A meteorological evaluation method, device and medium based on real-time measurement of meteorological elements

Abstract

The application discloses a kind of meteorological evaluation methods, equipment and medium based on meteorological element real-time measurement, is specifically related to meteorological evaluation technical field, and the equipment aging index, data transmission error index and electromagnetic interference index obtained by the present application are normalized, to obtain data accuracy coefficient, compare data accuracy coefficient with preset data accuracy coefficient threshold, and adjust the meteorological element data collected according to the comparison result, to obtain final meteorological element data, and input meteorological element data into preset meteorological evaluation model, evaluate the weather, by the above-mentioned mode, the meteorological element data collected can be sensed in time, and adjusted, so that meteorological element data is more accurate, so that the result of evaluation is more accurate, can provide accurate weather forecast and meteorological service in time.

Description

Technical Field

[0001] This invention relates to the field of meteorological assessment technology, specifically to a meteorological assessment method, equipment, and medium based on real-time measurement of meteorological elements. Background Technology

[0002] Meteorological assessment methods based on real-time measurement of meteorological elements refer to the use of various meteorological instruments and sensors to collect meteorological element data in real time, such as temperature, humidity, wind speed, and precipitation. By analyzing and calculating the collected meteorological element data, current and future meteorological conditions are assessed to provide accurate weather forecasts and meteorological services, so as to effectively respond to and mitigate the impact of natural disasters, support decision-making and planning in industries such as agriculture, transportation, and energy, ensure public safety, and promote the smooth operation of social and economic activities.

[0003] Traditional meteorological assessment methods based on real-time measurements of meteorological elements generally assume that the collected meteorological element data is accurate and directly analyze it to assess the weather. However, in the actual meteorological element data collection process, if errors in the collected data are not detected in time, and the collected meteorological element data is still used for assessment and analysis, the assessment results may be inaccurate, and timely and accurate weather forecasts and meteorological services cannot be provided. Summary of the Invention

[0004] The purpose of this invention is to solve the problem that, in the actual process of meteorological element data collection, if deviations in the collected data are not detected in time, and the collected meteorological element data is still used for meteorological evaluation and analysis, the evaluation results may be inaccurate and timely accurate weather forecasts and meteorological services may not be provided. Therefore, this invention proposes a meteorological evaluation method, equipment and medium based on real-time measurement of meteorological elements.

[0005] In a first aspect of this invention, a meteorological assessment method based on real-time measurement of meteorological elements is proposed, the method comprising:

[0006] When acquiring meteorological element data in real time, the equipment aging data of the equipment is collected, and the equipment aging index is obtained based on the equipment aging data.

[0007] When acquiring meteorological element data in real time, the data transmission information during the transmission process is collected, and a data transmission error index is obtained based on the transmission information data.

[0008] When acquiring meteorological element data in real time, electromagnetic interference data information around the equipment is collected during the acquisition process, and the electromagnetic interference index is obtained based on the electromagnetic interference data information.

[0009] The obtained equipment aging index, data transmission error index and electromagnetic interference index are normalized to obtain the data accuracy coefficient.

[0010] The data accuracy coefficient is compared with the preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison results to obtain the final meteorological element data. The final meteorological element data is then input into the preset meteorological assessment model to evaluate the meteorology.

[0011] Optionally, when acquiring meteorological element data in real time, the equipment aging data of the acquisition equipment is collected, and the equipment aging index is obtained based on the equipment aging data, including:

[0012] Equipment aging data includes equipment response latency index and equipment maintenance index. The equipment response latency index is obtained as follows:

[0013] Obtain the actual response time and the corresponding preset response time of the target acquisition device at different times within time T, and mark the actual response time and the corresponding preset response time as follows: and , This indicates the sequence number of the actual response time and the corresponding preset response time at different times. =1, 2, 3, 4, ... , It is a positive integer;

[0014] The device response latency exponent is calculated using the following expression: In the formula, This indicates the device response latency index.

