum degradation preliminary quantization data set; and if a high-frequency component attenuation coefficient in the spectrum degradation preliminary quantization data set exceeds an attenuation threshold value, optimizing propagation path parameters through a genetic algorithm, generating a corrected spectrum degradation model and the like. The precision and the real-time performance of lightning disaster early warning in the complex mountainous area can be remarkably improved, and the disaster risk is effectively reduced.

The invention discloses a lightning approaching trend forecasting method and system. The method comprises the steps of obtaining cloud cover space distribution and a time sequence, extracting a first cloud cover texture feature vector, and generating a cloud cover hierarchical feature matrix; performing dimensionality reduction on the first cloud cover texture feature vector to generate a second cloud cover texture feature vector, and generating a regionalized cloud cover distribution feature set through clustering in combination with the cloud cover hierarchical feature matrix; extracting humidity, temperature and wind field data to generate a lightning trigger factor data set, and analyzing a regionalized cloud cover distribution feature set by adopting a time sequence analysis method and an optical flow method to form a cloud cover dynamic feature set; and according to the cloud cover dynamic feature set and the cloud cover hierarchical feature matrix, in combination with a pre-established lightning association cloud type label, generating a lightning intensity grade classification feature set and the like. According to the invention, through deep fusion and dynamic optimization of spatial-temporal characteristics, the precision and timeliness of lightning prediction are significantly improved, and efficient technical support is provided for meteorological disaster early warning.

The invention provides a meteorological station power supply line lightning stroke fault positioning method, system and device and a medium. The method comprises the following steps: firstly, synchronously acquiring transient voltage and current traveling waves based on a preset multi-stage lightning protection area boundary to obtain multi-source transient data; performing cross-measuring-point fusion reconstruction on the acquired multi-source transient data, and marking waveform characteristics of the boundary of the protection area to obtain effective waveform data; then, calculating dynamic wave impedance, and determining a wave impedance break variable in combination with a boundary impedance calibration value; and through the reconstructed effective voltage waveform data or effective current waveform data, the traveling wave arrival time is calibrated by adopting a frequency-variable wave velocity model and wavelet transform. And finally, determining the positioning value of the lightning stroke fault at the access point of the meteorological station terminal equipment according to the frequency-varying wave velocity, the calibrated traveling wave arrival time and the wave impedance break variable, and outputting the position information of the lightning stroke fault in the multi-stage lightning protection area in combination with a preset multi-stage lightning protection area boundary position mapping table. According to the scheme, the lightning stroke fault can be accurately positioned in the multi-stage lightning protection area.

The invention provides a lightning activity prediction method based on Doppler radar data and lightning activity correlation analysis, and relates to the field of lightning early warning. The method comprises the steps of performing normalization processing on Doppler radar data, and calculating radar centroid trajectory data based on the clustered Doppler radar data; synchronously extracting the ground-to-ground lightning data according to the radar timestamp, and generating a ground-to-ground lightning centroid track based on the clustered ground-to-ground lightning data; calculating a trajectory position similarity value and a trajectory direction similarity value under different combined reflectivity; and carrying out correlation comparison analysis on the trajectory position similarity value and the trajectory direction similarity value corresponding to each combined reflectivity, and selecting a target combined reflectivity meeting a preset comparison condition in the combined reflectivity to carry out lightning activity trajectory prediction. According to the invention, the problem that the lightning activity prediction accuracy is low due to the fact that the traditional lightning early warning technology often has false alarm and missing alarm under the condition of complex topographic relief or multi-series convection superposition is solved.

