Low-altitude meteorological element real-time sensing system

Abstract

The invention discloses a low-altitude meteorological element real-time sensing system, relates to the technical field of meteorological data monitoring, and solves the technical problems that comprehensive analysis of space consistency and time consistency is lacked, real changes of meteorological elements are difficult to accurately distinguish from equipment faults, data transmission errors and the like, and abnormity is caused. According to the invention, through comprehensive analysis of space consistency and time consistency, dynamic threshold adjustment and multi-algorithm fusion, meteorological data abnormity can be accurately identified, real meteorological changes and data quality problems are effectively distinguished, data accuracy and reliability are improved, and the method is suitable for large-scale popularization and application. The abnormal quality analysis module and the comprehensive processing analysis module realize rapid positioning and predictive maintenance of equipment faults through deep mining and trend analysis of abnormal data, and meanwhile, the normal quality analysis module performs refined metadata management and regular evaluation on the data, so that powerful support is provided for long-term analysis and application of meteorological data.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological data monitoring, and particularly to a real-time low-altitude meteorological element perception system. Background Art

[0002] With the rapid development of the low-altitude economy, low-altitude flight activities such as unmanned aerial vehicle logistics and short-distance general aviation transportation are becoming increasingly frequent, posing higher requirements for the real-time monitoring and accurate forecasting of low-altitude meteorological elements.

[0003] According to the patent application with the publication number CN119848442B, a multi-meteorological element data prediction method based on fine-tuning training of a deep neural network is disclosed, including preprocessing a multi-meteorological data set to obtain a preliminary prediction result, and segmenting the preliminary prediction result by meteorological elements or by time steps; respectively matching each time series with a general lightweight fine-tuning module for fine-tuning, and fully extracting features through a multi-layer perceptron composed of multiple linear layers; multiplying the output of the linear layer by the weight V obtained by layer normalization to obtain the prediction result corresponding to the lightweight fine-tuning module; and finally combining the results of each lightweight fine-tuning module.

[0004] Traditional low-altitude meteorological monitoring systems mainly rely on single means such as ground meteorological stations and sounding balloons, and have problems such as limited data collection range, insufficient real-time performance, and weak multi-source data fusion ability. At the same time, in terms of data quality control, existing systems often only identify abnormal data through simple threshold judgment, lacking comprehensive analysis of spatial consistency and temporal consistency, and it is difficult to accurately distinguish the true changes of meteorological elements from abnormalities caused by equipment failures, data transmission errors, etc., and cannot meet the requirements of low-altitude flight for high reliability and high accuracy of meteorological data. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a real-time low-altitude meteorological element perception system, which solves the problem of lack of comprehensive analysis of spatial consistency and temporal consistency, and it is difficult to accurately distinguish the true changes of meteorological elements from abnormalities caused by equipment failures, data transmission errors, etc.

[0006] To achieve the above object, the present invention is realized through the following technical solutions: A real-time low-altitude meteorological element perception system, comprising: A data quality control processing module, configured to perform quality control processing on the meteorological element data transmitted by the meteorological element data acquisition module, and judge whether there are quality problems based on temporal and spatial consistency analysis, generate a quality normal or abnormal signal, and transmit the two respectively; A normal quality analysis module, configured to analyze the quality normal signal, perform metadata management on the meteorological element data, and perform periodic evaluation, generate data evaluation information, and transmit it to the processing information output module; An abnormal quality analysis module is used to analyze quality abnormal signals, determine the acquisition devices corresponding to abnormal data and the quantity of data, calculate the abnormal deviation value of the abnormal data, and at the same time calculate the proportion of the corresponding abnormal quantity, compare it with a preset value, generate a secondary analysis signal, and then transmit it to the comprehensive processing and analysis module; A comprehensive processing and analysis module is used to analyze the obtained secondary analysis signal, obtain the specific deviation of the abnormal times of the acquisition device, judge the deviation trend to generate a deviation increase or decrease signal, and at the same time analyze both of them respectively to generate device normal or abnormal information, and then transmit it to the processing information output module.

[0007] As a further solution of the present invention, it further includes a meteorological element data acquisition module and a processing information output module; A meteorological element data acquisition module is used to acquire meteorological element data, where the meteorological element data includes low-altitude air temperature, wind speed, wind direction, humidity, air pressure, and visibility data, and at the same time transmit it to the data quality control and processing module; A processing information output module is used to display the obtained data evaluation information and device normal or abnormal information to the corresponding management personnel.

