86 results about "Storm" patented technology

The invention discloses an ionosphere TEC forecasting method, system, medium and equipment fused with a geomagnetic field, and belongs to the field of ionosphere TEC forecasting, the method comprises the following steps: obtaining current ionosphere TEC grid data, solar activity index data and global geomagnetic field observation data, and constructing to obtain multi-channel fusion data; based on a preset ConvLSTM model, processing the multi-channel fusion data, and outputting an ionized layer TEC forecast result; wherein the ConvLSTM model is obtained by training an input sequence in historical multi-channel fusion data and a corresponding target sequence; the input sequence is composed of multi-channel fusion data of a plurality of consecutive time steps, and the target sequence is composed of ionized layer TEC grid data immediately after the input sequence. By implementing the method, the forecasting precision of the ionized layer TEC under complex space weather conditions such as magnetic storm can be improved.

The invention discloses a rainstorm flood risk early warning method and system based on machine learning and multi-source data fusion, and belongs to the technical field of flood prediction.The method comprises the steps that multi-source sample data is constructed based on flood disaster historical data; the multi-source sample data type comprises rainfall characteristic data, hydrological characteristic data, landform characteristic data, earth surface attribute characteristic data and social economic characteristic data; an XGBoost ensemble learning algorithm is adopted to construct a risk prediction model, and training and evaluation are carried out based on multi-source sample data; historical rainstorm flood event records are taken as labels in the training process; performing quantitative and application verification on the risk prediction model, and calibrating a risk level probability output by the risk prediction model based on a risk level distribution probability of historical disaster situation data; performing real-time estimation based on the optimized risk estimation model; and generating a spatial refined rainstorm flood risk grade early warning map in a future preset time period according to an estimation result in a rolling manner.

The invention discloses an extreme rainfall prediction method based on deep learning and numerical calculation, and the method comprises the following steps: employing a random forest classification method to process a rainfall data sequence and multi-element physical quantity data, employing a long-short-term memory network to optimize the processed data, and obtaining an optimized multi-element association sequence; performing feature recognition on the optimized multi-element association sequence, and performing dynamic association modeling and iterative parameter updating on multi-element expression to obtain prediction model input of comprehensive expression; performing regression and deviation correction on the spatial-temporal distribution data of the extreme rainfall event based on prediction model input of comprehensive expression, and performing multi-element dynamic association integration on the residual error part of the multi-scale characteristics by adopting a feedback cycle mechanism to obtain a final rainstorm event judgment basis; and based on a final rainstorm event judgment basis, carrying out evolution process simulation on real-time environmental factor updating data, and determining an accurate output sequence of extreme rainfall prediction.

The invention relates to the technical field of thunder and lightning mode recognition, and discloses a thunder and lightning intelligent target early warning method and system for a local key target, and the method comprises the steps: collecting target feature description, estimating storm motion information based on lightning positioning data and radar echo images at continuous moments, and carrying out the recognition of a thunder and lightning mode. And generating a risk corridor in the upstream direction of each target area, and forming a target area around the target area in combination with the risk corridor. Unified spatio-temporal data is obtained, spatio-temporal feature extraction is carried out to obtain storm features, cross-modal correlation selection and weighting are carried out on the storm features with target feature description as a drive, and target features are constructed. And generating an early warning result in a predetermined time window according to the target feature. And when the thunder risk probability reaches an early warning threshold and the spatial risk distribution intersects with the buffer range of the target area, generating targeted early warning information. According to the invention, thunder and lightning targeted early warning is realized, the hit rate is improved, and false alarms are reduced.

A Surface-affixed, Storm-Resistant Containment Unit involves a shelter structure, with internally-mounted photovoltaic solar panels, and movable doors which may be ‘closed’ to protect the photovoltaic solar panels from storm-related damage, e.g. hail, extreme wind and airborne debris. When weather conditions improve, the movable doors may be ‘opened’, allowing sunlight to strike the undamaged photovoltaic solar panels, and renewable energy production to resume. These Storm-Resistant Containment Units may be installed, and electrically connected in multiples to comprise a storm-resistant, commercially-sized, renewable power generating station (or ‘Micro-Grid’) for use in geographic areas prone to severe storms and hurricanes. Such storm-resistant, commercially-sized, power generation station may be advantageously applied at existing ‘Brown-Field’ industrial sites that have existing, unused electrical-grid infrastructure.

