56 results about "Automatic weather station" patented technology

The embodiment of the invention provides a method and a device for monitoring abnormity of an automatic ocean weather station based on multi-dimensional configuration characteristics, which are applied to the technical field of meteorological monitoring. The method comprises the following steps: acquiring meteorological monitoring data and position calibration data in a target station area; grouping stations in the target station area according to the meteorological monitoring data and the calibration data; respectively inputting the meteorological monitoring data of the stations in each group into a preset performance health degree model, and correspondingly outputting performance health indexes; and / or respectively inputting the meteorological monitoring data of the stations in each group into a preset configuration health degree model, and correspondingly outputting configuration health indexes; and determining abnormal sites according to the performance health indexes and / or the configuration health indexes of the sites in each group. In this way, real-time monitoring of the operation health degree of the coastal automatic weather station equipment, abnormal early warning and automatic recognition of fault points can be achieved.

The invention discloses a heavy rainfall short and temporary trigger forecasting method based on cooperation of radar echo extrapolation and machine learning, and relates to the technical field of weather forecast, and the method comprises the steps: S1, multi-source data collection: collecting three types of basic data, namely conventional radar echo data, dual-polarization radar data and automatic weather station real-time observation data; according to the method, the dual-polarization radar data and the real-time observation data of the automatic weather station are fused, comprehensive capture of key features formed by heavy rainfall is achieved, the problems that in the prior art, the data dimension is single, and the forecasting basis is insufficient are solved, and the real-time forecasting of heavy rainfall is achieved through the steps of splitting data collection, preprocessing, fusion, extrapolation forecasting and collaborative forecasting. A radar echo extrapolation and machine learning cooperation mechanism is constructed, double improvement of precision and timeliness of heavy rainfall short and temporary trigger forecasting is realized, the problems of large forecasting deviation and poor timeliness caused by single use of a single algorithm or model are solved, and heavy rainfall disaster loss is effectively reduced.

The invention discloses a weather prediction method, device and system based on federated learning, and belongs to the technical field of weather prediction, the weather prediction method based on federated learning combines a Transform model with a KAN model, and uses the advantages of the Transform model, the KAN model and a federated learning framework to predict the weather prediction. The provided first weather prediction model constructed on the basis of the Transform-KAN can have good data fitting performance. According to the method, the weather data are classified, then the weather data are placed under a federated learning framework, the automatic weather stations distributed at all places can carry out distributed collaborative learning, global features and space-time dependency relationships in the weather data can be well learned, and better data fitting ability and generalization performance can be achieved while data privacy is guaranteed.

This invention relates to the field of AI weather forecasting technology and discloses a weather forecasting method based on an AI weather forecasting model and a WRF model. The method includes: inputting ERA5 global atmospheric reanalysis gridded data into the AI ​​weather forecasting model to obtain an assimilated background field; constructing an effective multi-source observation vector based on observation data from ground automatic weather stations, radiosonde observation data, geostationary meteorological satellite radiance data, and Doppler radar VAD wind profile data; solving for the optimal atmospheric analysis field; extracting atmospheric state variables from the optimal atmospheric analysis field and writing them into the WRF model's side boundary driving file, driving the WRF model to complete the integration operation, and obtaining a gridded forecast field of meteorological elements. This method enables the WRF boundary condition update frequency to be higher than the traditional 6-hour static scheme, effectively characterizing the rapid evolution of the atmospheric state in the boundary region at the sub-hourly scale, thereby improving the WRF model's forecasting capability for high-impact weather events such as severe convection.

The present application discloses a method and device for identifying and predicting micro-rainfall weather processes, which belongs to the field of environmental monitoring technology. The method collects cloud data from Ka-band cloud radar, precipitation data from X-band rain radar, and data from automatic weather stations. A nonlinear model is established, and the data output by the nonlinear model are grouped according to the time axis and radar type. A fitting curve for the micro-rainfall weather process is established to calculate the coefficient of determination and generate eigenvalues, and the prediction result is determined based on the eigenvalues. The output data of the nonlinear model is corrected based on the data from the automatic weather station and the eigenvalues, and the corrected coefficient of determination and eigenvalues ​​are input into the historical data model library as prediction conditions. The judgment results under the same conditions are screened out and compared with the prediction results. If the comparison result is valid, an alarm information push is generated. The method and device for identifying and predicting micro-rainfall weather processes provided by the present application realize the full-process observation and prediction of water vapor-cloud-precipitation, significantly reducing the false alarm rate.

