Icing signal analysis method and system based on circulation index

Abstract

The present application relates to icing precursor signal forecasting technical field, especially in icing signal analysis method and system based on circulation index, integrated modern meteorological analysis tool and data processing technology, aims at improving the prediction accuracy and response efficiency of icing event, through the comprehensive use of the fifth generation global climate atmospheric reanalysis data provided by the European center for medium-range weather forecasts, combined with the actual icing record of the specific area transmission line, the analysis and calculation of key atmospheric circulation index, including Siberia high pressure intensity index, east Asia trough intensity index, etc., through these data support, can accurately track and predict the possibility and severity of icing occurrence, application of advance-lag correlation analysis method, further reveals the dynamic relationship between icing and atmospheric circulation index, provides scientific basis for formulating effective icing response measures.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of icing precursor signal forecasting, and in particular to an icing signal analysis method and system based on circulation indices. BACKGROUND

[0002] Researching quantitative analysis of large-scale circulation indices to determine icing precursor signals is an important topic in modern meteorological science, with significant practical application value and scientific significance. Icing phenomena pose a serious threat to power facilities, transportation, and infrastructure such as buildings, and can often lead to power outages, traffic accidents, and building damage in cold seasons. By studying large-scale circulation indices, we can gain a deeper understanding of the changes in atmospheric circulation patterns and their relationship with surface weather conditions, thereby identifying potential icing precursor signals. This quantitative analysis technique can provide early warning of potential icing risks, providing decision support for relevant departments to take preventive measures and reduce economic losses and casualties. In addition, using large-scale circulation indices to identify icing precursor signals can also enrich and improve weather forecasting models, improving the accuracy and reliability of weather forecasts.

[0003] In the background, large-scale circulation indices have been widely used to study the formation mechanisms of extreme weather events, and through in-depth analysis of these indices, key factors affecting icing phenomena can be captured. Therefore, research on this technology not only enhances scientific understanding of icing phenomena, but also provides effective early warning means in practical applications, with important theoretical research and practical application significance. SUMMARY

[0004] In view of the problems existing in the prior art, the present application is proposed.

[0005] Therefore, the technical problem to be solved by the present application is to overcome the shortcomings of the prior art and provide a technology for determining icing precursor signals based on quantitative analysis of large-scale circulation indices to accurately improve the accuracy of icing prediction and identification in plateau regions.

[0006] To solve the above technical problems, the present application provides the following technical solutions: an icing signal analysis method based on circulation indices, comprising: collecting and analyzing post-data, extracting key meteorological parameters as a data set; obtaining icing data records of power transmission lines in a specific region; classifying the processed data set; calculating atmospheric circulation indices; using lead-lag correlation analysis to determine the dynamic relationship between icing and atmospheric circulation indices.

[0007] As a preferred solution of the icing signal analysis method based on circulation indices, the key meteorological parameters include potential, relative humidity, specific humidity, temperature, wind u component, wind v component, and pressure level data set of vertical velocity.

[0008] As a preferred scheme of the icing signal analysis method based on the atmospheric circulation index, the icing data records of the transmission line in a specific region are collected from typical transmission line towers in a mountainous area in a specific province, and the geographical coordinates range from 103.33° E to 104.34° E and from 25.74° N to 26.01° N.

[0009] As a preferred scheme of the icing signal analysis method based on the atmospheric circulation index, the classification of the processed data set includes selecting data in a specific time period as a training set and a test set.

[0010] As a preferred scheme of the icing signal analysis method based on the atmospheric circulation index, the atmospheric circulation index includes the Siberian high pressure intensity index, the East Asian trough intensity index, the subtropical high ridge point, the subtropical high area index, and the 850 hPa subtropical high index.

[0011] As a preferred scheme of the icing signal analysis method based on the atmospheric circulation index, the lead-lag correlation analysis includes a statistical method for analyzing the dynamic relationship between two time series data, which determines the lead and lag relationship by calculating the correlation coefficient of one time series with respect to another time series at different time lags. Specifically, it includes selecting the time series data to be analyzed, calculating the correlation coefficient at the lag period, and determining the lag period. If the lag period is positive, it indicates that one sequence leads the other sequence. If it is negative, it indicates that one sequence lags behind the other sequence.

[0012] As a preferred scheme of the icing signal analysis method based on the atmospheric circulation index, the dynamic relationship between the icing and the atmospheric circulation index includes studying the dynamic interaction between the icing on the transmission line tower and the index in the atmospheric environment. The dynamic relationship includes the change of water state with meteorological conditions, as well as the influence on the thickness and density of the icing.