The utility model relates to the technical field of box-type transformer substations, in particular to a dustproof box-type transformer substation shell which comprises a shell body, ventilation grooves are formed in the two sides of the shell body, a plurality of rotating shafts are rotationally installed in the ventilation grooves, one end of each rotating shaft and one end of a louver board are fixedly installed, a vertical groove is formed in the shell body, and the louver board is fixedly installed in the vertical groove. And the other end of the ventilation groove penetrates through the vertical groove and is provided with a worm gear, a worm meshed with the worm gear is rotationally installed in the vertical groove, and a protection assembly for protecting the worm gear and the worm is arranged in the vertical groove. According to the utility model, the worm is rotated to enable the worm gear to drive the rotating shafts to rotate, so that the louver boards can be driven to rotate, in case of heavy rain or sand storm, the louver boards rotate downwards to relatively seal the ventilation slots, so that rainwater or sand dust entering the box transformer substation can be reduced, and the plurality of rotating shafts rotate simultaneously and the louver boards rotate synchronously through the meshing of the worm and the worm gear, so that the box transformer substation is prevented from being damaged. And one-by-one adjustment is not needed.

The invention discloses a processing method and system for a ship intelligent navigation scene, and relates to the technical field of ship intelligent navigation, and the method comprises the following steps: carrying out the continuous waveform analysis of an energy return path of a laser ranging link based on the sudden increase of the density of seawater suspended particles caused by the frontier of a storm, constructing a particle disturbance recognition zone, and carrying out the recognition of the particle disturbance; generating a disturbance identifier carrying an energy rebound mode characteristic according to an analysis result; and expanding the ranging pulse to a time domain by using the disturbance identifier, performing pulse form reconstruction on an energy abnormal section of the ranging pulse, so that the ranging pulse still keeps a stable main peak structure under the influence of energy rebound, and outputting a stable main peak waveform after pulse form reconstruction. According to the invention, through constructing a disturbance identification and form reconstruction mechanism, continuous restoration and smooth output of the distance measurement signals are realized, and the stability and anti-interference performance of distance sensing are improved; and through approaching artifact weakening and gradual change operation control, excessive operation is prevented, and stable course and avoidance safety of the ship in a storm environment are ensured.

This invention provides a peak-scale response analysis method based on nested sub-basin division. By constructing a nested sub-basin structure controlled by area thresholds, and based on a unified design storm conditions and hydrological model parameter system, the method calculates peak discharge under different scale conditions by only changing the sub-basin division scale. It also establishes a logarithmic decay function model between peak discharge and the number of sub-basin units, achieving a quantitative expression of peak-scale response. Furthermore, by comparing and analyzing the scale decay coefficients under different design frequencies, the method quantifies the sensitivity of peak discharge to changes in the division scale. This method forms a complete technical process from data acquisition, structure construction, control variable setting, model running to function modeling and sensitivity analysis. It features a clear logical closed loop, strong repeatability, and good generalization, and does not depend on specific hydrological model software or specific watershed conditions. Under the premise of meeting the unified storm input and nested division principles, it can be widely applied.

The application discloses a kind of disaster-causing rainstorm space-time characteristic quantitative description method, comprising: obtaining the time series rainfall grid data and basic geographic environment data of target area;Based on time series rainfall data, space-time clustering analysis is carried out, and the storm object and its physical properties are extracted every time;Establish the correlation of adjacent time storm object, construct storm evolution track, and calculate space-time evolution characteristics;Based on storm object and storm evolution track, combined with basic geographic environment data, calculate storm-environment coupling disaster-causing characteristics;Output disaster-causing rainstorm space-time characteristic vector containing physical properties, space-time evolution characteristics and storm-environment coupling disaster-causing characteristics.The application realizes the leap from static statistical description to dynamic disaster-causing mechanism coupling by constructing space-time evolution vector field and storm-river topological parameters, effectively improves the accuracy of disaster warning.

