A design method for measuring cloud droplet spectra and types of high-altitude power transmission towers

Abstract

This invention relates to the field of power technology, specifically to a design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers. The method includes: acquiring raw data from a joint CloudSat and CALIPSO observation data source as the basic data source; monitoring and recording the meteorological conditions in the area where the high-altitude power transmission tower is located in real time to acquire tower data; processing the data acquired from CloudSat and CALIPSO, as well as the data monitored by deployed meteorological stations and meteorological monitoring devices, to remove outliers and determine usable data; integrating and analyzing the processed data, storing the data in a database, and visualizing the data. This invention, employing a power transmission tower cloud and fog droplet spectrum and type measurement platform based on joint CloudSat and CALIPSO observation data, enables power transmission towers to more accurately monitor and assess the impact of clouds and fog on their operation, improving safety and reliability. It also solves the problems of limited data acquisition methods and the inability to guarantee the accuracy of acquired data in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of power technology, specifically to a design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers. Background Technology

[0002] Power supply in high-altitude areas typically relies on long-distance transmission lines and power towers. Cloudy and foggy weather can negatively impact power transmission lines, such as increasing line losses and resistance, and causing arcing. By monitoring cloud droplet spectra and cloud types, we can better understand the impact of clouds and fog on the power system, providing a reference for power transmission and energy management, and optimizing the operation and efficiency of the power system.

[0003] However, in current technology, high-altitude areas often experience foggy weather, especially in mountainous and plateau regions. The presence of fog can affect the operation and maintenance of power transmission towers, therefore, it is necessary to monitor fog around power transmission towers. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that the present invention aims to solve the problem that the existing technology has a single data acquisition method, which cannot guarantee the accuracy of the acquired data.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: Raw data is obtained from the joint observation data sources of CloudSat and CALIPSO as the basic data source; meteorological data of the area where high-altitude power transmission towers are located is monitored and recorded in real time to obtain tower data; the data obtained from CloudSat and CALIPSO, along with the data monitored by the deployed meteorological stations and meteorological monitoring devices, are processed to remove outliers and determine usable data; the processed data is integrated and analyzed, stored in a database, and visualized.

[0007] As a preferred embodiment of the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers according to the present invention, the basic data source includes: acquiring raw data from a joint observation data source of CloudSat and CALIPSO, and using the raw data of CloudSat and CALIPSO as the basic data source to acquire data on the vertical profile, height distribution, optical thickness, cloud top height, and cloud base height of the cloud layer; acquiring data on the types of stratiform clouds, cumulonimbus clouds, and cirrus clouds in the cloud layer; and acquiring atmospheric parameter data such as temperature and humidity. Acquiring tower data includes deploying meteorological stations and meteorological monitoring devices to record and monitor the meteorological conditions in the area where the high-altitude power transmission tower is located in real time, monitoring the regional meteorological conditions, and measuring the cloud and fog droplet spectrum. The cloud and fog droplet spectrum includes collecting cloud and fog particle size data and cloud droplet nuclei number in the cloud and fog droplet spectrum.

[0008] As a preferred embodiment of the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers described in this invention, the data acquired by CloudSat and CALIPSO include: processing CloudSat data, analyzing cloud-related parameters from the CloudSat data to obtain vertical contour information and geophysical characteristics of the clouds; and processing CALIPSO data to extract cloud and fog-related parameters, including optical thickness, cloud top height, and cloud base height. The specific data processing steps are as follows:

[0009] Receive raw lidar data from the CALIPSO satellite, wherein the lidar data is the lidar echo signal;

[0010] By using the echo signals of lidar, clouds and aerosols in the atmosphere are inverted to determine the existence of clouds, the height distribution of clouds, and the optical properties of clouds.

[0011] The cloud height H is determined by analyzing the time delay of the reflected signal based on the detection results. cloud :

[0012] H cloud = (c*Δt) / 2

[0013] Where c is the speed of light, and Δt is the time delay of the echo signal;

[0014] The extracted cloud-related parameters include cloud optical thickness, cloud top height, and cloud bottom height.