[0013] Another object of the present application is to provide an icing signal analysis system based on the circulation index, aiming to improve the accuracy and efficiency of icing prediction. By integrating advanced data collection, processing and analysis techniques, the system can effectively collect key meteorological parameters and icing data records of specific regional transmission lines. By classifying these data and combining the calculation of atmospheric circulation index, the system can make more accurate assessment of icing risk. In addition, the system uses the lead-lag correlation analysis method to explore the complex dynamic relationship between icing and atmospheric circulation index, so as to predict and identify potential icing events. The design of the system includes several key modules: data collection and analysis module, icing data acquisition module, data processing and classification module, circulation index calculation module and dynamic relationship analysis module, each module focuses on performing specific functions, and works together to provide a comprehensive solution. Through this comprehensive analysis, the system not only improves the accuracy of icing prediction, but also provides a powerful decision support tool for the power industry and related departments, helping to reduce economic losses and safety risks under extreme weather conditions.

[0014] To solve the above technical problems, the present application provides the following technical solutions: an icing signal analysis system based on the circulation index, comprising: a data collection and analysis module, an icing data acquisition module, a data processing and classification module, a circulation index calculation module and a dynamic relationship analysis module;

[0015] The data collection and analysis module collects and analyzes the data, extracts key meteorological parameters as a data set;

[0016] The icing data acquisition module acquires icing data records of specific regional transmission lines;

[0017] The data processing and classification module classifies the processed data set;

[0018] The circulation index calculation module calculates the atmospheric circulation index;

[0019] The dynamic relationship analysis module uses lead-lag correlation analysis to determine the dynamic relationship between icing and atmospheric circulation index.

[0020] A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement the steps of the icing signal analysis method based on the circulation index as described above.

[0021] A computer readable storage medium having a computer program stored thereon, characterized in that the computer program is executed by a processor to implement the steps of the icing signal analysis method based on the circulation index as described above.

[0022] The beneficial effects of the present application: by obtaining the actual European Center for Medium-Range Weather Forecasts (ECMWF) fifth generation global climate atmospheric reanalysis (ERA5) data and power transmission line tower icing data in Qujing City, Yunnan Province, and through a series of data processing and lead-lag correlation analysis, the accuracy of the icing prediction recognition in the plateau area can be more accurately predicted, which provides scientific and technological support for icing prediction, and has important scientific significance and application value. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0024] Figure 1 The flow chart of the fan icing inversion and prediction technology of the icing signal analysis method based on the circulation index provided by an embodiment of the present application.

[0025] Figure 2 The probability distribution graph of the maximum icing of the icing signal analysis method based on the circulation index provided by an embodiment of the present application.

[0026] Figure 3 The standardization schematic diagram of the selected daily average value of atmospheric circulation index in the icing process of the icing signal analysis method based on the circulation index provided by an embodiment of the present application.

[0027] Figure 4 The average daily variation and the lead and lag correlation coefficient of the maximum daily coverage thickness of each circulation index of the icing signal analysis method based on the circulation index provided by an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0029] Embodiment 1, refer to Figures 1-2 For an embodiment of the present application, the embodiment provides an icing signal analysis method based on circulation index, comprising:

[0030] S1: Collect and analyze the subsequent data, and extract the key meteorological parameters as a data set.

[0031] It should be noted that, such as Figure 1 As shown in S101, the key meteorological parameters include geopotential, relative humidity, specific humidity, temperature, wind u component, wind v component, and pressure level dataset of vertical velocity.

[0032] Furthermore, data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Generation 5 Global Climate-Atmosphere Reanalysis (ERA5) from January 5 to January 14, 2021 were collected;

[0033] Furthermore, by acquiring actual European Centre for Medium-Range Weather Forecasts (ECMWF) Generation 5 Global Climate-Atmosphere Reanalysis (ERA5) data and transmission line tower icing data from Qujing City, Yunnan Province, and through a series of data processing and lead-lag correlation analysis, the accuracy of icing prediction and identification in plateau areas can be improved relatively accurately, providing scientific and technological support for icing occurrence forecasting, which has significant scientific significance and application value. A single-layer dataset including mean sea level pressure was utilized, with pressure levels ranging from 1000 hPa to 400 hPa, totaling 18 layers. These datasets cover the range of 40-160°E and 10-70°N, with a spatial resolution of 0.25°×0.25° and a temporal resolution of 1 hour.

[0034] S2: Obtain icing data records for transmission lines in a specific area.