[0008] As a further solution of the present invention, the specific way for the quantity quality control and processing module to generate a quality normal or abnormal signal is: Judge the meteorological element data from two aspects of spatial and temporal consistency. If any group of anomalies exists in temporal or spatial consistency, generate a quality abnormal signal and transmit it to the abnormal quality analysis module at the same time. If both temporal and spatial consistency are normal, generate a quality normal signal and transmit it to the normal quality analysis module at the same time.

[0009] As a further solution of the present invention, the specific way for the quantity quality control and processing module to judge the meteorological element data from two aspects of spatial and temporal consistency is: For the judgment of spatial consistency, the data difference between adjacent stations at the same moment should not exceed the empirical threshold, which means normal, otherwise it means abnormal; For the judgment of temporal consistency, the data change rate of the same station needs to conform to meteorological laws, which means normal, otherwise it means abnormal; And so on to judge all the meteorological element data.

[0010] As a further solution of the present invention, the specific way for the abnormal quality analysis module to analyze the quality abnormal signal is: Screen out the meteorological data determined to be abnormal through spatial and temporal consistency analysis, mark the acquisition devices that generate abnormal data, number them by type as i, and i = 1, 2, …, j, where j represents the type of acquisition device. Count the number of abnormal data of the same type generated by each acquisition device, calculate the difference between the abnormal data and the mean value of the normal data of the same type, which is denoted as the abnormal deviation value, and calculate the proportion of the abnormal deviation value in all meteorological data of the same type, which is denoted as the abnormal quantity proportion. Compare the obtained abnormal quantity proportion with the preset value. If the abnormal quantity proportion is greater than the preset value, it indicates that there is an overall abnormality in the acquisition device, and a secondary analysis signal is generated. If the abnormal quantity proportion is less than the preset value, it indicates that the acquisition device is normal.

[0011] As a further solution of the present invention, the specific manner in which the comprehensive processing and analysis module processes the secondary analysis signal is as follows: Obtain the historical data of the acquisition device, record the number of times the device has an abnormality, and label it as n, and n = 1, 2, …, m, where m represents the number of abnormality times. Calculate the deviation value between each abnormal data and the normal data, analyze all abnormal deviations, and judge whether the data deviation shows an increasing or decreasing trend. If the data deviation shows an increasing trend, a deviation increasing signal is generated. Conversely, if the data deviation shows a decreasing trend, a deviation decreasing signal is generated.

[0012] As a further solution of the present invention, the specific manner in which the comprehensive processing and analysis module generates device normal or abnormal information is as follows: Analyze the generated deviation increasing signal, generate device abnormal information based on the corresponding acquisition device as the standard, and transmit it to the processing information output module at the same time. Analyze the generated deviation decreasing signal, obtain the number of abnormal data corresponding to the number of abnormality times n, and analyze the change situation of the number of abnormal data. If the number of abnormal data shows an increasing change, it indicates that the acquisition device is abnormal, and device abnormal information is generated. Conversely, if the number of abnormal data shows a decreasing change, it indicates that the acquisition device is normal, and device normal information is generated.

[0013] The present invention provides a low-altitude meteorological element real-time perception system. Compared with the prior art, it has the following beneficial effects: The present invention realizes the all-round and high-density acquisition of meteorological elements in the low-altitude area by integrating a variety of advanced detection devices, such as lidar, meteorological observation drones, etc., filling the monitoring blind area. By adopting redundant communication links and data verification technologies, it ensures the real-time and stable transmission of data, improving the timeliness and integrity of meteorological data.

[0014] Through the comprehensive analysis of spatial consistency and temporal consistency, combined with dynamic threshold adjustment and multi-algorithm fusion, the present invention can accurately identify abnormal meteorological data, effectively distinguish real meteorological changes from data quality problems, and improve data accuracy and reliability. For example, when judging abnormal wind speed data, not only the differences between neighboring stations at the same moment are considered, but also the time change rate and weather system conditions are combined to avoid misjudgment and missed judgment.