This invention relates to a method for predicting sandbar response under the combined effects of water level and waves, considering hysteresis, during storms. The method includes: starting with initial sandbar morphology data of a target shoreline during a specific storm event, using a sandbar evolution model considering hysteresis to predict sandbar response, and outputting a predicted curve of sandbar position change throughout the storm process. The sandbar evolution model calculates storm dynamic forcing based on historical storm hydrodynamic data, establishes a model relating relaxation timescales to storm dynamic forcing, obtains a relaxation timescale characterizing the hysteresis characteristics of the sandbar response, and establishes a model relating the sandbar equilibrium position to hydrodynamic forcing based on historical hydrodynamic forcing data and sandbar position changes, obtaining... t The sandbar equilibrium position at any given moment. This invention can more accurately simulate sandbar behavior throughout the entire storm process, especially during the attenuation phase, significantly improving the practicality and reliability of sandbar response prediction throughout the entire storm process (including the aftereffect period).

The application discloses a wind power generation site selection method based on ancient storm deposition background and relates to the field of power generation site selection, which comprises the following steps: setting a unified space reference, forming an input data set, performing wind source basin assimilation fusion, generating modern wind field three types of grids, and configuring a modern wind field deposition response calibration reference domain. Long-term wind direction and wind speed prior are established by using storm deposition records and direction evidence, annual uncertainty caused by only relying on short-term wind measurement is reduced, hard constraint filtering is formed by using soft sediment deformation risk coding and boundary stability marking, a penalty term is introduced into scoring, ground investigation and construction stage risks are reduced, candidate area output synchronously gives evidence chain index and uncertainty level, short-term wind measurement review, ground investigation review and deviation backwriting self-calibration iteration are performed, and finally, site selection achievement package containing superimposed graph and evidence chain list is solidified, so that site selection decision transparency and landing efficiency are improved.

This invention discloses a hail identification and tracking method and system for the entire life cycle of hail embryos, relating to the field of meteorological detection. The method includes: S1 acquiring dual-polarization radar volume scan data; S2 identifying hail embryo particles; S3 determining whether the hail embryo particles are new particles, and if so, creating a life profile; S4 tracking target particles in spatiotemporal correlation and updating the life profile; S5 determining whether the target particles have transformed into hail; S6 acquiring the current life profile of the hail particles; S7 determining whether hail precipitation conditions have been triggered, and if so, proceeding to S8, otherwise returning to S1; S8 analyzing the location of the precipitation area; S9 spatially clustering the precipitation area location and generating a probability map of the hail precipitation area and early warning information. By establishing a "life profile" for each hail embryo particle that includes its trajectory, phase evolution, and environmental thermodynamic conditions, the complete process of hail embryo formation from initial formation to final hail precipitation is tracked. Based on the statistical analysis of the life profile, key transformation characteristics of different hail storm types are adaptively identified, thereby achieving early hail warning.

The invention discloses a method and equipment for determining an urban rainstorm amount formula considering both the residence and building drainage standard and the water conservancy waterlogging control standard, and the method comprises the following steps: (1), calculating the theoretical design rainstorm amounts of different durations and different return periods through frequency analysis by using an actually measured rainfall database; (2) solving a rainstorm amount formula parameter, and (3) compiling a rainstorm amount formula. According to the method, in view of non-uniform design standards of urban drainage, waterlogging control and flood control projects, a rainstorm amount formula which is simultaneously suitable for the drainage standard of the residence and construction department and the waterlogging control standard of the water conservancy department is established, and the designed rainstorm amount under any length and short duration and any high and low recurrence period can be directly calculated; and the recurrence period level of any historical rainstorm event can be estimated, and multi-department cooperative treatment of urban rainfall flood can be promoted.

The application discloses a storm forecast method, device and system based on multi-mode integration, and belongs to the technical field of weather forecast. The method comprises the following steps: acquiring and preprocessing multi-mode precipitation forecast data; calculating the dynamic weight of each mode through the Spearman correlation coefficient based on the historical data of the dynamic sliding window, and generating a precipitation spatial distribution field through weighted average; at the same time, screening an optimal forecast subset based on the symmetric average absolute percentage error, and generating a precipitation intensity field through the interval median of the subset forecast value sorting; finally, replacing the forecast value of the spatial distribution field with the same rank value in the intensity field according to the rank matching, and obtaining the final storm forecast product. The application realizes the double optimization of storm spatial falling area and intensity, significantly improves the forecast accuracy, and reduces the false alarm rate and the missing alarm rate.