[0015] Optionally, the equipment maintenance index can be obtained as follows:

[0016] Obtain the time difference between the last maintenance time of the target acquisition device and the current time to obtain the maintenance time interval. ;

[0017] Obtain the average maintenance time of the target acquisition device from the time of its use to the current time. and the maintenance interval Divide by mean repair time The equipment maintenance index is obtained by using the following formula: In the formula, Indicates the equipment maintenance index;

[0018] The equipment aging index is obtained by weighted summation of the equipment response delay index and the equipment maintenance index. The formula for calculation is as follows: In the formula, This refers to the equipment aging index. and This represents the preset weighting coefficients for the equipment response delay index and the equipment maintenance index.

[0019] Optionally, when acquiring meteorological element data in real time, the data transmission information during the transmission process is included, and a data transmission error index is obtained based on the transmission information data, including:

[0020] The data transmission error index includes a data transmission quantity error index and a data time delay index, wherein the data transmission error index includes:

[0021] Obtain the actual number of meteorological element data collected by the acquisition device at different times within time T and upload them to the analysis system, along with the corresponding preset number of data uploads. Mark the actual number of data uploads and the corresponding preset number of data uploads as follows: and , This indicates the actual number of data uploads at different times and the corresponding sequence number of the preset data upload count. =1, 2, 3, 4, ... , It is a positive integer;

[0022] according to and Obtain the data transmission error index The calculation formula is: .

[0023] Optionally, the data transmission time delay index includes:

[0024] When meteorological element data collected by the acquisition device at different times within time T is uploaded to the analysis system, the actual upload time stamp of the data is as follows: , The number representing the actual number of times the data was transmitted. =1, 2, 3, 4, ... , It is a positive integer;

[0025] Will Within the preset data upload time range Re-mark the time outside of time, and mark it as , Indicates the actual upload time Within the preset data upload time range The number of times outside of time, =1, 2, 3, 4, ... , For positive integers; calculate the data transmission time delay exponent. The calculation formula is: ;

[0026] The data transmission error index is calculated using the following formula: In the formula, This is the data transmission error index. and The preset weighting coefficients represent the data transmission error index and the data time delay index.

[0027] Optionally, the logic for obtaining the electromagnetic interference index is as follows:

[0028] When acquiring meteorological element data, electromagnetic interference signals around the acquisition equipment at different times within time T during the acquisition process are recorded and tagged as follows: ,in, =1, 2, 3, 4, ... , It is a positive integer. Indicates the number of electromagnetic interference signals;

[0029] use Wavelet analysis of electromagnetic interference signals at each time step Continuous wavelet transform is performed to decompose the electromagnetic interference signal in both the time and frequency domains. The continuous wavelet transform is achieved through convolution, and its calculation formula is as follows: In the formula, It is the input signal. It is the selected wavelet basis function. It is a scaling parameter used to adjust the scale of the wavelet basis function; These are translation parameters used to adjust the position of the wavelet basis functions; The time coordinates of the signal, i.e., its position on the time axis;

[0030] For each scale Peaceful relocation The results calculated using wavelet transform are called wavelet coefficients;

[0031] Energy features are extracted from wavelet coefficients. Based on the calculated wavelet coefficients, energy features are further extracted by calculating the energy of the wavelet coefficients at each scale. Then, the energies at different scales are weighted and summed to obtain the comprehensive energy features. The calculation formula is as follows: In the formula, In scale The energy below, These are wavelet coefficients;

[0032] The electromagnetic interference index is calculated at each moment using the following expression: In the formula, Electromagnetic interference index;

[0033] Electromagnetic interference index at different times within time T Add them together to get the electromagnetic interference index. The formula for calculation is: In the formula, This represents the electromagnetic interference index.

[0034] Optionally, the acquired equipment aging index, data transmission error index, and electromagnetic interference index are normalized to obtain data accuracy coefficients, including:

[0035]

[0036] In the formula, The accuracy coefficient of the data. , and These are the equipment aging index, data transmission error index, and electromagnetic interference index, respectively. These are preset proportional coefficients for the equipment aging index, data transmission error index, and electromagnetic interference index, respectively. The average score is greater than 0.

[0037] Optionally, the data accuracy coefficient is compared with a preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison result to obtain the final meteorological element data, including:

[0038] The data accuracy coefficient is compared with the preset data accuracy coefficient threshold. If the data accuracy coefficient is less than the preset data accuracy coefficient threshold, the collected meteorological element data is directly input into the preset meteorological assessment model to assess the weather.

