Weather-considered line galloping three-dimensional state analysis method and system

Abstract

The invention discloses a weather-considered line galloping three-dimensional state analysis method and system, and relates to the technical field of line galloping monitoring information, and the method comprises the steps: collecting line galloping time sequence data in real time, and creating and reconstructing a first matrix; the Euclidean distance is calculated according to the reconstructed first matrix, and the icing thickness and the early warning value are calculated according to the micrometeorological information time sequence; and if the newly received line galloping time sequence data exceeds the sliding window, caching the data and performing state analysis. The weather-considered line galloping three-dimensional state analysis method provided by the invention improves data integrity and system response speed by collecting data in real time, optimizes data processing efficiency, improves accuracy and applicability of early warning by calculating the Euclidean distance of the time sequence before and after reconstruction, and improves the accuracy and applicability of early warning. By reconstructing and analyzing newly received data, the flexibility and practicability of the system are improved, and better effects are achieved in the aspects of processing efficiency, early warning accuracy and flexibility.

Description

Technical Field

[0001] The invention relates to the field of line galloping monitoring information technology, and in particular to a three-dimensional state analysis method of line galloping taking weather into consideration. Background Art

[0002] In traditional power transmission line galloping monitoring systems, the galloping data of transmission lines are mainly obtained by relying on the coupling algorithm of the global navigation satellite system (GNSS) and the inertial navigation system (INS). These systems record and analyze the time series data of line galloping, and trigger an alarm signal when the galloping index exceeds the preset fixed threshold. However, such monitoring technology usually fails to consider the impact of environmental factors on the safety of line galloping, especially changes in weather conditions.

[0003] For example, the same dancing amplitude and frequency will pose different threats to the line under different weather conditions. In an icy state, even a small dancing may pose a serious threat to line safety, while in un-iced conditions, the same dancing may be safe. Existing monitoring systems, due to their lack of adaptability to such environmental variables, often cannot accurately reflect actual safety risks, which may lead to excessive alarms or missed reports. A fixed threshold that is too high may result in failure to alarm for severe dancing, resulting in failure to carry out maintenance and omissions. A threshold that is too low may cause frequent false alarms, increasing operation and maintenance costs and interference. 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: the existing line galloping three-dimensional state analysis has false alarms or missed alarms and poor accuracy, and how to optimize the influence of environmental factors on transmission line galloping monitoring.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a three-dimensional state analysis method for line dancing taking into account weather, comprising real-time collection of line dancing time series data, creation of a first matrix and reconstruction; calculation of the Euclidean distance based on the reconstructed first matrix, and calculation of ice thickness and warning value based on the micro-meteorological information time series; if the newly received line dancing time series data exceeds the sliding window, caching the data and performing state analysis.

[0007] As a preferred solution of the three-dimensional state analysis method of line dancing taking into account weather as described in the present invention, wherein: the real-time collection of line dancing time series data includes obtaining window data, collecting line dancing time series data {X(0), X(1), ..., X(N)}, when N is greater than a first set threshold, setting a sliding window L, sliding the sliding window from the beginning of the time series data to obtain values, and obtaining window data {X(t), X(t+1), ..., X(t+L)} each time the sliding value is obtained.

[0008] As a preferred solution of the method for analyzing the three-dimensional state of line dancing taking into account weather conditions of the present invention, the creating and reconstructing of the first matrix includes creating a first matrix for each component of the window data, and reconstructing all the window data {X(t) i ,X(t+1) i ,...,X(t+L) i} as the rows of the matrix to form the first matrix, and the first matrix is ​​decomposed by SVD as follows:

[0009]

[0010] Among them, U i and are the left and right singular vectors of the i-th component, ∑ i is the singular value matrix of the i-th component, and the singular values ​​in the singular value matrix are Sort and remove the smallest a% of all singular values and the left and right singular vectors, through the remaining singular values The left singular vector and the right singular vector reconstruct the first matrix of each component. After reconstruction, the first matrix of each component is expressed as:

[0011]

[0012] Among them, U i * and are the left and right singular vectors of the remaining i-th component, respectively.

[0013] As a preferred solution of the method for analyzing the three-dimensional state of line waving taking into account weather conditions described in the present invention, wherein: the calculation of the Euclidean distance based on the reconstructed first matrix includes constructing a second matrix, taking out each row of the first matrix of each component after reconstruction from top to bottom, filling all the taken rows with 0 at the beginning and end, filling m-1 0s before the first element of the mth row, and filling NL 0s after the Lth element of the mth row, forming all the rows after 0 filling into rows of the second matrix in order, and taking the average of each column of the second matrix to reconstruct the line waving time series data of each component Calculate the Euclidean distance of each eigenmode component before and after reconstruction, expressed as:

[0014]

[0015] Among them, R i is the Euclidean distance of the eigenmode component, t is the time point, t≤N.