The invention relates to the technical field of ocean storm information analysis, in particular to a typhoon storm prediction method fusing numerical simulation and deep learning. The method comprises the following steps: establishing a heterogeneous wind field mapping model of the marine typhoon based on marine typhoon multi-source observation data, and generating the heterogeneous wind field mapping model of the marine typhoon; establishing a wind field space-sea wave spectrum net effect relation model through the multi-order grid wave space change data of the marine typhoon heterogeneous wind field mapping model; performing model optimization reconstruction processing of fusion wind field trend simulation on the marine typhoon heterogeneous wind field mapping model by using a preset long-short-term memory recursive network model to generate a fusion wind field trend simulation optimization model; and carrying out typhoon wave trend simulation numerical model analysis processing on the fused wind field trend simulation optimization model by utilizing a wind field space-sea wave spectrum net effect relationship model to generate a typhoon wave trend simulation model. According to the invention, accurate typhoon storm prediction is realized.

The invention discloses a storm radar characteristic quantity driven machine learning tornado identification method, and belongs to the field of meteorological disaster weather identification, and the method comprises the following steps: obtaining a storm radar characteristic quantity containing key characteristic information through characteristic extraction and optimization processing based on body sweeping radabundance data; performing feature quantity normalization processing and feature quantity missing value processing on the storm radar feature quantity to obtain an input sequence containing a plurality of elevation angle layer data; and inputting the input sequence into a recognition model fusing Transform and CNN, and outputting a tornado recognition result. According to the method, the technical problems of feature redundancy, insufficient local and global feature fusion, data missing sensitivity and the like in a traditional tornado identification method are effectively solved.

The application relates to the technical field of architectural design, in particular to a metal texture slope roof suitable for tropical storm and typhoon areas, which comprises, from bottom to top, a reinforced concrete roof panel, a mortar layer, a three-layer waterproof layer, an isolation layer, a concrete protective layer and a silver gray paint layer; the three-layer waterproof layer comprises a polyurethane waterproof paint layer, an elastomer modified bitumen waterproof roll material and a hard foam polyurethane spraying layer. Reinforced anchor rings, reinforced meshes and cold-drawn steel wire meshes are all arranged in the concrete layer and have no direct contact with the atmosphere, so that corrosion and loss of effectiveness are avoided, and roof corrosion prevention is effectively realized; through the design of the three-layer waterproof layer, waterproof effect is effectively achieved, and heat preservation effect is simultaneously achieved; the metal texture slope roof suitable for tropical storm and typhoon areas is designed in the aspects of material selection, construction technology and combination reliability to adapt to tropical storm and typhoon areas, so that the requirements of roof structure on wind lifting resistance, waterproofness and corrosion resistance are met.

This invention relates to the field of disaster forecasting and early warning technology, and discloses a method and system for early warning of rainstorm disasters based on the rainstorm disaster bearing capacity coefficient. The method includes the following steps: acquiring multi-source data and basic geographic information of the warning area; extracting spatiotemporal features based on the multi-source data and basic geographic information; and calculating the gridded forecast rainfall within a predetermined time period based on the spatiotemporal features; acquiring historical rainstorm disaster data of the warning area; calculating the gridded rainstorm disaster bearing capacity coefficient based on the historical rainstorm disaster data and basic geographic information; establishing an empirical model based on the historical rainstorm disaster data and basic geographic information to calculate the gridded rainfall threshold; and obtaining the rainstorm disaster prediction result of the warning area based on the gridded forecast rainfall, the gridded rainstorm disaster bearing capacity coefficient, the gridded rainfall threshold, and the on-site measured rainfall, combined with the algorithm model. This method solves the problem of weak monitoring capabilities in existing disaster forecasting and early warning systems.

The application discloses a radar echo extrapolation method based on a space-time attention mechanism, first obtains radar echo data of a target area, and carries out pretreatment on the obtained radar echo data; the radar echo data after the pretreatment is subjected to sliding grouping and data augmentation, so that a radar echo sequence data set is obtained, and then the radar echo sequence data set is divided into a training set and a test set; a radar echo prediction network model based on a SimVP architecture is constructed and trained and tested, a multi-target loss function is used to supervise model training; and a future radar echo image is predicted in real time. Through the method, complex weather phenomena such as storms can be more accurately captured in dynamic evolution, the precision and interpretability of short-term nowcasting can be significantly improved, more reliable technical support is provided for timely and accurate early warning of meteorological disasters, and the method has important practical application value.