[0039] If the data accuracy coefficient is not less than the preset data accuracy coefficient threshold, it indicates that the accuracy of the collected meteorological element data is low. In this case, it is necessary to adjust the collected meteorological element data according to the size of the data accuracy coefficient to obtain the final meteorological element data, and then input the final meteorological element data into the preset meteorological assessment model to assess the meteorology.

[0040] In a second aspect of the present invention, an electronic device is provided, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus.

[0041] Memory, used to store computer programs;

[0042] When a processor executes a program stored in memory, it implements any of the steps described above.

[0043] In a third aspect of the present invention, a computer-readable storage medium is provided, characterized in that the computer-readable storage medium stores a computer program, which, when processed, executes the steps of any of the methods described above.

[0044] The beneficial effects of this invention are:

[0045] This invention proposes a meteorological assessment method based on real-time measurement of meteorological elements. By acquiring equipment aging index, data transmission error index, and electromagnetic interference index, and performing normalization processing, a data accuracy coefficient is obtained. This data accuracy coefficient is compared with a preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted based on the comparison result to obtain the final meteorological element data. This meteorological element data is then input into a preset meteorological assessment model to evaluate the weather. Through this method, the collected meteorological element data can be sensed and adjusted in a timely manner, resulting in more accurate meteorological element data and more accurate assessment results, enabling the timely provision of accurate weather forecasts and meteorological services. Attached Figure Description

[0046] The present invention will now be further described with reference to the accompanying drawings.

[0047] Figure 1 A flowchart illustrating a meteorological assessment method based on real-time measurement of meteorological elements, provided as an embodiment of the present invention;

[0048] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0050] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] This invention provides a meteorological assessment method based on real-time measurement of meteorological elements. See also... Figure 1 , Figure 1 A flowchart illustrating a meteorological assessment method based on real-time measurement of meteorological elements, provided as an embodiment of the present invention. The method includes the following steps:

[0052] When acquiring meteorological element data in real time, the equipment aging data of the equipment is collected, and the equipment aging index is obtained based on the equipment aging data.

[0053] When acquiring meteorological element data in real time, the data transmission information during the transmission process is collected, and a data transmission error index is obtained based on the transmission information data.

[0054] When acquiring meteorological element data in real time, electromagnetic interference data information around the equipment is collected during the acquisition process, and the electromagnetic interference index is obtained based on the electromagnetic interference data information.

[0055] The obtained equipment aging index, data transmission error index and electromagnetic interference index are normalized to obtain the data accuracy coefficient.

[0056] The data accuracy coefficient is compared with the preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison results to obtain the final meteorological element data. The final meteorological element data is then input into the preset meteorological assessment model to evaluate the meteorology.

[0057] This invention provides a meteorological assessment method based on real-time measurement of meteorological elements. The method acquires equipment aging index, data transmission error index, and electromagnetic interference index, and performs normalization processing to obtain a data accuracy coefficient. This coefficient is then compared with a preset data accuracy coefficient threshold. Based on the comparison result, the collected meteorological element data is adjusted to obtain the final meteorological element data. This data is then input into a preset meteorological assessment model to evaluate the weather. Through this method, the collected meteorological element data can be promptly sensed and adjusted, resulting in more accurate meteorological element data and more accurate assessment results. This enables the timely provision of accurate weather forecasts and meteorological services.

[0058] In one embodiment, when acquiring meteorological element data in real time, the equipment aging data of the acquisition equipment is collected, and the equipment aging index is obtained based on the equipment aging data, including:

[0059] Equipment aging data includes equipment response latency index and equipment maintenance index. The equipment response latency index is obtained as follows:

[0060] Obtain the actual response time and the corresponding preset response time of the target acquisition device at different times within time T, and mark the actual response time and the corresponding preset response time as follows: and , This indicates the sequence number of the actual response time and the corresponding preset response time at different times. =1, 2, 3, 4, ... , It is a positive integer;

[0061] The device response latency exponent is calculated using the following expression: In the formula, Indicates the device response latency index;

[0062] The method for obtaining the equipment maintenance index is as follows:

[0063] Obtain the time difference between the last maintenance time of the target acquisition device and the current time to obtain the maintenance time interval. ;

[0064] Obtain the average maintenance time of the target acquisition device from the time of its use to the current time. and the maintenance interval Divide by mean repair time The equipment maintenance index is obtained by using the following formula: In the formula, Indicates the equipment maintenance index;

[0065] The equipment aging index is obtained by weighted summation of the equipment response delay index and the equipment maintenance index. The formula for calculation is as follows: In the formula, This refers to the equipment aging index. and This represents the preset weighting coefficients for the equipment response delay index and the equipment maintenance index.

[0066] It should be noted that the actual response time of the target acquisition device at different times within time T can be obtained in real time by the monitoring system in the meteorological assessment system based on real-time measurement of meteorological elements. Furthermore, the corresponding preset response time refers to the specific interval at which the acquisition device responds, as set in advance; the specific value is not limited. The maintenance interval and the average maintenance time from the start of use to the current time for the target acquisition device can be obtained from the maintenance log; the specific values ​​are not limited.

[0067] It should be noted that the equipment aging index refers to the degree of equipment response delay and the length of equipment maintenance intervals when collecting meteorological element data. A higher degree of equipment response delay and a longer maintenance interval indicate a greater likelihood of errors in the collected meteorological element data. Using this collected meteorological element data for meteorological evaluation and analysis may lead to inaccurate evaluation results and prevent the timely provision of accurate weather forecasts and services. The reasons are as follows:

[0068] Increased response delay: As equipment ages, sensors react more slowly to changes in meteorological elements and cannot reflect actual environmental changes in a timely manner. This delay causes data to lag behind reality, and delayed measurement data cannot accurately reflect real-time weather conditions. Especially under rapidly changing weather conditions (such as thunderstorms, sudden strong winds, etc.), the delay will lead to significant error accumulation. Due to data lag, the accuracy of real-time meteorological data is reduced, making it difficult to capture instantaneous changes. The input error of meteorological assessment and prediction models based on delayed data increases, resulting in inaccurate prediction results.

[0069] Untimely maintenance: Aging equipment leads to frequent failures. Long maintenance intervals mean that the equipment may be in a sub-healthy or faulty state for a long time, affecting data quality. Equipment that has not been maintained for a long time is more likely to experience unpredictable failures, such as sensor drift and data transmission errors. These problems will directly affect the stability and accuracy of data acquisition.

[0070] Therefore, when collecting meteorological data, the greater the equipment response delay and the longer the equipment maintenance interval, the higher the degree of equipment aging.

[0071] In one embodiment, when acquiring meteorological element data in real time, the transmission information data of the meteorological element data during the transmission process, and the data transmission error index obtained based on the transmission information data, include:

[0072] The data transmission error index includes a data transmission quantity error index and a data time delay index. The data transmission error index includes:

[0073] Obtain the actual number of meteorological element data collected by the acquisition device at different times within time T and upload them to the analysis system, along with the corresponding preset number of data uploads. Mark the actual number of data uploads and the corresponding preset number of data uploads as follows: and , This indicates the actual number of data uploads at different times and the corresponding sequence number of the preset data upload count. =1, 2, 3, 4, ... , It is a positive integer;

[0074] according to and Obtain the data transmission error index The calculation formula is: ;

[0075] Data transmission time delay index includes:

[0076] When meteorological element data collected by the acquisition device at different times within time T is uploaded to the analysis system, the actual upload time stamp of the data is as follows: , The number representing the actual number of times the data was transmitted. =1, 2, 3, 4, ... , It is a positive integer;

[0077] Will Within the preset data upload time range Re-mark the time outside of time, and mark it as , Indicates the actual upload time Within the preset data upload time range The number of times outside of time, =1, 2, 3, 4, ... , For positive integers; calculate the data transmission time delay exponent. The calculation formula is: ;

[0078] The data transmission error index is calculated using the following formula: In the formula, This is the data transmission error index. and The preset weighting coefficients represent the data transmission error index and the data time delay index.