[0015] As a preferred embodiment of the design method for cloud and fog droplet spectrum and type measurement platform of high-altitude power towers described in this invention, the removal of outliers includes comparing the same and similar parameters of data obtained by CloudSat and CALIPSO with the data obtained by the tower meteorological detection system, and then performing independent data verification.

[0016] The specific steps for independent data validation are as follows:

[0017] Data obtained from different data sources has the same or similar parameters;

[0018] Data acquired from CloudSat and CALIPSO were compared with data acquired from the tower meteorological monitoring system to detect outlier data points. The standard deviation method was used to identify outlier data points.

[0019]

[0020] Where N is the number of data samples, μ is the sample mean, and the z-score method is used to analyze the degree of deviation of outlier data points:

[0021]

[0022] Where z represents the degree of deviation, and σ represents the standard deviation; if the absolute value of z is greater than a predetermined threshold, then the data point x i It is considered an outlier;

[0023] When validating temperature data, a deviation threshold of twice its own standard deviation is used. Data points with an absolute deviation z greater than twice the standard deviation are considered outliers. When validating humidity data, a deviation threshold of one standard deviation is used. Cloud cover data, cloud droplet nuclei, and cloud droplet nuclei are all considered outliers. When validating cloud droplet nuclei, a deviation threshold of three standard deviations is used. When data anomalies are detected, data points are corrected, and an independent data validation report is created, including comparison results, identification of outlier data points, and corrective measures.

[0024] As a preferred embodiment of the design method for measuring cloud and fog droplet spectra and types of high-altitude power transmission towers according to the present invention, the removal of outliers further includes: evaluating the data acquired by CloudSat and CALIPSO and the data acquired by the tower meteorological monitoring system by calculating the confidence intervals of the data; the data uncertainty estimation step specifically includes: calculating the confidence intervals of different types of meteorological data acquired by CloudSat and CALIPSO and the data acquired by the tower meteorological monitoring system; analyzing the width and distribution of the confidence intervals to determine the uncertainty level of the evaluated data and obtain the data credibility; determining the data credibility based on the uncertainty level of the data; and for the evaluated outlier data, experts conduct an evaluation based on experience to determine the final data.

[0025] As a preferred embodiment of the design method for measuring cloud and fog droplet spectrum and type of high-altitude power transmission towers according to the present invention, the integrated analysis of the processed data includes fitting and integrating the processed tower meteorological data with CloudSat and CALIPSO data to establish a comprehensive tower cloud and fog environment database.

[0026] Based on data mining and machine learning techniques, the data in the database is analyzed and statistically analyzed to determine the distribution characteristics of cloud droplet spectra and cloud types near high-altitude power transmission towers;

[0027] The distribution characteristics include: droplet spectrum distribution characteristics, which are determined by data mining to identify droplet spectrum distribution characteristics in different time periods and seasons near high-altitude power transmission towers, including the size, number, and distribution density of water droplets and ice crystals; cloud and fog type distribution, which determines the distribution of various cloud and fog types under different conditions near high-altitude power transmission towers; and spatiotemporal distribution characteristics, which determine the distribution in different seasons and weather conditions, as well as the changes in cloud and fog within a day.

[0028] The fitting integration includes constructing a Log-Normal distribution function to describe the cloud droplet spectrum near the power tower:

[0029]

[0030] Where N(D) is the number of cloud droplets obtained after fitting, N0 is the nucleus concentration in the cloud droplet spectrum, and D m N is the median cloud particle size in the cloud droplet spectrum. σ It is the logarithmic standard deviation of the number of cloud droplets.

[0031] As a preferred embodiment of the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers described in this invention, the visualization includes establishing a visualization platform based on geographic information GIS technology to visualize the specific analytical features of cloud and fog distribution, droplet spectrum and type, and generating corresponding feature maps.

[0032] Another objective of this invention is to provide a system for designing a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers. This system can accurately measure the cloud and fog droplet spectrum and type around high-altitude power transmission towers by constructing a cloud and fog droplet spectrum and cloud and fog type measurement system.