The application discloses a terrain self-adaptive rainstorm waterlogging spatio-temporal joint prediction method and system, and belongs to the field of alarm responding to disaster events. In order to overcome the defects of the existing method, such as insufficient terrain adaptability of fixed feature weight, and prediction fragmentation caused by independent operation of the spatio-temporal model, the technical scheme of the application is as follows: on the one hand, a terrain self-adaptive dynamic feature weight mechanism is constructed, an adjustment coefficient is generated by quantifying the terrain undulation, and the feature factor weight of the geographical spatio-temporal weighted regression model is dynamically adjusted to adapt to the complex underlying surface; on the other hand, a spatio-temporal joint weighted fusion framework is proposed, a random forest spatial model and a PredFormer time series model are combined, the spatial prediction result is taken as the initial condition of the time series, and the time series collaborative prediction of the flooded range and the water depth is realized. The application is suitable for rainstorm waterlogging prediction of different terrains in cities, and has the advantages of strong terrain adaptability, high prediction accuracy and stability, and unified spatio-temporal rapid response.

The application discloses an urban waterlogging intelligent prediction method considering sewer pipe silting, constructs a sewer pipe silting considered underground pipe network and two-dimensional surface coupling waterlogging numerical simulation model by using underground drainage pipe network data; by using the stormwater monitoring data of the application area, the constructed underground pipe network and the numerical simulation model are subjected to model calibration and verification; a storm event data set is constructed, and storm events of different rainfall types and different return periods are designed; an urban waterlogging intelligent prediction model is fused by an improved convolutional neural network, a bidirectional long short-term memory neural network and a Bayesian optimization algorithm, a rainfall time sequence of a database is taken as input of the model, a flooded time sequence is taken as output of the model, a training set of the database is used for training and parameter optimization of the urban waterlogging intelligent prediction model; and the rainfall time sequence in the test set of the database is taken as input, and urban waterlogging intelligent prediction under a pipe silting scenario is realized by the constructed urban waterlogging intelligent prediction model.

The utility model relates to the technical field of coast environment monitoring, in particular to a coast environment monitoring and early warning device, an electric telescopic rod comprises an outer rod body and an inner rod, the bottom end of the outer rod body is fixedly installed with a boss, the inner rod is in transmission connection with the outer rod body, the top end of the inner rod is fixedly provided with an installation platform, and the installation platform is in transmission connection with the inner rod body. A reinforcing frame is arranged on the outer side of the inner rod; during use, when the wind speed sensor on the mounting platform monitors that the wind power level reaches the maximum bearing wind power of the electric telescopic rod in severe stormy weather, the inner rod of the electric telescopic rod is contracted into the outer rod body to drive the mounting platform to move downwards, so that the height of the mounting platform is reduced; the impact force bearing capacity of the supporting rod is enhanced, the height of the supporting rod can be adjusted in a self-adaptive mode according to the wind wave level, the reinforcing frame is arranged on the outer side of the inner rod, the inner rod can be further supported and reinforced, the stability of the electric telescopic rod is enhanced, the risk that the electric telescopic rod is bent and damaged is avoided, and the service life is prolonged.

The invention discloses a multi-disaster-oriented environment coupling type power grid vulnerability assessment method and system, and relates to the technical field of fault assessment. Firstly, a power transmission line is decomposed into an electric tower node and a virtual node, so that the linear damage calculation complexity is reduced, power grid second-level time sequence simulation is supported, and the power grid vulnerability assessment efficiency is improved; secondly, by constructing a multi-disaster unified coupling mechanism: constructing a geographic matrix, an environment matrix and a meteorological matrix, driving a plurality of disaster damage models, and realizing joint quantification of a disaster chain physical process; and finally, by taking the topology power supply availability rate and the cascade failure fault condition as damage measurement indexes, power grid vulnerability evaluation is performed in an earthquake disaster scene and a storm disaster scene, and the problem of fault underestimation caused by neglecting power redistribution in a traditional model is solved.