[0079] It should be noted that the actual upload time of meteorological element data collected by the acquisition devices at different times within time T to the analysis system can be obtained in real time by the monitoring system in the meteorological assessment system based on real-time measurement of meteorological elements. In addition, the corresponding preset data upload time range refers to the fastest and slowest upload time that each data can be effectively transmitted. The specific time depends on the actual situation, and no specific value is limited.

[0080] It should be noted that the data transmission error index refers to the difference between the actual data transmitted to the analysis system and the corresponding preset data, as well as the difference between the actual transmission time and the corresponding preset transmission time. The greater the difference, the higher the probability of errors in the collected meteorological data. Using the collected meteorological data for meteorological evaluation and analysis may lead to inaccurate evaluation results and prevent the timely provision of accurate weather forecasts and services. The reasons are as follows:

[0081] Data loss: If the actual number of data transmitted is less than the preset number, it may mean that data was lost during transmission. Data loss leads to incomplete data, affecting the underlying dataset for analysis and preventing a comprehensive reflection of meteorological conditions.

[0082] Data redundancy: If the actual number of data transmitted exceeds the preset number, it may indicate duplicate or erroneous data transmission, increasing data noise and affecting data accuracy. Data redundancy or duplicate transmission increases noise and errors in the dataset, reducing data quality.

[0083] Delayed transmission: If the actual upload time exceeds the preset upload time range, it indicates that there is a delay in data transmission. Delayed transmission leads to a decrease in real-time performance; the data cannot reflect the current weather conditions in a timely manner, affecting the timeliness of real-time weather monitoring and forecasting.

[0084] Synchronization issues: Data transmission delays can cause time synchronization problems between different sensors, affecting the consistency of data timing and the accuracy of analysis. Time discrepancies between different data sources can lead to disordered timing of data analysis results, affecting the accuracy of comprehensive analysis.

[0085] Therefore, the cumulative effect of numerical errors and time delays leads to increased data bias, resulting in inaccurate evaluation results based on biased data.

[0086] In one embodiment, when acquiring meteorological element data in real time, electromagnetic interference data information around the acquisition equipment is collected during the acquisition process, and the electromagnetic interference index is obtained based on the electromagnetic interference data information, including:

[0087] The logic for obtaining the electromagnetic interference index is as follows:

[0088] When acquiring meteorological element data, electromagnetic interference signals around the acquisition equipment at different times within time T during the acquisition process are recorded and tagged as follows: ,in, =1, 2, 3, 4, ... , It is a positive integer. Indicates the number of electromagnetic interference signals;

[0089] use Wavelet analysis of electromagnetic interference signals at each time step Perform continuous wavelet transform, through continuous wavelet transform ( The electromagnetic interference signal is decomposed in the time and frequency domains. The continuous wavelet transform is implemented through convolution, and its calculation formula is as follows: In the formula, It is the input signal. It is the selected wavelet basis function. It is a scaling parameter used to adjust the scale of the wavelet basis function; These are translation parameters used to adjust the position of the wavelet basis functions; The time coordinates of the signal, i.e., its position on the time axis;

[0090] For each scale Peaceful relocation The results calculated using wavelet transform are called wavelet coefficients;

[0091] Energy features are extracted from wavelet coefficients. Based on the calculated wavelet coefficients, energy features are further extracted by calculating the energy of the wavelet coefficients at each scale. Then, the energies at different scales are weighted and summed to obtain the comprehensive energy features. The calculation formula is as follows: In the formula, In scale The energy below, These are wavelet coefficients;

[0092] The electromagnetic interference index is calculated at each moment using the following expression: In the formula, Electromagnetic interference index;

[0093] Electromagnetic interference index at different times within time T Add them together to get the electromagnetic interference index. The formula for calculation is: In the formula, This represents the electromagnetic interference index.

[0094] It should be noted that when collecting meteorological element data, the electromagnetic interference signals around the acquisition equipment at different times during the acquisition process T can be obtained by high-precision electromagnetic sensors installed nearby.

[0095] It should be noted that electromagnetic interference affects the accuracy of meteorological data during the acquisition process in the following ways:

[0096] Signal interference: Meteorological data acquisition equipment typically includes sensors, data acquisition units, and data transmission modules. Electromagnetic interference can affect data transmission between sensors and acquisition units, leading to noise, errors, or even data loss in the acquired data.