[0015] The abnormal quality analysis module and the comprehensive processing and analysis module of the present invention realize the rapid positioning of equipment failures and predictive maintenance through in-depth mining and trend analysis of abnormal data. At the same time, the normal quality analysis module conducts refined metadata management and regular evaluation of the data, providing strong support for the long-term analysis and application of meteorological data, and improving the intelligent management level and business guarantee ability of the entire low-altitude meteorological element real-time perception system. Brief Description of the Drawings

[0016] Figure 1 It is a system block diagram of the present invention. Detailed Embodiments

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiment 1: Please refer to Figure 1 , the present application provides a low-altitude meteorological element real-time perception system, including a meteorological element data acquisition module, a data quality control and processing module, an abnormal quality analysis module, a normal quality analysis module, a comprehensive processing and analysis module, and a processing information output module. Combining Figure 1 It can be known that the above functional modules are connected in a one-way electrical manner.

[0019] The meteorological element data acquisition module is used to acquire meteorological element data and transmit it to the data quality control and processing module, and the meteorological element data includes low-altitude air temperature, wind speed, wind direction, humidity, air pressure, visibility, etc.

[0020] The data quality control and processing module is used to conduct quality detection and analysis on the acquired meteorological element data. Specifically, it conducts a comprehensive analysis from both spatial consistency and temporal consistency to judge whether there are abnormalities in the meteorological element data; For the judgment of spatial consistency, the data difference between neighboring stations at the same moment should not exceed the empirical threshold (for example, if the temperature difference between adjacent stations 10 kilometers apart > 5°C, it is considered suspicious); For the judgment of time consistency, the data change rate of the same site should conform to meteorological laws (for example, when the wind speed mutation > 5 m / s / min and there is no impact of weather systems, it is regarded as abnormal). Based on the above analysis, if there is any group of anomalies in time or space consistency, it means that there are problems with the quality of the collected meteorological element data, and a quality anomaly signal is generated. At the same time, it is transmitted to the abnormal quality analysis module. If both time and space consistency are normal, it means that there are no problems with the quality of the collected meteorological element data, and a quality normal signal is generated. At the same time, it is transmitted to the normal quality analysis module.

[0021] Suppose there are three meteorological automatic observation stations A, B, and C in a certain area. Among them, the distance between A and B is 8 kilometers, and the distance between B and C is 12 kilometers. At 14:00:00 on June 10, 2025, the meteorological element data collected by each site is as follows:

[0022] Spatial consistency analysis Air temperature: The temperature difference between stations A and B is 2°C, and the temperature difference between stations B and C is 1°C, both of which do not exceed the set threshold of 5°C. The spatial consistency of the air temperature data is normal. Wind speed: The wind speed difference between stations A and B is 5 m / s. Since the distance between stations A and B is relatively close and there is no obvious weather system passing by (judged by radar echo and satellite cloud image), the wind speed difference of 5 m / s exceeds the normal fluctuation range, marked as abnormal spatial consistency of wind speed data, triggering a yellow warning. Time consistency analysis: By checking the wind speed data of station B in the past 10 minutes, it is found that the wind speed at 13:55:00 is 3 m / s and suddenly changes to 8 m / s within 5 minutes. The change rate is 1 m / s / min, which does not exceed the set threshold of 5 m / s / min. And combined with the weather situation judgment, there is no impact of strong convection and other weather systems at this time. Therefore, this mutation is an abnormal situation, marked as abnormal time consistency, triggering a yellow warning.

[0023] Since the data of station B shows anomalies in both spatial consistency and time consistency, the data quality control processing module generates a quality anomaly signal and transmits it to the abnormal quality analysis module.

[0024] The normal quality analysis module is used to analyze the obtained quality normal signal and manage the metadata of the obtained meteorological element data. Specifically, metadata (such as equipment number, collection time, calibration status, quality flag, etc.) is attached to each piece of data. At the same time, the meteorological element data is regularly evaluated at a time period T to generate corresponding data evaluation information and transmit it to the processing information output module.

[0025] Specifically, in addition to basic metadata such as device number, collection time, calibration status, and quality label, information such as sensor model, data collection frequency, data source path, data transmission protocol, and device installation longitude and latitude is added. Taking the data collected by a lidar wind sensor as an example, metadata such as its model (e.g., a certain brand of S-band lidar), collection frequency (once per second), and the path from the lidar device to the data center via the 5G network are recorded, providing richer information for subsequent data traceability, device performance analysis, and transmission link optimization.

[0026] At the same time, different evaluation periods T are set according to the change characteristics of meteorological elements and business requirements. For scenarios with drastic weather changes and high real-time requirements (such as heavy rain warning and severe convective weather monitoring), T is set to 1 hour or shorter to grasp the quality of meteorological data in real time; for scenarios such as climate research that focus on long-term data trends, T can be set to 1 month or 1 year for macroscopic data quality assessment.