The invention relates to the technical field of rain and snow phase state identification, in particular to a dual-polarization radar ground rain and snow phase state identification system based on machine learning and multi-source data, comprising a temperature and humidity profile identification module used for generating a temperature and humidity profile based on real-time radar basic reflectivity, microwave radiation, automatic station data, EC forecast data and ERA5 temperature and humidity data; the phase state discrimination condition generation module is used for combining the temperature and humidity lattice point data of each air pressure layer into vertically distributed temperature and humidity lattice point data through a program based on the temperature and humidity contour line, calculating a cloud top temperature matrix and a 0 DEG C layer height matrix based on a temperature and humidity lattice point data point field, and generating a phase state discrimination condition according to a calculation result; and CC-HCL for generating a rain and snow phase state based on the generated phase state discrimination condition.

The invention discloses a miniature automatic weather station and a temperature measurement optimization control method and system. The temperature measurement performance of the miniature weather station is improved through global comprehensive optimization in the aspects of a system structure, circuit layout and a data algorithm. The system structure is improved, the structural design of the double-layer vertical-wall hollow cylindrical radiation-proof cover retains the advantage of compact structure of the miniature automatic weather station, and meanwhile, a conventional horizontal natural ventilation radiation-proof cover in a louver blade overlapping form is changed into the double-layer vertical-wall hollow cylindrical radiation-proof cover; sampling airflow is changed from horizontal natural ventilation airflow to vertical active air exhaust sampling. According to real-time meteorological environment data, a sampling air pump is driven and controlled in a segmented mode to operate, the solar radiation intensity, the atmospheric wind speed and the atmospheric temperature are used as control variables to determine the operation speed and the sampling flow of the sampling air pump, and a working mode, a circulation control variable and a working time sequence are selected. And in the aspect of a data processing algorithm, a multi-source data fusion calibration method is adopted to improve the accuracy of temperature measurement data.

The invention discloses an automatic meteorological station operation state detection method based on multi-modal data, and relates to the technical field of meteorological monitoring, and the method comprises the steps: obtaining meteorological training samples of an automatic meteorological station in different operation states, and the multi-modal feature extraction module, the multi-modal feature fusion module and the time sequence anomaly detection module are cascaded in sequence to construct a network architecture of the automatic meteorological station operation state detection model, and the automatic meteorological station operation state detection model is trained by taking the meteorological training sample as input and the operation state of the automatic meteorological station as output. And obtaining multi-modal meteorological time sequence data to form a to-be-detected time sequence, and determining the operation state of the automatic meteorological station at the current operation moment based on the to-be-detected time sequence by using the trained automatic meteorological station operation state detection model. By integrating the multi-mode meteorological time sequence data, the detection precision and efficiency of the running state of the automatic meteorological station are effectively improved, and stable running of the automatic meteorological station is guaranteed.

The application relates to the anchoring technical field of a weather station, in particular to an automatic weather station anchoring device for an ice cover environment and a mounting method. The anchoring device comprises an expansion assembly and a fixing assembly which are sleeved on a rod core assembly; the fixing assembly is sleeved on a support rod at the upper portion of the expansion assembly, the upper end of the support rod is connected with an end cover through a second screw joint, a lifting sleeve is arranged in the expansion assembly, a plurality of sets of pawl assemblies are arranged in the circumferential direction of the expansion assembly, one end of each pawl assembly is hinged to the cylinder of the expansion assembly, the other end of each pawl assembly is hinged to the lifting sleeve, the pull rod of the rod core assembly passes through the expansion assembly, and the upper end of the pull rod is connected with an operating device through a first screw joint.