[0097] Equipment performance degradation: Long-term exposure to strong electromagnetic interference may cause the performance of electronic components inside meteorological equipment to degrade, increase the failure rate of the equipment, and thus affect the accuracy and reliability of the data.

[0098] Data transmission errors: Electromagnetic interference can cause data transmission errors during wireless transmission of meteorological data, leading to incorrect received data. This effect is particularly pronounced in meteorological stations employing wireless communication technology.

[0099] Clock drift: Electromagnetic interference can also affect the device's clock system, leading to inaccurate data acquisition time. Time synchronization of meteorological data is crucial; clock drift can cause errors in data timestamps, thus affecting the timeliness and accuracy of the data.

[0100] Sensor error: Some meteorological sensors (such as radar and laser sensors) are very sensitive to the electromagnetic environment. Electromagnetic interference may directly affect the sensor readings, leading to deviations in the measurement results.

[0101] In summary, the greater the electromagnetic interference, the greater the impact on the accuracy of meteorological data acquisition equipment.

[0102] In one embodiment, the acquired equipment aging index, data transmission error index, and electromagnetic interference index are normalized to obtain data accuracy coefficients, including:

[0103]

[0104] In the formula, The accuracy coefficient of the data. , and These are the equipment aging index, data transmission error index, and electromagnetic interference index, respectively. These are preset proportional coefficients for the equipment aging index, data transmission error index, and electromagnetic interference index, respectively. The average score is greater than 0.

[0105] The data accuracy coefficient is compared with the preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison results to obtain the final meteorological element data, including:

[0106] The data accuracy coefficient is compared with the preset data accuracy coefficient threshold. If the data accuracy coefficient is less than the preset data accuracy coefficient threshold, it means that the accuracy of the collected meteorological element data is relatively high. At this time, the collected meteorological element data can be directly input into the preset meteorological assessment model to assess the weather.

[0107] If the data accuracy coefficient is not less than the preset data accuracy coefficient threshold, it indicates that the accuracy of the collected meteorological element data is low. In this case, it is necessary to adjust the collected meteorological element data according to the size of the data accuracy coefficient to obtain the final meteorological element data, and then input the final meteorological element data into the preset meteorological assessment model to assess the meteorology.

[0108] It should be noted that adjusting the collected meteorological data based on the accuracy coefficient can be done to varying degrees depending on the specific meteorological element. For example, for temperature data, if the accuracy coefficient slightly exceeds a threshold, interpolation methods (such as linear or polynomial interpolation) can be used to smooth the data. If the accuracy coefficient is high (significantly exceeding the threshold), it is necessary to refer to temperature data from nearby weather stations for correction, or use historical temperature data as a reference for adjustment. For humidity data, when the accuracy coefficient slightly exceeds a threshold, a weighted average method can be used, averaging the current humidity data with humidity data from nearby times. If the accuracy coefficient is high, more significant adjustments are needed, using calibration data from the humidity sensor or referring to data from nearby weather stations.

[0109] For wind speed and direction data, when the accuracy coefficient slightly exceeds a threshold, filtering methods (such as moving average filtering) can be used to smooth the data. If the accuracy coefficient is high, it is necessary to combine historical wind speed and direction data with data from nearby weather stations for correction. Additionally, wind field models can be used for simulation and adjustment to ensure data accuracy.

[0110] For precipitation data, if the accuracy coefficient slightly exceeds the threshold, it can be fine-tuned using the cumulative error correction method. If the accuracy coefficient is high, it is necessary to refer to precipitation data from surrounding meteorological stations and combine it with radar echo data for adjustment to ensure the accuracy of the precipitation data.

[0111] For air pressure data, if the accuracy coefficient slightly exceeds the threshold, time series analysis can be used to smooth the data. If the accuracy coefficient is high, it is necessary to refer to data from nearby weather stations and historical air pressure data for correction to ensure the accuracy of the air pressure data.

[0112] Therefore, the data of different meteorological elements can be adjusted to different degrees according to the magnitude of the data accuracy coefficient. The appropriate method and degree can be selected according to the specific situation to ensure that the data of each meteorological element reaches the expected accuracy, thereby providing reliable data support for meteorological assessment. The adjustment can be made by experts with reference and is not limited.