The invention discloses an observation data correction method under an offshore wind wave and ocean current coupling condition, and the method comprises the steps: collecting original observation data in a coupling scene through an ocean wind wave current assimilation correction platform, screening target data meeting the coupling condition, and carrying out the initial correction through a wave current vortex energy covariance correction model, and inputting the preliminary correction data into a wind wave and flow combined cost function optimization algorithm to analyze an error source. And adjusting model key parameters and algorithm calculation coefficients according to an error result, performing secondary correction on the data, and finally feeding back the secondary correction data to a platform for comparison verification with historical data. The platform comprises a data acquisition and transmission unit, a model operation unit, an algorithm processing unit, a parameter adjustment unit, a thermal management monitoring unit and a result verification and storage unit, can correlate a wind wave and ocean current energy relationship, integrates thermal management parameters, solves the problem of insufficient correction precision in the prior art, and improves the accuracy of observation data under a coupling condition.

The embodiment of the invention provides a composite extreme event diagnosis method, device and equipment and a storage medium, and the method comprises the steps: determining the blocking high pressure of a first place and a second place, carrying out the strength diagnosis, and obtaining the formation condition of a dual-blocking system; determining a third place, determining a cold vortex center, calculating the vertical vortex advection intensity of the third place, and obtaining the formation condition of a cold vortex system corresponding to the cold vortex center; determining a double-blocking high-pressure center according to the first place and the second place, calculating the air pressure gradient force of the double-blocking center and the cold vortex center, and judging the mutual reinforcement degree of the two systems according to the air pressure gradient force; and determining a fourth place, constructing a decision matrix based on the four places, the formation conditions of the two systems and the mutual reinforcement degree, and diagnosing the extreme event by using the decision matrix. Quantitative evaluation of the concurrent probability of multiple disasters such as strong wind, violent snow and strong cooling is realized, the missing report rate of composite extreme events is reduced, and the early warning capability is improved.

The application discloses a kind of ocean storm early warning float and ocean storm early warning method, applied in ocean storm early warning float technical field, its technical solution key points are: including float platform;The suspension rod is suspended in the float platform with coaxial center along vertical direction, sliding connection detection sleeve is sleeved on the suspension rod with coaxial center, first plumb component and second plumb component for always keeping vertical are respectively arranged on the suspension rod and the detection sleeve, universal floating component is equipped between the float platform and the detection sleeve, a plurality of direction detection components and intensity detection components are respectively fixed on the detection sleeve, wind cup component for detecting wind power size is rotatably connected on the suspension rod;With technical effect is: simple structure, early warning precision is high, can realize real-time early warning.

A bracket assembly for use in securing a panel to protect a structure opening from high winds. The assembly employing a triangular shape retaining bracket hingedly attached a base member. The base member secured to a Structure with fasteners wherein the retaining bracket may be placed in an open position for receipt of a storm panel, and then placed in a closed position to secure the panel in position. The retainer bracket and base member have reciprocal tab members that will receive a pin member to secure the bracket in a closed position. The retaining bracket is preferably of a decorative design wherein the retaining bracket becomes a permanent decorative accessory to the structure, the retaining bracket conceals the base member when in the closed position.

A storm water capture and filtration system may secure in a catch basin or other area subject to flows of water from streets, channels, and the like as a result of run off from storms. A filter system may include a capture portion including attachment mechanisms, a funnel, various supports, and a filter hanger designed and calculated to capture all water entering a storm water inlet and directing it toward a bag filter. A gap is provided between a funnel and filter hanger in order to provide accommodation for overflow, while an anti-backflow skirt on the filter bag resists flushing of captured pollution out of the bag in overflow condition.

The invention relates to the cross technical field of meteorological detection and electric power disaster prevention, and discloses a method and a device for intelligently identifying thunderstorm and gale risks of a power transmission line based on a weather radar. And the nearest approaching distance and the arrival time between the storm single body and the target tower section are accurately calculated, and then the early warning level is determined according to the thunderstorm and gale risk comprehensive index and the time-space parameters. Quantitative evaluation and graded early warning of thunderstorm and gale risks of the power transmission line can be realized, the early warning accuracy and timeliness are improved, the influence of disasters on the line is reduced, and safe and stable operation of a power transmission system is guaranteed.