[0027] The processing information output module is used to display the obtained data evaluation information to the corresponding management personnel.

[0028] Embodiment 2: As Embodiment 2 of the present invention, it is implemented on the basis of Embodiment 1, and the differences from Embodiment 1 are as follows: The abnormal quality analysis module is used to analyze the obtained quality abnormal signals to obtain abnormal data in meteorological element data. Here, the abnormal data is obtained after spatial and temporal consistency analysis. At the same time, according to the obtained abnormal data, the corresponding collection device is obtained and labeled as i, where i = 1, 2,..., j, and j represents the type of collection device. Then, the number of abnormal data corresponding to the collection device i is obtained. Here, the abnormal data represents the same type of meteorological data, and the data difference between the abnormal data and the normal data is calculated and recorded as the abnormal deviation value. The normal data represents the numerical mean corresponding to the same type of meteorological data, specifically the data without differences. At the same time, the ratio of the abnormal deviation value to the same type of meteorological element data is calculated and recorded as the abnormal quantity ratio. Here, the same type of meteorological element data is all the same type of data; The obtained abnormal quantity ratio is compared with a preset value, and the specific value of the preset value is set by the operator. If the abnormal quantity ratio is greater than the preset value, it indicates that the overall collection device is abnormal, and a secondary analysis signal is generated and transmitted to the comprehensive processing and analysis module. If the abnormal quantity ratio is less than the preset value, it indicates that the collection device is normal, and a normal deviation information is generated and transmitted to the processing information output module.

[0029] For example, assume that a real-time perception system for low-altitude meteorological elements includes 10 automatic meteorological observation stations. Among them, Station A-03 was determined to have abnormal wind speed data during the period from 14:00 to 15:00 on June 10, 2025. A total of 15 abnormal wind speed data records were obtained for Station A-03 during this period. The normal data (the average wind speed data of the other 9 stations during the same period) was 4 m / s. The wind speed values of the abnormal data ranged from 8 to 12 m / s, and the calculated abnormal deviation value was 4 to 8 m / s. There were a total of 360 wind speed data records in the system during this period. The calculated proportion of abnormal data was 15÷360×100%≈4.17%.

[0030] Since it is currently the windy season in summer, the preset value for the proportion of abnormal wind speed data set by the operator is 3%. 4.17% is greater than 3%, so a secondary analysis signal is generated and transmitted to the comprehensive processing and analysis module.

[0031] Comprehensive processing and analysis module. This module is used to process the obtained secondary analysis signal, obtain the historical data of the corresponding acquisition device, and at the same time obtain the number of anomalies corresponding to the acquisition device, denoted as n, and n = 1, 2, …, m, where m represents the number of anomaly times, and obtain the specific deviation situation corresponding to the anomaly times. Here, the specific deviation situation is expressed as the corresponding deviation value. Integrate all the specific deviation situations of the anomaly times for analysis, judge the deviation trend, and generate a deviation increasing signal or a deviation decreasing signal; Analyze the generated deviation increasing signal, generate device anomaly information based on the corresponding acquisition device as a standard, and at the same time transmit it to the processing information output module; Analyze the generated deviation decreasing signal, obtain the number of abnormal data corresponding to the anomaly times n. Here, the number of abnormal data is expressed as the number of the same type of data corresponding to a single anomaly time, and analyze the change situation of the number of abnormal data. If the number of abnormal data shows an increasing change, it indicates that the acquisition device is abnormal, and generate device anomaly information. On the contrary, if the number of abnormal data shows a decreasing change, it indicates that the acquisition device is normal, and generate device normal information. At the same time, transmit both to the processing information output module.

[0032] Processing information output module. This module is used to display the obtained device normal or device anomaly information to the corresponding management personnel.

[0033] Embodiment 3: As Embodiment 3 of the present invention, the key lies in combining the implementation processes of Embodiment 1 and Embodiment 2 for implementation.

[0034] Some of the data in the above formula are taken for numerical calculation without substituting parameter units for calculation. At the same time, the content not described in detail in this specification belongs to the well-known prior art in the art.