[0113] This invention also provides an electronic device, such as... Figure 2 As shown, it includes a processor 301, a communication interface 302, a memory 303, and a communication bus 304, wherein the processor 301, the communication interface 302, and the memory 303 communicate with each other through the communication bus 304.

[0114] Memory 303 is used to store computer programs;

[0115] When processor 301 executes a program stored in memory 303, it performs the following steps:

[0116] When acquiring meteorological element data in real time, the equipment aging data of the equipment is collected, and the equipment aging index is obtained based on the equipment aging data.

[0117] When acquiring meteorological element data in real time, the data transmission information during the transmission process is collected, and a data transmission error index is obtained based on the transmission information data.

[0118] When acquiring meteorological element data in real time, electromagnetic interference data information around the equipment is collected during the acquisition process, and the electromagnetic interference index is obtained based on the electromagnetic interference data information.

[0119] The obtained equipment aging index, data transmission error index and electromagnetic interference index are normalized to obtain the data accuracy coefficient.

[0120] The data accuracy coefficient is compared with the preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison results to obtain the final meteorological element data. The final meteorological element data is then input into the preset meteorological assessment model to evaluate the meteorology.

[0121] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0122] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0123] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0124] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0125] In another embodiment of the present invention, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described meteorological assessment methods based on real-time measurement of meteorological elements.

[0126] In another embodiment of the present invention, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the meteorological assessment methods based on real-time measurement of meteorological elements in the above embodiments.

[0127] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A meteorological assessment method based on real-time measurement of meteorological elements, characterized in that, Includes the following steps: When acquiring meteorological element data in real time, the equipment aging data of the equipment is collected, and the equipment aging index is obtained based on the equipment aging data. When acquiring meteorological element data in real time, the data transmission information during the transmission process is collected, and a data transmission error index is obtained based on the transmission information data. When acquiring meteorological element data in real time, electromagnetic interference data information around the equipment is collected during the acquisition process, and the electromagnetic interference index is obtained based on the electromagnetic interference data information. The obtained equipment aging index, data transmission error index and electromagnetic interference index are normalized to obtain the data accuracy coefficient. The data accuracy coefficient is compared with the preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison results to obtain the final meteorological element data. The final meteorological element data is then input into the preset meteorological assessment model to evaluate the meteorology.

2. The meteorological assessment method based on real-time measurement of meteorological elements according to claim 1, characterized in that, When acquiring meteorological element data in real time, the equipment aging data of the acquisition equipment is collected, and the equipment aging index is obtained based on the equipment aging data, including: Equipment aging data includes equipment response latency index and equipment maintenance index. The equipment response latency index is obtained as follows: Obtain the actual response time and the corresponding preset response time of the target acquisition device at different times within time T, and mark the actual response time and the corresponding preset response time as follows: and , This indicates the sequence number of the actual response time and the corresponding preset response time at different times. =1, 2, 3, 4, ... , It is a positive integer; The device response latency exponent is calculated using the following expression: In the formula, This indicates the device response latency index.

3. The meteorological assessment method based on real-time measurement of meteorological elements according to claim 2, characterized in that, The method for obtaining the equipment maintenance index is as follows: Obtain the time difference between the most recent maintenance time of the target acquisition device and the current time to obtain the maintenance time interval. ; Obtain the average maintenance time of the target acquisition device from the time of its use to the current time. and the maintenance interval Divide by mean repair time The equipment maintenance index is obtained by using the following formula: In the formula, Indicates the equipment maintenance index; The equipment aging index is obtained by weighted summation of the equipment response delay index and the equipment maintenance index. The formula for calculation is as follows: In the formula, This refers to the equipment aging index. and This represents the preset weighting coefficients for the equipment response delay index and the equipment maintenance index.