[0033] As a preferred embodiment of the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers according to the present invention, the system includes: a data acquisition module, a data processing module, and an analysis and display module; the data acquisition module obtains raw data from the joint observation data source of CloudSat and CALIPSO as the basic data source, monitors and records the meteorological conditions in the area where the high-altitude power transmission tower is located in real time, and acquires tower data; the data processing module processes the data obtained from CloudSat and CALIPSO and the data monitored by the deployed meteorological stations and meteorological monitoring devices, respectively, removes outliers, and determines usable data; the analysis and display module performs integrated analysis on the processed data, stores the data in a database, and provides a visual display.

[0034] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers.

[0035] The present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the aforementioned design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers.

[0036] The beneficial effects of this invention are as follows: Compared with cloud and fog type measurement platforms, the cloud and fog droplet spectrum of power transmission towers using CloudSat and CALIPSO joint observation data has more detailed vertical distribution information, multi-parameter comprehensive analysis capabilities, and spatiotemporal consistency of data. This enables power transmission towers to more accurately monitor and evaluate the impact of clouds and fog on their operation, improve safety and reliability, and solve the problem of the single data acquisition method in the existing technology, which cannot guarantee the accuracy of the acquired data. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0038] Figure 1 This is a flowchart illustrating the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers provided by the present invention. Detailed Implementation

[0039] To make the above-mentioned objects, features, and advantages of the present invention more readily understood, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0040] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0041] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0042] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0043] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0044] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0045] Example 1

[0046] Reference Figure 1This is the first embodiment of the present invention, which provides a design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers.

[0047] S1: Collect meteorological data from meteorological satellites.

[0048] The basic data sources include raw data obtained from the joint observation data source of CloudSat and CALIPSO, using the raw data of CloudSat and CALIPSO as the basic data source to obtain data on the vertical profile, height distribution, optical thickness, cloud top height, and cloud bottom height of the cloud layer, cloud type data of stratiform clouds, cumulonimbus clouds, and cirrus clouds in the cloud layer, and atmospheric parameter data such as temperature and humidity.

[0049] S2: Collect meteorological data from the iron tower.

[0050] Meteorological stations and observation devices are set up around high-altitude power transmission towers to record and monitor the meteorological conditions in the area where the towers are located in real time, and to monitor the regional meteorological conditions and measure cloud and fog droplet spectra.

[0051] The meteorological observation equipment includes temperature sensors, humidity sensors, air pressure sensors, wind speed and direction instruments, as well as a laser particle spectrometer and a multi-angle light scattering instrument.

[0052] The cloud droplet spectrum includes data on cloud particle size and droplet nuclei collected from the cloud droplet spectrum around the power tower.

[0053] S3: Process the data.

[0054] S301: CloudSat Data Processing.

[0055] Based on CLOUDSAT-2B-GEOPROF, cloud-related parameters of CloudSat data are analyzed to obtain the vertical contour information and spatial physical characteristics of the cloud.

[0056] S302: CALIPSO data processing.

[0057] Based on the CALIOPLidarLevel2 data processing algorithm, cloud-related parameters are extracted, including cloud optical thickness, cloud top height, and cloud base height. The specific data processing steps include:

[0058] The system receives raw lidar data from the CALIPSO satellite, which is the lidar echo signal.

[0059] By using the echo signals of lidar, clouds and aerosols in the atmosphere can be inverted to determine the existence of clouds, their height distribution, and their optical properties.

[0060] The cloud height H is determined by analyzing the time delay of the reflected signal based on the detection results. cloud :

[0061] H cloud = (c*Δt) / 2

[0062] Where c is the speed of light and Δt is the time delay of the echo signal.

[0063] The extracted cloud-related parameters include cloud optical thickness, cloud top height, and cloud bottom height.

[0064] S303: Perform data quality control.

[0065] Specifically, the data obtained from CloudSat and CALIPSO are compared with the data obtained from the tower meteorological monitoring system for the same or similar parameters, and then independent data verification is performed.

[0066] The specific steps for independent data validation are as follows:

[0067] Data obtained from different data sources has the same or similar parameters;

[0068] Data acquired from CloudSat and CALIPSO were compared with data acquired from the tower meteorological monitoring system to detect outlier data points. The standard deviation method was used to identify outlier data points.