[0035] It should be noted that, such as Figure 1 As shown in S102, obtaining icing data records for transmission lines in a specific region includes collecting icing data of typical transmission line towers in mountainous areas of a specific province, with geographical coordinates ranging from 103.33°E to 104.34°E and 25.74°N to 26.01°N.

[0036] Furthermore, data on icing on typical transmission line towers located in the mountainous areas of Fuyuan, Zhanyi, and Huize in eastern Qujing City, Yunnan Province, were collected.

[0037] Furthermore, data on icing on typical transmission line towers in the mountainous areas of Fuyuan, Zhanyi, and Huize in eastern Qujing City, Yunnan Province, were collected. These towers have experienced severe and rapid icing over the years; their geographical coordinates range from approximately 103.33°E to 104.34°E and 25.74°N to 26.01°N. From January 7th to 13th, 2021, Qujing experienced a significant temperature drop due to the influence of a southern trough and cold air, causing continuous icing on the ultra-high voltage transmission lines in the mountainous areas of Fuyuan, Zhanyi, and Huize. The severely iced areas are mainly concentrated on the Kunliulong line, and the probability distribution of maximum icing is shown below. Figure 2 As shown in the figure, the horizontal axis Maximum Ice Thickness represents the maximum ice thickness, and the vertical axis Probability represents the probability.

[0038] S3: Classify the processed dataset.

[0039] It should be noted that, as shown in S103, classifying the processed dataset includes selecting data of a specific time period as a training set and a test set. Figure 1

[0040] Further, the processed dataset is classified, and data from January 21, 2024 16:30 to February 1, 2024 23:50 is selected as the training set, and data from February 2, 2024 00:10 to February 10, 2024 20:00 is selected as the test set.

[0041] Embodiment 2, referring to Figure 1 、 Figures 3-4 , for an embodiment of the present application, the embodiment provides an icing signal analysis method based on the atmospheric circulation index, comprising:

[0042] S4: Calculate the atmospheric circulation index.

[0043] It should be noted that, as shown in S104, the atmospheric circulation index includes the Siberian high pressure intensity index, the East Asian trough intensity index, the subtropical high ridge point, the subtropical high pressure area index, and the 850 hPa subtropical high pressure index. Figure 1

[0044] Further, the Siberian high pressure intensity index (Siberian high pressure system), the East Asian trough intensity index, the subtropical high ridge point, the subtropical high pressure area (intensity) index, and the 850 hPa subtropical high pressure index (50-110°E) are calculated.

[0045] Further, the Siberian high intensity index is calculated as the normalized sea level pressure in the region of 80-120°E and 40-65°N; the East Asian trough intensity index is calculated according to the normalized 500 hPa height field in the region of 110-145°E and 25-45°N; the subtropical high pressure index is calculated in the range of 90-160°E north of 10°N; the subtropical area index is defined as the number of grid points in the region with 500 hPa potential height greater than 5880 gpm; the intensity index is the cumulative difference between the grid points with potential height greater than 5880 gpm and 5870 gpm; the subtropical ridge point is determined as the westernmost longitude of the potential height 5880 gpm contour; and the 850 hPa subtropical high pressure index represents the average deviation of 850 hPa potential height in the range of 50-110°E and 10-30°N.

[0046] S5: Determine the dynamic relationship between icing and atmospheric circulation index using lead-lag correlation analysis.

[0047] It should be noted that, as shown in S104, the atmospheric circulation index includes the Siberian high pressure intensity index, the East Asian trough intensity index, the subtropical high ridge point, the subtropical high pressure area index, and the 850 hPa subtropical high pressure index. Figure 1 ​​As shown in S105, the lead-lag correlation analysis includes a statistical method for analyzing the dynamic relationship between two time series data, and determines the lead and lag relationship by calculating the correlation coefficient of one time series relative to another time series at different time lags; specifically, it includes selecting the time series data to be analyzed, calculating the correlation coefficient at the lag period, and determining the lag period; if the lag period is positive, it indicates that one sequence leads another sequence; if it is negative, it indicates that one sequence lags behind another sequence.

[0048] Further, the dynamic relationship between icing and atmospheric circulation indices includes studying the dynamic interaction between icing on the tower of the power transmission line and the indices in the atmospheric environment; the dynamic relationship includes the change of the state of water with the meteorological conditions, and the influence on the thickness and density of the icing.

[0049] Specifically, the relationship between the Siberian high, the East Asian trough, the 50-110 °E subtropical high and the icing degree is analyzed by using the lead-lag correlation analysis.