The invention relates to the technical field of meteorological services, and particularly discloses a meteorological forecasting method and system fused with high-precision geographic information, geographic data is obtained through a satellite, the influence of a macroscopic geographic environment on climate can be reflected, real-time monitoring data of an automatic meteorological station can provide accurate observation of microscopic point locations, and the accuracy of meteorological forecasting is improved. A macroscopic-microcosmic linkage complete data chain is formed, analysis deviation caused by a data surface is avoided, a positioning system of the automatic weather station ensures accurate binding of detection data and geographic coordinates, and by combining with a preset geographic layout boundary, the position fuzziness of the data can be avoided, so that each piece of climate data can anchor a specific geographic scene, and the accuracy of data analysis is improved. A precise space reference is provided for subsequent analysis, and the characteristics of precise data, clear monitoring, sensitive and reliable prediction and wide application range are cooperatively realized through multi-modal technology fusion.

The invention provides an automatic weather station, component equipment and an operation entropy index calculation method of an automatic weather station network. The method comprises the following steps: acquiring the fault-free operation time and rain gauge maintenance time interval of each component equipment in the automatic weather station; according to the fault-free operation time of each component device and the rain gauge maintenance time interval, the operation entropy index and the operation fuzzy state of each component device in the automatic weather station are calculated, the operation entropy indexes and the operation fuzzy states of the automatic weather station and the automatic weather station network are calculated, and the operation state of the automatic weather station is evaluated in real time. Through the method of the invention, the operation states of each component of the automatic weather station, the automatic weather station and the automatic weather station network are evaluated, the operation risk is estimated, timely discovery, disposal and alarm are facilitated through monitoring alarm, and preventive measures are taken.

The utility model relates to the technical field of meteorological station monitoring, in particular to a novel meteorological automatic station data transmission monitoring device which comprises a meteorological station stand column, camera shooting assemblies are symmetrically arranged on the two sides of the meteorological station stand column, and supporting side frames are assembled at the bottoms of the camera shooting assemblies in a butt joint mode through installation bases. Assembling side plates are hinged to the inner side ends of the two sets of supporting side frames through a left shaft column and a right shaft column correspondingly, the inner sides of the two sets of assembling side plates are assembled on the outer wall of a meteorological station stand column in a surrounding mode through integrally-arranged inner hoops and assembled and fastened through bolts, inner supporting plates are assembled on the inner sides of the assembling side plates, and telescopic cylinders are assembled in the inner supporting plates; the camera shooting assembly and the telescopic cylinder are electrically connected with the meteorological station power distribution control module through data wires. The device can be conveniently assembled and supported outside the vertical rod of the meteorological station for auxiliary surrounding use according to use requirements, so that the device is more convenient and efficient to use.

The invention provides an insurance authentication automatic generation system based on multi-source meteorological data fusion, and the system comprises an input module which is used for obtaining claim settlement point information inputted by a user, and the claim settlement point information comprises at least one of the position information, time range, claim settlement conditions and meteorological elements of a target claim settlement point; the meteorological service data acquisition subsystem is used for acquiring and storing multi-source meteorological detection data acquired by an automatic meteorological station, a radar and a satellite; the meteorological data query subsystem is used for screening the multi-source meteorological detection data according to the claim settlement point information and outputting a meteorological authentication product of a target claim settlement point; the insurance meteorological parameter authentication subsystem is used for making an insurance meteorological authentication certificate according to the meteorological authentication product; and the monitoring subsystem is used for inputting and auditing an insurance meteorological authentication certificate. The insurance authentication automatic generation system provided by the invention can automatically obtain, analyze and utilize the meteorological data, and automatically generate the insurance authentication report, thereby improving the insurance claim settlement efficiency.

The invention discloses a method for storing sensor data based on gradient difference interpolation marks. Comprising the following steps: S1, data collection: collecting and obtaining various minute data of a collector; s2, gradient data processing: carrying out gradient operation on the collected moment data, carrying out gradient operation on a current sensor data value and a previous moment data value to realize data monitoring, and preparing for differential mark data storage; and S3, differential marked data storage: carrying out differential operation on the data obtained in the S2, removing the same or meaningless data values, and / or carrying out marked storage on suspected data. The data of the automatic meteorological station has the characteristic of strict time correspondence and limitation, and the gradient advantage can be fully utilized: the data is processed through the optimization and compression functions of a gradient algorithm, so that the storage space is reduced; data partition management is achieved in combination with interpolation marks, and the query and management efficiency is improved; and data monitoring can be realized based on gradient analysis data trend.