The utility model discloses a lightning protection circuit and a power converter, and relates to the technical field of power electronics. According to the lightning protection circuit, for the condition that a capacitor parallel branch in a bus capacitor circuit comprises a first capacitor, a second capacitor and an inductor, and the first capacitor is connected with the inductor in series and then connected with the second capacitor in parallel, a lightning protection device is arranged to be connected with the inductor in parallel; in the lightning stroke process, the voltage at the two ends of the inductor exceeds the action voltage of the lightning protection device, so that the lightning protection device is broken down, and the voltage at the two ends of the inductor is clamped at the voltage drop after the lightning protection device is broken down, so that overlarge voltage cannot be formed on the second capacitor; therefore, the problem of voltage oscillation caused by current backflow at the lightning stroke moment can be weakened, the voltage stress borne by a corresponding power device in a post-stage circuit is reduced, and the corresponding power device is effectively protected.

The invention provides a severe convective weather early warning method and system based on monomer identification and lightning jump, and is applied to the technical field of data processing. The method comprises the following steps: processing high-precision lightning positioning data and meteorological radar data to generate convection monomer characteristic parameter information; processing the ground observation data to generate ground meteorological element associated information; processing the convective monomer characteristic parameter information and the ground meteorological element association information to generate severe convective monomer identification result information; processing the high-precision lightning positioning data based on the strong convection monomer identification result information to generate lightning jump judgment information; and processing the severe convection monomer identification result information and the lightning jump judgment information based on the target severe convection weather early warning model to generate severe convection weather early warning result information.

The invention relates to a lightning trip risk assessment method and system for a current collection line of a wind power plant station, and belongs to the technical field of lightning protection of a power system, and the method comprises the following steps: collecting a multi-dimensional data set of a target wind power plant station, the multi-dimensional data set comprising lightning activity parameters, landform data, equipment structure parameters and historical lightning fault data; constructing a three-dimensional electromagnetic transient model of the current collection line, wherein the three-dimensional electromagnetic transient model of the current collection line integrates an electromagnetic transient program EMTP counterattack simulation model, a time domain finite difference method FDTD induction lightning shielding model and a terrain correction electrical geometric model EGM; calculating lightning trip-out rates based on the multi-dimensional data set and the three-dimensional electromagnetic transient model of the current collection line, wherein the lightning trip-out rates comprise an impact trip-out rate, a shielding failure trip-out rate and an induction lightning trip-out rate under fan shielding; and carrying out risk grading on the tower according to the lightning trip-out rate, establishing a terrain-tower type coupling risk assessment system, and outputting a risk assessment result.

The invention discloses a power distribution network line fault positioning method, device and equipment, and relates to the technical field of power distribution network line fault positioning, and the method comprises the steps: obtaining operation data and lightning ground lightning data; feature extraction is carried out on the operation data, spatial-temporal feature mapping is carried out on the lightning and ground lightning data, and multi-source feature parameters are generated; probabilistic reasoning is carried out on the input multi-source characteristic parameters through section agents deployed in a distributed mode and Bayesian network submodules of the section agents, and real-time fault probability values of all independent sections of the power distribution network are output; and taking the real-time fault probability value of each independent section as an input, dynamically coordinating an output result of each agent through a Nash equilibrium strategy, and generating a global consistency fault positioning decision. The method is used for solving the problem that a traditional line fault positioning method is difficult to effectively fuse heterogeneous data and is difficult to coordinate local judgment conflicts.

The invention relates to a multi-mode power transmission line state monitoring method and system based on thunder and shooting fusion, and belongs to the technical field of circuit monitoring. The method comprises the following steps: acquiring historical multi-mode power transmission line data, and constructing a lightning-shooting fusion power transmission line monitoring set according to the historical multi-mode power transmission line data; a power transmission line state monitoring model is obtained through multi-sensor fusion modeling according to the lightning shooting fusion power transmission line monitoring set; the real-time multi-mode power transmission line data is acquired, the real-time multi-mode power transmission line data is processed through the power transmission line state monitoring model to obtain the power transmission line state label, high-precision, all-weather and low-cost power transmission line state monitoring is achieved, and efficient and reliable technical guarantee is provided for safe operation of a power grid.