[0050] Further, the relationship between the Siberian high, the East Asian trough, the 50-110 °E subtropical high and the icing degree is analyzed by using the lead-lag correlation analysis; the results show that: when the East Asian trough strength and the subtropical high area lead by 1d, their correlation coefficients with the maximum icing thickness are the lowest, which are-0.86 and-0.83 respectively; when the 850hPa subtropical high strength index leads by 2d, the correlation is the lowest, and the correlation coefficient is-0.82; on the contrary, the correlation between the subtropical high, the Siberian high and the subtropical high ridge point and the icing thickness is the highest, and the correlation coefficients are 0.46, 0.92 and 0.86 respectively; in summary, each index can provide a relatively clear precursor signal for the daily maximum icing thickness when it leads by 0-2d.

[0051] Specifically, the lead-lag correlation analysis method is a statistical method for analyzing the dynamic relationship between two time series data; by calculating the correlation coefficient of one time series relative to another time series at different time lags, the lead and lag relationship between them can be determined; the specific process includes selecting the time series data to be analyzed, calculating the correlation coefficient at each possible lag period, and determining the lag period corresponding to the maximum correlation coefficient; if the lag period is positive, it indicates that one sequence leads another sequence; if it is negative, it indicates that one sequence lags behind another sequence.

[0052] This method is widely used in economics, meteorology and engineering, for example, in economics to analyze the relationship between consumption and income, unemployment and inflation, etc. in meteorology to analyze the relationship between meteorological variables such as temperature and precipitation, and in engineering to optimize system design and control strategies. Its advantages are that it can reveal the dynamic relationship between variables and help prediction and decision-making, but it also has limitations, such as only suitable for linear relationships and dependent on the stationarity of time series. Therefore, in practical applications, appropriate data preprocessing is required.

[0053] Specifically as shown in Figure 3 、 Figure 4 :

[0054] Figure 3 The standardization of the daily average value of the selected atmospheric circulation index during the icing process (the time point on the horizontal axis represents today 08:00 to next day 07:00); where the vertical coordinate Index represents the index; the horizontal coordinate Month / Day represents the month / day; East Asia trough intensity index represents the East Asia trough intensity index; 850 hPa subtropical high index represents the 850 hPa subtropical high index; Subtropical high area represents the subtropical high pressure area; Subtropical high intensity represents the subtropical high pressure intensity; Siberian High Pressure System represents the Siberian High Pressure System; Subtropical ridge point represents the subtropical ridge point.

[0055] Figure 4 The average daily variation of each circulation index and the leading and lagging correlation coefficient of the maximum daily coverage thickness; negative (positive) horizontal coordinate represents the leading (lagging) day, vertical coordinate represents the correlation coefficient; negative (positive) delay on the horizontal axis represents the leading (lagging) correlation between the daily average circulation index and the daily maximum coverage thickness; where (a) East Asia trough intensity index represents the East Asia trough intensity index; (b) 850 hPa subtropical high index represents the 850 hPa subtropical high index; (c) subtropical high area represents the subtropical high pressure area; (d) subtropical high intensity represents the subtropical high pressure intensity; (e) Siberian High Pressure system represents the Siberian High Pressure system; (f) subtropical ridge point represents the subtropical ridge point.

[0056] In summary, the method provided by the embodiment of the present application can obtain the actual ECMWF (European Centre for Medium-Range Weather Forecasts) ERA5 (fifth generation of the ECMWF global climate reanalysis) data and the tower icing data of the power transmission line in Qujing City, Yunnan Province, and through a series of data processing and lead-lag correlation analysis, the accuracy of the icing prediction and identification in the plateau area can be relatively accurately obtained, which provides scientific and technological support for the icing occurrence prediction and has important scientific significance and application value.

[0057] The above is a schematic scheme of the icing signal analysis method based on the circulation index. It should be noted that the technical scheme of the icing signal analysis system based on the circulation index belongs to the same concept as the technical scheme of the icing signal analysis method based on the circulation index described above. The technical scheme of the icing signal analysis system based on the circulation index in the embodiment is not described in detail, and the description of the technical scheme of the icing signal analysis method based on the circulation index can be referred to.

[0058] In embodiment 3, a system for analyzing icing signals based on circulation indices is provided, which includes a data collection and analysis module, an icing data acquisition module, a data processing and classification module, a circulation index calculation module, and a dynamic relationship analysis module.

[0059] The data collection and analysis module collects and analyzes subsequent data, extracts key meteorological parameters as a data set, and classifies the processed data set.

[0060] The icing data acquisition module acquires icing data records of the power transmission line in a specific area.

[0061] The data processing and classification module classifies the processed data set.

[0062] The circulation index calculation module calculates the atmospheric circulation index.