1. The name of this design product: Pole-mounted shipborne automatic weather station. 2. Purpose of this design product: It can provide meteorological data such as temperature, relative humidity, air pressure, true wind direction, true wind speed and visibility when the ship is sailing or stopped, and can also provide navigation data such as latitude and longitude, heading and speed. 3. The key design point of this appearance design product lies in the overall shape of the product. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The application relates to the anchoring technical field of a weather station, in particular to an automatic weather station anchoring device for an ice cover environment and a mounting method. The anchoring device comprises an expansion assembly and a fixing assembly which are sleeved on a rod core assembly; the fixing assembly is sleeved on a support rod at the upper portion of the expansion assembly, the upper end of the support rod is connected with an end cover through a second screw joint, a lifting sleeve is arranged in the expansion assembly, a plurality of sets of pawl assemblies are arranged in the circumferential direction of the expansion assembly, one end of each pawl assembly is hinged to the cylinder of the expansion assembly, the other end of each pawl assembly is hinged to the lifting sleeve, the pull rod of the rod core assembly passes through the expansion assembly, and the upper end of the pull rod is connected with an operating device through a first screw joint.

1. The name of this design product: Automatic Weather Station (Micro). 2. Purpose of this design product: used for observing meteorological climate. 3. The key design point of this appearance design product lies in the overall shape of the product. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

This invention discloses a quality control method for minute-by-minute temperature variability at automatic weather stations based on a lightweight gradient booster. The quality control method includes: P1, Data Acquisition: Collecting multi-source data from automatic weather stations and standardizing the data; P2, Data Preprocessing: Cleaning and performing preliminary quality checks on the acquired multi-source data to obtain a preprocessed dataset; P3, Feature Extraction: Extracting multi-dimensional features and performing spatiotemporal matching on the preprocessed dataset to obtain a feature vector dataset; P4, Model Training and Evaluation: Constructing an adaptive automatic weather station temperature variability quality control model based on the LightGBM quantile regression algorithm and completing model training and quantitative evaluation; P5, Automatic Weather Station Temperature Variation Quality Control: Using the constructed adaptive automatic weather station temperature variability quality control model, outputting the temperature variability results of the target automatic weather station, and performing real-time quality control and judgment on the temperature of the target automatic weather station. This invention can solve the problem that traditional fixed threshold methods cannot adapt to complex climatic environments.

The utility model discloses an automatic weather station for a highway, which comprises a mounting rod, and a weather sensor, a pavement condition monitoring device and a camera are arranged on the mounting rod. The mounting rod comprises a rod bottom section, a rod middle section and a rod upper section, the rod middle section is mounted on the rod bottom section, the rod middle section can slide up and down on the rod bottom section and is locked, one end of the rod upper section is connected with the rod middle section in a hinged mode, and the rod upper section can rotate around the hinged position of the rod upper section and the rod middle section; the meteorological sensor and the camera are both arranged on the pole upper section, and the meteorological sensor comprises a wind speed and direction sensor, a temperature and humidity sensor and an air pressure sensor; and the road surface condition monitoring device is arranged on the rod middle section. By means of the mode, in the installation and maintenance process, the pole upper section can be laid flat, and the risk of high-altitude operation is greatly reduced. In addition, a rotatable locking structure is arranged between the upper section and the middle section, so that the upper section of the rod can rotate to any required position, and the safety and convenience of equipment maintenance are further improved.