[0069]

[0070] Where N is the number of data samples, μ is the sample mean, and the z-score method is used to analyze the degree of deviation of outlier data points:

[0071]

[0072] Where z represents the degree of deviation, and σ represents the standard deviation; if the absolute value of z is greater than a predetermined threshold, then the data point x i It is considered an outlier.

[0073] When validating temperature data, a deviation threshold of twice the standard deviation of the data point is used. When the absolute value of the deviation z of the data point is greater than twice the standard deviation, it is considered an outlier.

[0074] When validating humidity data, a deviation threshold of one standard deviation is used. When the absolute value of the deviation z of a data point is greater than one standard deviation, it is considered an outlier.

[0075] When validating cloud data, a deviation threshold of one standard deviation is used. When the absolute value of the deviation z of a data point is greater than one standard deviation, it is considered an outlier.

[0076] When verifying the number of cloud droplets, a deviation threshold of three times the standard deviation is used. When the absolute value of the deviation z of a data point is greater than three times the standard deviation, it is considered an outlier.

[0077] When data anomalies are detected, correct the data points and create an independent data verification report, including comparison results, identification of anomaly data points, and corrective measures.

[0078] Furthermore, the removal of outliers also includes evaluating the data acquired by CloudSat and CALIPSO and the data acquired by the tower meteorological monitoring system by calculating the confidence interval of the data.

[0079] The specific steps for estimating data uncertainty include:

[0080] Calculate the confidence intervals of different types of meteorological data acquired by CloudSat and CALIPSO, as well as the data acquired by the tower meteorological monitoring system;

[0081] Analyze the width and distribution of confidence intervals to determine the level of uncertainty in the assessment data and thus the data confidence level.

[0082] The reliability of the data is determined based on the level of uncertainty. For the evaluation of anomalous data, experts use their experience to determine the final data.

[0083] S4: Determine distribution characteristics and perform integrated analysis.

[0084] Specifically, the integrated analysis of the processed data includes fitting and integrating the processed tower meteorological data with CloudSat and CALIPSO data to establish a comprehensive tower cloud and fog environment database.

[0085] Based on data mining and machine learning techniques, the data in the database is analyzed and statistically analyzed to determine the distribution characteristics of cloud droplet spectra and cloud types near high-altitude power transmission towers.

[0086] The distribution characteristics include: droplet spectrum distribution characteristics, which are determined by data mining to identify the droplet spectrum distribution characteristics in different time periods and seasons near high-altitude power transmission towers, including the size, number, and distribution density of water droplets and ice crystals; cloud and fog type distribution, which determines the distribution of various cloud and fog types under different conditions near high-altitude power transmission towers; and spatiotemporal distribution characteristics, which determine the distribution in different seasons and weather conditions, as well as the changes in clouds and fog within a day.

[0087] Further fitting integration includes constructing a Log-Normal distribution function to describe the cloud droplet spectrum near the power tower:

[0088]

[0089] Where N(D) is the number of cloud droplets obtained after fitting, N0 is the nucleus concentration in the cloud droplet spectrum, and D m N is the median cloud particle size in the cloud droplet spectrum. σ It is the logarithmic standard deviation of the number of cloud droplets.

[0090] S5: Visual presentation.

[0091] Specifically, the visualization includes establishing a visualization platform based on Geographic Information System (GIS) technology to visualize the specific analytical features of cloud and fog distribution, droplet spectrum, and type, and to generate corresponding feature maps.

[0092] The feature maps include: a map-style visualization; a droplet spectral curve showing the particle size distribution of water droplets and ice crystals in clouds and fog; a cloud and fog type classification map showing the distribution of different types of clouds and fog near high-altitude power transmission towers; and a cloud height distribution map showing the bottom height distribution of clouds.

[0093] Example 2

[0094] A second embodiment of the present invention provides specific calculation steps for data uncertainty estimation in a design method for measuring cloud and fog droplet spectra and types of high-altitude power transmission towers.

[0095] The specific steps for estimating data uncertainty include:

[0096] Determine the confidence intervals for different types of meteorological data acquired by CloudSat and CALIPSO, as well as the data acquired by the tower meteorological monitoring system.

[0097] In this embodiment, the calculation is performed at a 95% confidence level, and statistical methods are used to estimate the model parameters, including the mean and standard deviation.