4. The meteorological assessment method based on real-time measurement of meteorological elements according to claim 1, characterized in that, When acquiring meteorological element data in real time, the data transmission information during the transmission process is considered, and a data transmission error index is derived based on this information, including: The data transmission error index includes a data transmission quantity error index and a data time delay index, wherein the data transmission error index includes: Obtain the actual number of meteorological element data collected by the acquisition device at different times within time T and upload them to the analysis system, along with the corresponding preset number of data uploads. Mark the actual number of data uploads and the corresponding preset number of data uploads as follows: and , This indicates the actual number of data uploads at different times and the corresponding sequence number of the preset data upload count. =1, 2, 3, 4, ... , It is a positive integer; according to and Obtain the data transmission error index The calculation formula is: .

5. A meteorological assessment method based on real-time measurement of meteorological elements according to claim 4, characterized in that, Data transmission time delay index includes: When meteorological element data collected by the acquisition device at different times within time T is uploaded to the analysis system, the actual upload time stamp of the data is as follows: , The number representing the actual number of times the data was transmitted. =1, 2, 3, 4, ... , It is a positive integer; Will Within the preset data upload time range Re-mark the time outside of time, and mark it as , Indicates the actual upload time Within the preset data upload time range The number of times outside of time, =1, 2, 3, 4, ... , For positive integers; calculate the data transmission time delay exponent. The calculation formula is: ; The data transmission error index is calculated using the following formula: In the formula, This is the data transmission error index. and The preset weighting coefficients represent the data transmission error index and the data time delay index.

6. The meteorological assessment method based on real-time measurement of meteorological elements according to claim 1, characterized in that, The logic for obtaining the electromagnetic interference index is as follows: When acquiring meteorological element data, electromagnetic interference signals around the acquisition equipment at different times within time T during the acquisition process are recorded and tagged as follows: ,in, =1, 2, 3, 4, ... , It is a positive integer. Indicates the number of electromagnetic interference signals; use Wavelet analysis of electromagnetic interference signals at each time step Continuous wavelet transform is performed to decompose the electromagnetic interference signal in both the time and frequency domains. The continuous wavelet transform is achieved through convolution, and its calculation formula is as follows: In the formula, It is the input signal. It is the selected wavelet basis function. It is a scaling parameter used to adjust the scale of the wavelet basis function; These are translation parameters used to adjust the position of the wavelet basis functions; The time coordinates of the signal, i.e., its position on the time axis; For each scale Peaceful relocation The results calculated using wavelet transform are called wavelet coefficients; Energy features are extracted from wavelet coefficients. Based on the calculated wavelet coefficients, energy features are further extracted by calculating the energy of the wavelet coefficients at each scale. Then, the energies at different scales are weighted and summed to obtain the comprehensive energy features. The calculation formula is as follows: In the formula, In scale The energy below, These are wavelet coefficients; The electromagnetic interference index is calculated at each moment using the following expression: In the formula, Electromagnetic interference index; Electromagnetic interference index at different times within time T Add them together to get the electromagnetic interference index. The formula for calculation is: In the formula, This represents the electromagnetic interference index.

7. A meteorological assessment method based on real-time measurement of meteorological elements according to claim 1, characterized in that, The obtained equipment aging index, data transmission error index, and electromagnetic interference index are normalized to obtain the data accuracy coefficient, which includes: In the formula, The accuracy coefficient of the data. , and These are the equipment aging index, data transmission error index, and electromagnetic interference index, respectively. These are preset proportional coefficients for the equipment aging index, data transmission error index, and electromagnetic interference index, respectively. The average score is greater than 0.

8. A meteorological assessment method based on real-time measurement of meteorological elements according to claim 1, characterized in that, The data accuracy coefficient is compared with the preset data accuracy coefficient threshold, and the collected meteorological element data is adjusted according to the comparison results to obtain the final meteorological element data, including: The data accuracy coefficient is compared with the preset data accuracy coefficient threshold. If the data accuracy coefficient is less than the preset data accuracy coefficient threshold, the collected meteorological element data is directly input into the preset meteorological assessment model to assess the weather. If the data accuracy coefficient is not less than the preset data accuracy coefficient threshold, it indicates that the accuracy of the collected meteorological element data is low. In this case, it is necessary to adjust the collected meteorological element data according to the size of the data accuracy coefficient to obtain the final meteorological element data, and then input the final meteorological element data into the preset meteorological assessment model to assess the meteorology.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-8.

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