The utility model relates to a device for detecting lightning protection conductivity of an offshore wind turbine generator, which comprises a support rod and a resistance detector, one end of the support rod is connected with a tower drum, the other end of the support rod extends outwards and is provided with a conducting piece, and the conducting piece is positioned on the motion trail of a lightning arrester; and two terminals of the resistance detector are respectively connected with the conducting piece and the grounding wire through a first lead and a second lead. According to the utility model, the supporting rod extends out of the window in the tower drum, so that the conducting piece is positioned on the motion trail of the lightning arrester, and the resistance detector, the conducting piece, the blade, the cabin and the tower drum form a complete loop through the first lead and the second lead, so that the lightning protection conductivity detection of the blade of the wind turbine generator can be completed. The purposes of reducing the operation risk coefficient, shortening the detection period and improving the working efficiency are achieved.

The invention relates to the field of data processing, in particular to a method and system for analyzing the performance of a lightning protection device in a flammable and explosive place, and the method comprises the steps: firstly collecting resistance, temperature and humidity data in a preset number of days, and carrying out the preprocessing to construct a target resistance time sequence of each day; thirdly, clustering the days based on the day and night temperature difference, and dividing a plurality of periodic windows; secondly, decomposing the target resistance time sequence of all days, calculating the periodicity level and the abnormal degree of each layer, converting the periodicity level and the abnormal degree into weights, and performing weighted summarization to obtain a performance evaluation value; finally, if the value is smaller than or equal to a preset abnormal threshold value, it is judged that the device is abnormal. According to the method, the periodicity level and the abnormal degree of resistance change are comprehensively considered, the performance of the lightning protection grounding device can be comprehensively and accurately evaluated, potential abnormity can be found in time, and misjudgment or missed judgment caused by single-factor evaluation is avoided.

The invention discloses a lightning fire occurrence risk grade forecasting method and device and a storage medium. Belongs to the technical field of forest fire prediction. The method comprises the following steps: acquiring hour-scale real-time data of a target area; extracting a real-time numerical value corresponding to each key factor in a predefined key factor set from the real-time data; inputting the real-time numerical values corresponding to all the key factors into a pre-trained risk level prediction model to obtain a lightning fire occurrence probability corresponding to each lightning in the target area; and according to the occurrence probability of the lightning fire, determining the risk level of the lightning fire caused by each lightning in the target area. Therefore, scientific screening of key factors of lightning fire forecasting is realized, hour-scale real-time data acquisition is adopted, and data processing and model forecasting logic adapted to hour-scale dynamic change are adopted, so that forecasting accuracy and real-time performance are effectively improved.

The invention is suitable for the technical field of distribution network risk assessment, and provides a distribution line risk assessment method and system based on a lightning and associated disaster coupling probability model, and the method comprises the steps: obtaining meteorological data, geographic data and distribution line parameters of a target region; calculating a first fault probability of the lightning disaster lower line section or the tower and a second fault probability of the associated disaster lower line section or the tower; combining the disaster type conversion probability and the disaster accompanying time coefficient, determining the third fault probability of the lower segment or the tower of the comprehensive disaster, calculating the failure probability of the distribution line, and screening a typical fault scene set by using the system information entropy; calculating a line fault consequence value, and generating a line risk index in combination with the failure probability; and finally, generating a target risk line list according to the sorting of the line risk indexes. Based on the influence on the line fault probability under the condition of expected associated disasters of lightning disasters, the accuracy of line fault prediction in extreme weather is improved.

The invention relates to the technical field of live detection, in particular to a power distribution gap lightning arrester live detection result compensation algorithm, which comprises the following steps: acquiring a voltage signal and dividing a period section, extracting waveform characteristics to generate a mark set, identifying trend reversal to construct a sudden change section list, analyzing intersection point spacing to form an abnormal set, and calculating a power distribution gap lightning arrester live detection result. And tracking trend deviation to determine correction data, mapping a reference path to reconstruct a reference baseline, and completing conduction state correction recording. According to the method, the detection data of the operation state of the power distribution gap lightning arrester is processed, waveform segmentation marks of a continuous period are constructed, a reversal trend path and slope abrupt change characteristics are combined, potential interference is identified, an abnormal fluctuation area is formed, and a voltage recovery deviation trend is constructed and analyzed through a front window and a trend line segment; and the offset starting and ending points are positioned and the reference path is corrected, so that the reliability of detection data, the accuracy of state judgment and the adaptability of operation conditions are effectively improved.