[0098] Analyze the width and distribution of confidence intervals to determine the level of uncertainty in the assessment data and thus the data reliability.

[0099] For the confidence interval of the mean (at a 95% confidence level):

[0100]

[0101] Where CI represents the confidence interval. σ is the sample mean, Z is the z-score corresponding to the selected confidence level, σ is the population standard deviation, and n is the sample size.

[0102] It should be noted that a confidence interval represents the range of parameter values ​​(e.g., the mean) at a given confidence level. A 95% confidence interval means that there is 95% confidence that the true parameter value is within that range.

[0103] The reliability of the data is determined based on the level of uncertainty. For the evaluation of anomalous data, experts use their experience to determine the final data.

[0104] When observing temperature data, a set of temperature observation data is collected, and the behavior and standard deviation are calculated.

[0105] Temperature observation data: X = [20.5, 21.2, 22.0, 19.8, 20.7, 20.0, 21.5].

[0106] Sample mean: Sample standard deviation: σ = 0.53.

[0107] Choose a 95% confidence level: Z-value is 1.96 (corresponding to a 95% Z-score).

[0108] Calculate the 95% confidence interval for the mean temperature:

[0109]

[0110] This indicates a 95% confidence level that the actual average temperature is between approximately 20.50 and 21.36 degrees Celsius, and the data is further evaluated based on expert experience.

[0111] Example 3

[0112] The third embodiment of the present invention provides a workflow and beneficial effects of a design method for measuring cloud and fog droplet spectra and types of high-altitude power transmission towers.

[0113] Research by the China Meteorological Administration on the global cloud distribution characteristics studied by joint observations of CloudSat and CALIPSO shows that, compared with using CloudSat alone, the frequency of cloud occurrence increased by 28.04% when using cloud observation data from CloudSat and CALIPSO satellites, improving the accuracy of cloud area identification, but the improvement in clear sky identification was not significant. CALIPSO satellites can observe more high-altitude ice clouds over land that are not detectable by cloud radar, and the observation advantages become more and more obvious as the temperature decreases. Based on this, this study monitors cloud and fog droplet spectra and cloud and fog types on high-altitude power towers. It combines CloudSat and CALIPSO joint observation data with tower meteorological data, employing meteorological observation equipment and cloud and fog droplet spectrum measurement equipment to measure light scattering and absorption characteristics to obtain droplet size distribution. Droplets in the clouds and fog are measured to obtain their size distribution, concentration, and reflectivity. CloudSat and CALIPSO joint observation data are used to determine the cloud's vertical profile, height, thickness, and optical properties, thus enabling meteorological observation and droplet spectrum measurement of high-altitude power towers. Combining CloudSat and CALIPSO joint observation data yields more comprehensive cloud and fog environmental data, allowing researchers to determine cloud type, distribution characteristics, and vertical structure, thereby helping them to more intuitively understand the nature and evolution of clouds and fog.

[0114] Based on the vertical distribution and cloud top height information provided by the CALIPSO lidar, the optical thickness, cloud top height, and cloud bottom height parameters of the cloud are estimated, while the CloudSat cloud radar provides vertical profile reflectivity data of the cloud, which is used to infer the cloud type, fog droplet spectrum, and cloud particle properties.

[0115] Next, the data acquired by CloudSat and CALIPSO are compared with the data acquired by the tower meteorological monitoring system for the same and similar parameters. By comparing the data acquired by CloudSat and CALIPSO with the data acquired by the tower meteorological monitoring system for the same and similar parameters, the differences and consistency between the data sources are determined. This is to verify the accuracy and consistency of the data. For example, the cloud top height and cloud base height acquired by the fog droplet spectrum measurement equipment and CloudSat / CALIPSO data are compared to check for obvious differences or consistent trends. This is to determine the consistency of the cloud top height and cloud base height data. Then, experts evaluate the confidence interval of the data by calculating the data and make a final determination on the data that shows anomalies. This is to improve the accuracy and reliability of the evaluation data.