The invention relates to an intelligent street lamp turn-on control method and system considering special meteorological factors, and the method comprises the steps: calculating reference radiation based on an NARP clear sky net radiation model, and carrying out the real-time collection of precipitation, visibility and relative humidity data through an automatic meteorological station; and dynamically generating a meteorological adjustment coefficient through sliding window statistics and a logarithm-linear scaling algorithm, and comprehensively adjusting the reference radiation to obtain the actual received radiation intensity of the earth surface. And when the adjusted radiation value is lower than a preset threshold value, a street lamp turn-on instruction is automatically triggered. According to the method, expensive sensors do not need to be added, and the attenuation influence of special weathers such as rainstorm and low visibility on illumination can be accurately quantified only by using conventional meteorological data. Actual measurement shows that the method reduces the root-mean-square error of the turn-on time to 8.2 minutes, obviously solves the problem that the turn-on of the street lamp lags behind or is too early in special weather, has the advantages of high precision, low cost and easy popularization, effectively guarantees traffic safety and saves energy.

1. The name of this design product: Lightning protection voltage limiter. 2. Purpose of this design product: It is used to protect automatic weather stations and other meteorological equipment from lightning strikes, thereby ensuring that these equipment can operate normally and provide accurate meteorological data. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

1. Name of the design product: Automatic weather station (QX5YGG-1). 2. Use of the design product: The specific usage scenarios of this design product are for marine and buoy applications, and it can measure wind speed, wind direction, air temperature, relative humidity, and air pressure. 3. Design key points of the design product: Lies in the shape. 4. Picture or photo that best shows the design key points: Perspective view 1.

The utility model discloses a double power supply device of regional automatic weather station with automatic selection function relates to automatic weather station technical field. Include: A electric control input, B electric control input, control unit and relay, the control unit includes undervoltage protection circuit and voltage stabilizing delay circuit, and through undervoltage protection circuit, voltage stabilizing delay circuit and the cooperation of relay interlock A electric control input and B electric control input, realize the automatic switching of power supply, undervoltage protection circuit includes reference power supply chip and PNP switch tube, and reference power supply chip and PNP switch tube are communicated through the wire between. The utility model discloses adopting the very mature component of technology, and the circuit structure is simple, and the cost is low and easy to make and stable and reliable work, effectively solved the fault of the collector caused by the battery charging shortage, both saved regional station maintenance cost and ensured the continuity of meteorological data.

The application provides a complex terrain wind farm automatic weather station data anomaly identification and intelligent quality control cleaning method, and relates to the technical field of new energy meteorological data processing. The method comprises the following steps: acquiring multi-source data, performing standardization processing and physical quantity conversion, and constructing a multi-dimensional feature matrix; at least one of threshold and logic verification, time sequence consistency detection, distribution offset detection and extreme weather adaptation verification is executed for initial detection, and the data triggering any initial detection abnormal condition is marked as suspicious data; a hybrid classification model containing LightGBM, bidirectional LSTM and attention mechanism is used to classify and determine the suspicious data; and differential repair is respectively performed on different classification labels. The abnormal data identification accuracy of the application is greater than or equal to 95%, the missed detection rate is less than or equal to 3%, and the false detection rate is less than or equal to 5%, and the application can especially accurately distinguish between real extreme data and sensor fault data.

The present invention relates to a mechanical calculation method for LSAM-50 full-depth asphalt pavement considering high-temperature temperature field. Temperature sensors are buried in the service pavement, and an automatic weather station is established. By collecting the temperature data of the pavement structure and synchronously recording the real-time data of environmental parameters, considering the most unfavorable situation, taking the highest temperature of each layer as the characteristic temperature, a pavement temperature-pavement depth model is established. Cylindrical specimens corresponding to the indoor forming are tested for the resilient modulus values of asphalt mixtures at different temperatures, and a temperature-resilient modulus dependence model of asphalt mixtures is established. The asphalt pavement structure layer and structural sub-layer are divided. According to the pavement temperature-pavement depth model, the calculation temperature corresponding to each calculation depth is determined. According to various temperature-resilient modulus models of asphalt mixtures, the calculated resilient modulus corresponding to each calculation temperature is determined. According to the determined resilient modulus of each structural sub-layer, the elastic layered continuous system theory under the action of double circular uniform vertical loads is used to calculate the mechanical indexes of the pavement structure.