The invention relates to the field of thunder and lightning early warning, and discloses an intelligent thunder and lightning early warning system for a large oil and gas storage base, which consists of a multi-source monitoring module, a data processing and analyzing module, an early warning module and a linkage protection module, wherein the multi-source monitoring module is responsible for collecting data from multiple dimensions, and the data processing and analyzing module is used for preprocessing the data and calculating the probability of lightning occurrence through a specific model; the early warning module sends out a corresponding early warning signal according to the danger level, and the linkage protection module automatically triggers a corresponding protection measure according to the early warning signal; by adopting multi-source data fusion, probability model analysis and a hierarchical linkage mechanism, the problems of false alarm and missing alarm existing in a traditional single monitoring method are effectively solved, accurate early warning and intelligent protection of the oil and gas storage base are achieved, and the thunder and lightning safety protection capacity of the large oil and gas storage base is remarkably improved.

The invention provides an intelligent temperature measurement system of a temperature measurement type overhead transmission line image video monitoring device, and the system comprises a dual-light image fusion module which is used for generating a fusion image of an infrared image and a visible light image; the target detection module is used for identifying a target object in the image by adopting a target detection algorithm; the intelligent distance measuring module is used for calculating the actual distance between the device and the target; the environment parameter acquisition module is used for acquiring environment temperature data of an area where the cable terminal or the lightning arrester is located; the temperature measurement correction module is used for correcting an infrared temperature measurement error by using a multivariate nonlinear regression model based on Lasso regularization and outputting a corrected temperature value; and the image splicing module is used for generating a complete infrared image covering a plurality of cable terminals or lightning arresters. According to the invention, the problems of poor image information acquisition capability, insufficient target detection precision, large temperature measurement error, limited field angle coverage, single alarm mechanism, low system intelligence degree and the like in the prior art can be solved.

The utility model provides a lightning impulse protection device for a transformer, and relates to the technical field of lightning arresters, the lightning impulse protection device for the transformer comprises a mounting plate, two ends of the mounting plate are respectively provided with a protection mechanism, the protection mechanism comprises two rectangular blocks, the inner walls of the two rectangular blocks are rotatably connected with a rotating shaft, and the rotating shaft is connected with the mounting plate. A rotating shaft is arranged on the outer side of the screw rod, a coil spring is arranged on one side of the rotating shaft, an L-shaped rod is fixedly connected to the outer surface of the rotating shaft, and a piston block is rotationally connected to one end of the screw rod. The piston block slides on the inner wall of the rectangular groove by rotating the screw rod, so that the airbag sheet deforms and expands outwards, the outer side of the joint of the lightning arrester body and the high-voltage line is wrapped and protected, the influence of rain and sun on the outer side of the joint of the high-voltage line and the lightning arrester body is reduced as much as possible, the service life of the lightning arrester body is prolonged, and the use effect of the lightning arrester body is improved.

The invention relates to the technical field of meteorological disaster monitoring and early warning and numerical forecasting fusion, in particular to an extreme gale weather forecasting method based on a weather forecasting large model, which comprises the following steps: acquiring a numerical weather forecasting three-dimensional physical field, a weather radar, a weather satellite and ground meteorological observation and assimilating the numerical weather forecasting three-dimensional physical field into a consensus field; time advances, sinking potential energy and cold pool diagnosis are obtained through a micro-downburst calculation program, coarse-resolution gust is formed through boundary layer similarity mapping and a hysteresis kernel, and a fine-scale base map is generated under cold pool frontal surface limitation through optimal transmission of advection constraint; the conditional diffusion probability generation model outputs pixel gust distribution and a threshold exceeding probability and extracts a wind damage polygon; radar, satellites, lightning and ground gust are fused, monotonous normalized flow calibration is used, parameters are updated through intersection-to-parallel ratio and shape-preserving coverage inspection and online amplitude limitation, and the credibility of spatial positioning, occurrence time and probability description is improved.

