70 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.

The invention discloses a uniform hourly air temperature data processing method for regional automatic weather stations. The method comprises the following steps: collecting data sources (regional automatic weather station observation data and regional automatic weather station metadata) of each regional automatic weather station and national automatic weather station observation data; performing quality control on the observation data of the regional automatic weather station by adopting climate boundary value inspection, internal consistency inspection, inspection that the temperature value is negative from June to August, climate abnormal value inspection and space consistency inspection; screening a regional automatic weather station; carrying out homogenization analysis to obtain homogenization hourly air temperature data of the regional automatic weather station; performing data quality evaluation on the uniform hourly air temperature data of the regional automatic weather station; and analyzing air temperature trend characteristics. The invention relates to the technical field of meteorological observation data processing, and can solve the problems that in the prior art, a climate data set lacks a data source of a regional automatic meteorological station, a homogenization processing technology is not enough in application, and a research analysis result is uncertain.

The invention provides a distributed photovoltaic ultra-short-term power prediction method and device based on remote sensing information, and the method comprises the steps: obtaining a distributed photovoltaic ultra-short-term power prediction model through a cloud condition power change relational expression and a solar resource utilization rate relational expression according to the remote sensing information of a target satellite, a to-be-predicted time period and basic information; generating distributed photovoltaic power variation and distributed photovoltaic theoretical power of the to-be-predicted time period; through an ultra-short-term power prediction model, according to target meteorological monitoring data, target satellite remote sensing information, distributed photovoltaic power variation and distributed photovoltaic theoretical power of a to-be-predicted time period, distributed photovoltaic predicted power of the to-be-predicted time period is generated, and the ultra-short-term power prediction model is obtained by training based on a dynamic recurrent neural network. Satellite remote sensing information and real-time meteorological monitoring data of an automatic meteorological station are combined, ultra-short-term power prediction of a distributed photovoltaic power generation cluster is achieved, the utilization efficiency of green energy is improved to the maximum extent, and the safety of a power grid 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 relates to the technical field of weather station detectors, in particular to an automatic weather station five-element signal comprehensive fault detector and system, which comprises a power supply box, a control circuit board and a voltmeter, and is characterized in that the voltmeter and the power supply box are electrically coupled with the control circuit board; the control circuit board is electrically coupled with a rainfall sensor, a wind speed sensor, a wind direction sensor, a temperature sensor and a humidity sensor; in the invention, the requirements of field maintenance work are combined, the functions of main maintenance tools are replaced, the main maintenance tools comprise a mechanical multimeter, an electric multimeter, a rainfall counter, a maintenance power supply, an oscilloscope, a frequency meter and the like, the maintenance operation and fault judgment are very simple and direct, independent pulse signal fault maintenance can be carried out on each sensor separated from a collector, and the maintenance efficiency is greatly improved. And pulse signal data of each element can be measured on line, and a fault part can be well determined by comparing according to a detection result, so that the maintenance is more convenient, faster and more accurate, the consumed time is less, and the efficiency is high.

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 invention discloses an urban local environment air temperature effect characteristic analysis method, which comprises the following steps of: representing a base station by using a conventional weather station, representing a specific environment station by using an encrypted automatic weather station, judging the representation range of the base station according to a Thiessen polygon, and judging local environment air temperature effect characteristics by comparing the air temperature of the encrypted station and the air temperature of the base station. The air temperature observation data processing comprises the steps of initial data quality control, air temperature effect intensity calculation and ambiguity value screening, statistical time period determination and the like, and the result can provide reference for local environment air temperature effect research, urban planning and construction and the like.

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 discloses a remote data return method and system for an automatic meteorological station in a depopulated area, and relates to the technical field of meteorological data transmission, and the method comprises the steps: collecting temperature, humidity, air pressure and wind speed data monitored by a meteorological station, and generating a multi-type meteorological data set; obtaining a signal quality score through a signal quality monitoring strategy in combination with the multi-type meteorological data set; obtaining meteorological importance indexes of all to-be-distributed data through a priority evaluation algorithm, and forming a priority queue; setting a meteorological data hierarchical return strategy, and distributing a transmission period for all the to-be-distributed data according to the priority queue; and uploading the received data to a receiving platform. According to the invention, the problems of limited system resources and easy data loss of meteorological data under the condition of unstable signals or severe environment are solved.

The invention relates to a short-time forecasting and correcting method for visibility of an expressway. The method comprises the following steps: acquiring 10-minute meteorological observation historical data of traffic meteorological observation stations along a measured road section of the expressway; calculating a Pearson's correlation coefficient between the visibility and each meteorological factor, and carrying out significance test; acquiring hour-by-hour real-time meteorological observation data along the measured road section of the expressway; training the LSTM prediction model to obtain visibility prediction results of stake marks per 10 minutes in the future 2 hours; the method comprises the following steps: performing probability correction on a visibility prediction result by using visibility observation data obtained from an automatic weather station, performing trend correction on the visibility prediction result by using visibility data inverted by a video image and obtained along a highway, and correcting a subsequent new visibility prediction result by using a correction result. And obtaining visibility forecasting results of stake marks and 10-minute intervals along the measured road section of the expressway within 0-2 hours of short-time adjacent time.

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.