[0035] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A real-time low-altitude meteorological element perception system, characterized in that, Including: A data quality control processing module, which is used to perform quality control processing on the meteorological element data transmitted by the meteorological element data acquisition module, judge whether there are quality problems based on time and space consistency analysis, generate quality normal or abnormal signals, and transmit them respectively; A normal quality analysis module, which is used to analyze the quality normal signal, manage the metadata of the meteorological element data, and perform periodic evaluation, generate data evaluation information, and transmit it to the processing information output module at the same time; An abnormal quality analysis module, which is used to analyze the quality abnormal signal, determine the acquisition device corresponding to the abnormal data and the data quantity, calculate the abnormal deviation value of the abnormal data, calculate the proportion of the corresponding abnormal quantity at the same time, compare it with the preset value, generate a secondary analysis signal, and then transmit it to the comprehensive processing and analysis module; A comprehensive processing and analysis module, which is used to analyze the obtained secondary analysis signal, obtain the specific deviation of the abnormal times of the acquisition device, judge the deviation trend to generate a deviation increase or decrease signal, analyze the two respectively at the same time, generate device normal or abnormal information, and then transmit it to the processing information output module.

2. The real-time perception system for low-altitude meteorological elements according to claim 1, characterized in that It also includes a meteorological element data acquisition module and a processing information output module; The meteorological element data acquisition module is used to collect meteorological element data, where the meteorological element data includes low-altitude air temperature, wind speed, wind direction, humidity, air pressure, visibility data, and transmit it to the data quality control processing module at the same time; The processing information output module is used to display the obtained data evaluation information and device normal or abnormal information to the corresponding management personnel.

3. The real-time perception system for low-altitude meteorological elements according to claim 1, characterized in that, The specific way for the quantity quality control processing module to generate quality normal or abnormal signals is: Judge the meteorological element data from two aspects of space and time consistency respectively. If there is any group of anomalies in time or space consistency, generate a quality abnormal signal and transmit it to the abnormal quality analysis module at the same time. If both time and space consistency are normal, generate a quality normal signal and transmit it to the normal quality analysis module at the same time.

4. The real-time low-altitude meteorological element perception system according to claim 3, characterized in that, The specific way for the quantity quality control processing module to judge the meteorological element data from two aspects of space and time consistency is: For the judgment of space consistency, the data difference between adjacent stations at the same moment should not exceed the empirical threshold, which means normal, otherwise it means abnormal; For the judgment of time consistency, the data change rate of the same station needs to conform to the meteorological law, which means normal, otherwise it means abnormal; And so on to judge all meteorological element data.

5. A real-time low-altitude meteorological element perception system according to claim 1, characterized in that, The specific way for the abnormal quality analysis module to analyze the quality abnormal signal is: Screen out the meteorological data determined to be abnormal through space and time consistency analysis, mark the acquisition device that generates the abnormal data, number it as i according to the type, and i = 1, 2,..., j, where j represents the type of the acquisition device corresponding to it, count the quantity of the same type of abnormal data generated by each acquisition device, calculate the difference between the abnormal data and the average value of the same type of normal data and record it as the abnormal deviation value, and calculate the proportion of the abnormal deviation value in all the same type of meteorological data and record it as the abnormal quantity proportion; Compare the obtained proportion of the number of exceptions with a preset value. If the proportion of the number of exceptions is greater than the preset value, it indicates that there is an overall exception in the acquisition device and a secondary analysis signal is generated. If the proportion of the number of exceptions is less than the preset value, it indicates that the acquisition device is normal.

6. The real-time low-altitude meteorological element perception system according to claim 1, characterized in that, The specific way for the comprehensive processing and analysis module to process the secondary analysis signal is as follows: Obtain the historical data of the acquisition device, record the number of times the device has an exception, and label it as n, where n = 1, 2, …, m, and m represents the number of exception times. Calculate the deviation value between each exception data and the normal data, analyze all exception deviations, and judge whether the data deviation shows an increasing or decreasing trend; If the data deviation shows an increasing trend, a deviation increasing signal is generated. On the contrary, if the data deviation shows a decreasing trend, a deviation decreasing signal is generated.

7. The real-time perception system for low-altitude meteorological elements according to claim 1, characterized in that The specific way for the comprehensive processing and analysis module to generate device normal or abnormal information is as follows: Analyze the generated deviation increasing signal, generate device abnormal information based on the corresponding acquisition device as the standard, and at the same time transmit it to the processing information output module; Analyze the generated deviation decreasing signal, obtain the number of exception data corresponding to the exception times n, and analyze the change situation of the number of exception data. If the number of exception data shows an increasing change, it indicates that the acquisition device is abnormal and device abnormal information is generated. On the contrary, if the number of exception data shows a decreasing change, it indicates that the acquisition device is normal and device normal information is generated.

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