The invention relates to the technical field of atmospheric science detection, in particular to a lightning radiation source positioning method based on multi-station synchronous observation. Comprising the following steps: synchronously acquiring lightning broadband electromagnetic signals by multiple stations and performing time-frequency analysis; by calculating indexes such as cross-station coherence and interference level, high-quality frequency points are intelligently screened out to suppress noise and interference; reconstructing a narrow-band signal for each high-quality frequency point and performing high-precision time difference (TDOA) estimation by adopting an improved generalized cross-correlation method; and carrying out weighted fusion on TDOA measurement values of a plurality of high-quality frequency points, carrying out optimization solution by adopting a Grid Search algorithm, and finally obtaining a three-dimensional coordinate of lightning. Through intelligent screening of high-quality frequency points, accurate time difference estimation, optimization of a positioning algorithm, multi-band information fusion and intelligent processing, the defects that a traditional single-band positioning method is prone to interference and limited in precision are effectively overcome, the lightning positioning precision, the anti-interference capability and the reliability are remarkably improved, and the method is suitable for popularization and application. And the lightning positioning requirements in various environments are met.

The present application relates to the technical field of lightning arresters, and discloses an environment-adjusted lightning arrester, which comprises a protective shell, a lifting platform slidingly arranged in the protective shell, a lightning arrester arranged on the lifting platform, a triggering member arranged below the protective shell and used for driving the lightning arrester to automatically contract, a lightning sensor arranged on the protective shell and used for detecting lightning activities, an opening and closing member arranged on the protective shell and used for being opened when the lifting platform is lifted and being closed when the lifting platform is lowered, so as to control the exposure or hiding state of the lightning arrester, and a mounting member arranged on the protective shell and used for fixing the protective shell on a crossbar. The triggering member based on wind force is arranged, so that when the wind speed is large, the lightning arrester body can be automatically contracted, the key parts such as the insulating umbrella skirt can be retracted into the protective shell, and the wind sand erosion and the insulation aging can be prevented.

The invention provides a lightning fall area identification method based on a wind cloud satellite temperature profile and an atmospheric instability index, and relates to the technical field of weather forecast, and the method comprises the steps: obtaining vertical layering temperature profile data, atmospheric instability index data and satellite lightning positioning data of a wind cloud satellite; the vertical stratification temperature profile data, the atmospheric instability index data and the satellite lightning positioning data are preprocessed, and the preprocessed vertical stratification temperature profile data, the preprocessed atmospheric instability index data and the preprocessed satellite lightning positioning data are obtained; and on the basis of the preprocessed vertical stratification temperature profile data, atmospheric vertical temperature gradient derivative elements are obtained by calculating atmospheric vertical temperature gradients between different air pressure layers. According to the method, intelligent identification and auxiliary decision-making of the lightning falling area can be realized, and meanwhile, technical support is provided for satellite-to-ground lightning observation data quality evaluation and control.

The invention relates to the technical field of lightning data processing, in particular to a lightning wave generation method and system based on a diffusion model. A diffusion model is adopted to generate lightning wave data, a denoising neural network adopted in the reverse diffusion process is obtained by improving a UNET model structure, and the improvement mode is that a wavelet attention unit is added after each down-sampling and before each up-sampling. According to the method, the denoising neural network is improved, attention technology wavelet transformation is combined, multi-scale transformation is captured at the same time, the detail capturing capacity of the model is improved, particularly, high-frequency components are captured, the model is helped to better reserve key features of lightning waves, and therefore the quality of the diffusion model applied to a lightning wave generation task is improved. The defect that a diffusion model is directly applied to lightning waves in the prior art is overcome.