[0116] Finally, the data is integrated, analyzed, and visualized to facilitate user access to and browsing of cloud and fog monitoring data, integrating data collection, processing, analysis, and display functions. This enables real-time monitoring of changes in the cloud and fog environment and provides early warning capabilities, thereby assisting power tower managers in making appropriate decisions and taking appropriate measures.

[0117] CloudSat and CALIPSO observation data include multiple parameters such as cloud radar reflectivity and lidar reflectivity, which can be comprehensively analyzed to infer information such as cloud and fog type and particle size distribution. At the same time, CloudSat and CALIPSO can provide vertical profile information of clouds and fog, including cloud top height, cloud base height, and cloud optical thickness, enabling power transmission towers to obtain more detailed vertical distribution information of clouds and fog and to analyze cloud and fog characteristics more accurately.

[0118] In summary, compared with traditional methods, the cloud and fog droplet spectrum of power transmission towers using joint observation data from CloudSat and CALIPSO provides more detailed vertical distribution information, multi-parameter comprehensive analysis capabilities, and spatiotemporal consistency of data. This enables power transmission towers to more accurately monitor and assess the impact of clouds and fog on their operation, thereby improving safety and reliability.

[0119] Example 4

[0120] The fourth embodiment of the present invention differs from the previous embodiment in that:

[0121] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0122] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0123] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0124] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0125] Furthermore, in order to provide a concise description of exemplary embodiments, not all features of actual embodiments (i.e., those features that are not relevant to the currently considered best mode for carrying out the invention, or those features that are not relevant to implementing the invention) may be omitted.

[0126] It should be understood that numerous specific implementation decisions can be made during the development of any practical implementation, such as in any engineering or design project. Such development efforts may be complex and time-consuming, but for those skilled in the art who benefit from this disclosure, the development effort will be a routine work of design, manufacturing, and production without requiring much experimentation.

[0127] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers, characterized in that: include, Raw data is obtained from the joint observation data source of CloudSat and CALIPSO as the basic data source; Monitor and record the meteorological conditions in the areas where high-altitude power transmission towers are located in real time to obtain tower data; The data obtained from CloudSat and CALIPSO, as well as the data monitored by the deployed meteorological stations and meteorological monitoring devices, were processed to remove outliers and determine usable data. The processed data is integrated and analyzed, stored in a database, and then visualized. The data acquired by CloudSat and CALIPSO includes processing CloudSat data, analyzing cloud-related parameters to obtain cloud vertical contour information and cloud positional physical characteristics; and processing CALIPSO data to extract cloud-related parameters, including optical thickness, cloud top height, and cloud base height. The specific data processing steps are as follows: Receive raw lidar data from the CALIPSO satellite, wherein the lidar data is the lidar echo signal; By using the echo signals of lidar, clouds and aerosols in the atmosphere are inverted to determine the existence of clouds, the height distribution of clouds, and the optical properties of clouds. The height of the cloud is determined by analyzing the time delay of the reflected signal based on the detection results. : ； Where c is the speed of light. It is the time delay of the echo signal; Extracted cloud-related parameters include cloud optical thickness, cloud top height, and cloud base height; Outlier removal involves comparing data from CloudSat and CALIPSO with data from the tower meteorological monitoring system for identical or similar parameters, and then performing independent data verification. The specific steps for independent data validation are as follows: Data obtained from different data sources has the same or similar parameters; Data acquired from CloudSat and CALIPSO were compared with data acquired from the tower meteorological monitoring system to detect outlier data points; the standard deviation method was used to detect outlier data points. ； Where N is the number of data samples, Using the sample mean, the z-score method is used to analyze the degree of deviation of outlier data points: ； Where z represents the degree of deviation. The standard deviation is denoted by z; if the absolute value of z is greater than a predetermined threshold, then the data point... It is considered an outlier; When validating temperature data, a deviation threshold of twice the standard deviation of the data point is used. When the absolute value of the deviation z of the data point is greater than twice the standard deviation, it is considered an outlier. When validating humidity data, a deviation threshold of one standard deviation is used. When the absolute value of the deviation z of a data point is greater than one standard deviation, it is considered an outlier. When validating cloud data, a deviation threshold of one standard deviation is used. When the absolute value of the deviation z of a data point is greater than one standard deviation, it is considered an outlier. When verifying the number of cloud droplets, a deviation threshold of three times the standard deviation is used. When the absolute value of the deviation z of a data point is greater than three times the standard deviation, it is considered an outlier. When data anomalies are detected, correct the data points and create an independent data verification report, including comparison results, identification of anomaly data points, and corrective measures. The integrated analysis of the processed data includes fitting and integrating the processed tower meteorological data with CloudSat and CALIPSO data to establish a comprehensive tower cloud and fog environment database. Based on data mining and machine learning techniques, the data in the database is analyzed and statistically analyzed to determine the distribution characteristics of cloud droplet spectra and cloud types near high-altitude power transmission towers; The distribution characteristics include: droplet spectrum distribution characteristics, determined through data mining to identify droplet spectrum distribution characteristics near high-altitude power transmission towers at different time periods and seasons, including the size, quantity, and distribution density of water droplets and ice crystals; cloud and fog type distribution, determining the distribution of various cloud and fog types under different conditions near high-altitude power transmission towers; and spatiotemporal distribution characteristics, determining the distribution under different seasons and weather conditions, as well as the changes in cloud and fog within a day. The fitting integration includes constructing a Log-Normal distribution function to describe the cloud droplet spectrum near the power tower: ; Where N(D) is the number of cloud droplets obtained after fitting. It is the nucleus number concentration in the cloud droplet spectrum. It is the median cloud particle size in the cloud droplet spectrum. It is the logarithmic standard deviation of the number of cloud droplets.