The invention relates to the technical field of climate resource development and health-care industry, and discloses a method for planning three-dimensional climate health-care resources in a low-latitude plateau mountainous area, which is characterized in that the climate shows a vertical differentiation characteristic of'ten days different from each other 'due to large altitude fall (generally 2000-3000 meters) in the low-latitude plateau mountainous area, so that the three-dimensional climate health-care resources in the low-latitude plateau mountainous area can be developed. Therefore, the mapping relation of altitude gradient-microclimate-health value needs to be established in general survey, and during specific implementation, automatic meteorological stations (such as 600 meters, 900 meters, 1200 meters... 3200 meters) are arranged at intervals according to the altitude of 300 meters. According to the three-dimensional climate health resource planning method for the low-latitude plateau mountainous area, when the high-altitude research and study requirements are insufficient, by combining the phototherapy course developed by the ultraviolet light resources, the market blank is filled, the deep value of the three-dimensional climate can be played, the resource waste is avoided, the continuous attraction is kept, and the mode that development is not damaged and adjustment follows up is adopted. The three-dimensional climate health resources are ensured to benefit people at present and benefit descendants for a long time.

The invention discloses a gale event classification method based on iterative clustering analysis, and the method comprises the following steps: collecting the observation data, reanalysis data and rainfall data of an automatic weather station in a target region, screening and extracting gale event samples, and calculating a plurality of environmental physical quantities corresponding to each gale event; based on the environmental physical quantity, performing first clustering analysis on all the gale event samples by using an unsupervised clustering algorithm to obtain a preliminary gale type division result; based on the primary classification result, evaluating the importance of each environmental physical quantity to different strong wind types by using a random forest algorithm, and screening out key feature variables; and performing secondary clustering analysis on the gale events which are misjudged or have fuzzy boundaries in the primary classification result by using the key feature variables, and re-dividing the types of the gale events to obtain a final gale weather system classification result.

This invention relates to a method for short-term visibility forecasting and correction on highways, comprising the following steps: acquiring 10-minute historical meteorological observation data from traffic meteorological observation stations along the measured section of the highway; calculating the Pearson correlation coefficient between visibility and various meteorological factors, and performing a significance test; acquiring hourly real-time meteorological observation data along the measured section of the highway; training an LSTM prediction model to obtain visibility forecast results for 10 minutes and station numbers within the next 2 hours; performing probabilistic correction on the visibility forecast results using visibility observation data acquired from automatic weather stations, performing trend correction on the visibility forecast results using visibility data retrieved from video images along the highway, and using the correction results to correct subsequent new visibility forecast results, thereby obtaining visibility forecast results for station numbers and 10-minute intervals along the measured section of the highway within a short-term near-term timeframe of 0-2 hours.

A method for forecasting the intrusion of sea fog into land and identifying its types based on automatic weather station data, including making a historical dataset of the intrusion of sea fog into land; classifying the types and degrees of the intrusion of sea fog into land; establishing a forecasting equation for the intrusion of sea fog into land, discriminating the occurrence of sea fog and the types of intrusion into land, calculating the perturbation changes in relative humidity and temperature in the 6 hours before the forecasting time, and judging whether the wind direction at the forecasting time is onshore. If it is onshore, the value range of which type the sea fog belongs to is calculated according to the equation. The method for depicting the intrusion of sea fog into land based on automatic weather stations of the present invention can use automatic weather stations to depict the types and degrees of the intrusion of sea fog into land hour by hour and in a refined manner, and quantitatively forecast in advance the degree of the intrusion of sea fog into land, providing a reference for sea fog forecasting in coastal areas.

The invention discloses a ground automatic meteorological station operation state prediction method based on multivariate data, and relates to the technical field of meteorological monitoring, and the method comprises the steps: obtaining an operation environment image and an equipment state data sequence of a ground automatic meteorological station; performing image quality detection on the operation environment image to obtain a prediction index result of a camera state index; and performing target identification on the operation environment image by using the observation environment identification model to obtain a prediction index result of the environment target state index. And obtaining a prediction index result of the working parameters based on the equipment state data sequence by using the equipment state time sequence prediction model. And determining a prediction index result of the equipment support index. And fusing prediction index results of the camera state index, the environment target state index, the working parameters and the equipment support index at the future moment to obtain an operation state prediction result. The running state of the ground automatic weather station at the future moment is predicted, and the maintenance efficiency and the maintenance quality are improved.