[0063] The dynamic relationship analysis module determines the dynamic relationship between icing and atmospheric circulation index by using lead-lag correlation analysis.

[0064] The embodiment also provides a computing device suitable for the icing signal analysis method based on the circulation index, which includes:

[0065] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to realize the icing signal analysis method based on the circulation index proposed in the above embodiment.

[0066] The embodiment also provides a storage medium having a computer program stored thereon, and the program is executed by the processor to realize the icing signal analysis method based on the circulation index proposed in the above embodiment.

[0067] The storage medium proposed in this embodiment belongs to the same inventive concept as the icing signal analysis method based on the ring current index proposed in the above embodiment, and the technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0068] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or the part of the present application that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0069] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered a list of executable instructions for implementing logical functions, and can be specifically embodied in any computer-readable medium for use by an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, apparatus or device and execute the instructions, or in conjunction with these instructions execution systems, apparatus or devices. For the purpose of this specification, the "computer-readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by an instruction execution system, apparatus or device or in conjunction with these instruction execution systems, apparatus or devices.

[0070] It should be understood that parts of the present application can be realized in hardware, software, firmware or a combination thereof. In the above embodiments, a plurality of steps or methods can be realized by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if realized in hardware, and as in another embodiment, it can be realized by any one or a combination of the following technologies known in the art: discrete logic circuit with logic gate circuit for implementing logical functions on data signals, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA), etc.

[0071] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced, without departing from the spirit and scope of the technical solutions of the present application, which should be covered in the scope of the claims of the present application.

Claims

1. A method for ice accretion signal analysis based on a circulation index, characterized in that: The method comprises the following steps: Collecting and analyzing climate data to extract key meteorological parameters as a dataset; The key meteorological parameters include potential temperature, relative humidity, specific humidity, temperature, wind u component, wind v component, and pressure level data set of vertical velocity; Obtaining icing data records of power transmission lines in a specific region; Classifying the processed dataset into training set and test set; Calculating atmospheric circulation index; Using lead-lag correlation analysis to determine the lead and lag relationship by calculating the correlation coefficient of one time series to another time series at different time lags, and determining the dynamic relationship between icing and atmospheric circulation index, including the change of water state with meteorological conditions, and the thickness and density of the ice.

2. The icing signal analysis method based on the circulation index according to claim 1, characterized in that: The step of obtaining icing data records of power transmission lines in a specific region includes collecting typical tower icing data of power transmission lines in mountainous areas of a specific province, with geographical coordinates ranging from 103.33° E to 104.34° E and 25.74° N to 26.01° N.

3. The icing signal analysis method based on the circulation index according to claim 2, characterized in that: The step of classifying the processed dataset includes selecting data of a specific time period as the training set and the test set.

4. The icing signal analysis method based on the circulation index according to claim 3, characterized in that: The atmospheric circulation index includes Siberian high pressure intensity index, East Asian trough intensity index, subtropical high ridge point, subtropical high area index, and 850 hPa subtropical high index.

5. The icing signal analysis method based on the circulation index according to claim 4, characterized in that: The lead-lag correlation analysis includes a statistical method for analyzing the dynamic relationship between two time series data, which determines the lead and lag relationship by calculating the correlation coefficient of one time series to another time series at different time lags; specifically, it includes selecting the time series data to be analyzed, calculating the correlation coefficient of the lag period, and determining the lag period; if the lag period is positive, it means that one sequence leads the other; if it is negative, it means that one sequence lags behind the other.

6. The icing signal analysis method based on the circulation index according to claim 5, characterized in that: The dynamic relationship between icing and atmospheric circulation index includes studying the dynamic interaction between the icing on the power transmission line tower and the index in the atmospheric environment; the dynamic relationship includes the change of water state with meteorological conditions, and the thickness and density of the ice.

7. A system for ice accretion signal analysis based on the circulation index according to any one of claims 1 to 6, characterized in that: The method comprises the following steps: A data collection and analysis module, an icing data acquisition module, a data processing and classification module, a circulation index calculation module, and a dynamic relationship analysis module; The data collection and analysis module collects and analyzes climate data to extract key meteorological parameters as a dataset; The icing data acquisition module obtains icing data records of power transmission lines in a specific region; The data processing and classification module classifies the processed dataset; The circulation index calculation module calculates the atmospheric circulation index; The dynamic relationship analysis module uses lead-lag correlation analysis to determine the dynamic relationship between icing and atmospheric circulation index.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to realize the steps of the icing signal analysis method based on circulation index according to any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the icing signal analysis method based on circulation index according to any one of claims 1 to 6.

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