2. The design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers as described in claim 1, characterized in that: The basic data sources include raw data obtained from the joint observation data sources of CloudSat and CALIPSO, and using the raw data of CloudSat and CALIPSO as the basic data sources, obtaining data on the vertical profile, height distribution, optical thickness, cloud top height, and cloud bottom height of the cloud layer, obtaining data on the types of stratiform clouds, cumulonimbus clouds, and cirrus clouds in the cloud layer, and obtaining atmospheric parameter data such as temperature and humidity. The acquisition of tower data includes setting up meteorological stations and meteorological monitoring devices to record and monitor the meteorological conditions in the area where the high-altitude power towers are located in real time, and to monitor the regional meteorological conditions and measure cloud and fog droplet spectra. The cloud droplet spectrum includes collecting cloud particle size data and cloud droplet nucleus number data in the cloud droplet spectrum.

3. The design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers as described in claim 2, characterized in that: The removal of outliers also includes evaluating the data acquired by CloudSat and CALIPSO and the data acquired by the tower meteorological monitoring system by calculating the confidence interval of the data; The specific steps for estimating data uncertainty include: Calculate the confidence intervals of different types of meteorological data acquired by CloudSat and CALIPSO, as well as the data acquired by the tower meteorological monitoring system; Analyze the width and distribution of confidence intervals to determine the level of uncertainty in the assessment data and thus the data confidence level. The reliability of the data is determined based on the level of uncertainty. For the evaluation of anomalous data, experts use their experience to determine the final data.

4. The design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers as described in claim 3, characterized in that: The visualization includes establishing a visualization platform based on geographic information GIS technology to visualize the specific analytical features of cloud and fog distribution, droplet spectrum and type, and generate corresponding feature maps.

5. A system employing the design method for a cloud and fog droplet spectrum and type measurement platform for high-altitude power transmission towers as described in any one of claims 1 to 4, characterized in that: The system includes a data acquisition module, a data processing module, and an analysis and display module; The data acquisition module obtains raw data from the joint observation data source of CloudSat and CALIPSO as the basic data source, monitors and records the meteorological conditions in the area where the high-altitude power towers are located in real time, and obtains tower data. The data processing module processes the data obtained from CloudSat and CALIPSO, as well as the data monitored by the deployed meteorological stations and meteorological monitoring devices, to remove outliers and determine usable data. The analysis and display module integrates and analyzes the processed data, stores the data in the database, and provides a visual display.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the design method for a cloud and fog droplet spectrum and type measurement platform for a high-altitude power transmission tower according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the design method for a cloud droplet spectrum and type measurement platform for high-altitude power transmission towers according to any one of claims 1 to 4.

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