[0016] As a preferred solution of the three-dimensional state analysis method of line dancing taking into account weather according to the present invention, wherein: the calculation of ice thickness and warning value according to the micro-meteorological information time series includes obtaining the temperature time series of the line dancing monitoring point, extracting the time points below zero degrees Celsius in the dancing monitoring point temperature time series, obtaining the micro-meteorological information time series at the time points below zero degrees Celsius, and calculating the ice thickness at the time points below zero degrees Celsius according to the micro-meteorological information time series, expressed as:

[0017]

[0018] Where j is the time variable, P(j) is the process precipitation at time j, K is the unit adjustment coefficient, ρ i is the density of rime, V(j) is the horizontal wind speed perpendicular to the conductor at time j, W(j) is the liquid water content at time j, and the warning weight coefficient at the time point is calculated. The warning weight coefficient at the time point below zero degrees Celsius is expressed as:

[0019]

[0020] Among them, T max is the maximum ice thickness, and the warning value at time t is calculated, which is expressed as:

[0021] Al i (t) = R i (t)*β(t)

[0022] Among them, Al i (t) is the warning value at time t. If the warning value is greater than the preset threshold, the time is marked as the warning point.

[0023] As a preferred solution of the three-dimensional state analysis method of line dancing taking into account weather according to the present invention, wherein: the calculation of ice thickness and warning value according to the micro-meteorological information time series also includes extracting the time points above zero degrees Celsius in the dancing monitoring point temperature time series, obtaining the micro-meteorological information time series at the time points above zero degrees Celsius, and calculating the ice thickness at the time points above zero degrees Celsius according to the micro-meteorological information time series, expressed as:

[0024]

[0025]

[0026] Where τ is the ice reflectivity, S is the average solar radiation intensity, ∈ is the emissivity of ice, λ is the Stefan-Boltzmann constant, and T s is the temperature of ice, T a is the temperature of the surrounding air, h c is the heat transfer coefficient, L 1 is the melting heat of ice, t 0 is the starting time when the temperature is above zero degrees, and the warning weight coefficient of the icing impact time point is calculated.

[0027] As a preferred solution of the three-dimensional line dancing state analysis method taking weather into consideration described in the present invention, wherein: the caching data and performing state analysis includes if the newly received line dancing time series data exceeds L and is less than m·L, then (m-1)·L newly received line dancing time series data are intercepted, and the remaining line dancing time series data are cached, the intercepted (m-1)·L line dancing time series data are processed by constructing a first matrix and a second matrix to obtain reconstructed (m-1)·L line dancing time series data, the (m-1)·L line dancing time series data before reconstruction are added to the original line dancing time series data before reconstruction in chronological order, the reconstructed (m-1)·L line dancing time series data are added to the original line dancing time series data after reconstruction in chronological order, and the warning point time is marked by calculating the warning value.

[0028] Another object of the present invention is to provide a three-dimensional state analysis system for line galloping that takes weather into consideration. The system can calculate the Euclidean distance at each time point through an early warning calculation module and evaluate the risk of line galloping, thereby solving the current problem of being unable to accurately evaluate the actual threat of galloping under adverse conditions such as icing.

[0029] As a preferred solution of the three-dimensional state analysis system of line dancing taking into account weather as described in the present invention, it includes: a collection construction module, an early warning calculation module, and a cache analysis module; the collection construction module is used to collect line dancing time series data in real time, create a first matrix and reconstruct it; the early warning calculation module is used to calculate the Euclidean distance according to the reconstructed first matrix, and calculate the ice thickness and early warning value according to the micro-meteorological information time series; the cache analysis module is used to cache data and perform state analysis if the newly received line dancing time series data exceeds the sliding window.

[0030] A computer device includes a memory and a processor, wherein the memory stores a computer program, and wherein the processor executes the computer program to implement a step of a three-dimensional state analysis method of line dancing taking into account weather.

[0031] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a method for analyzing the three-dimensional state of line dancing taking into account weather are implemented.

[0032] Beneficial effects of the present invention: The three-dimensional state analysis method of line dancing taking weather into consideration provided by the present invention improves data integrity and system response speed by real-time data collection, optimizes data processing efficiency by segmented processing of large-scale data, reduces the possibility of false alarms and missed alarms by creating matrices for each component of window data, improves the accuracy of analysis results by reconstructing the matrix after filtering out noise, improves the accuracy and applicability of early warning by calculating the Euclidean distance of the time series before and after reconstruction, reduces the risk of accidents by calculating and analyzing the early warning value, improves the flexibility and practicality of the system by reconstructing and analyzing the newly received data, and achieves better results in processing efficiency, early warning accuracy and flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0034] Figure 1 An overall flow chart of a method for analyzing three-dimensional state of line motion taking weather into consideration provided in the first embodiment of the present invention.

[0035] Figure 2 An overall module diagram of a three-dimensional line dancing state analysis system taking weather into consideration provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0037] Example 1

[0038] Reference Figure 1 , which is an embodiment of the present invention, provides a method for analyzing the three-dimensional state of line dancing taking into account weather conditions, comprising:

[0039] S1: Collect line dancing time series data in real time, create the first matrix and reconstruct it.

[0040] Furthermore, real-time acquisition of line dancing time series data includes obtaining window data.

[0041] It should be noted that the line dancing time series data {X(0), X(1), ..., X(N)} is collected. When N is greater than the first set threshold, the sliding window L is set, and the sliding window starts to slide from the beginning of the time series data to obtain window data {X(t), X(t+1), ..., X(t+L)} each time the sliding value is obtained.

[0042] It should also be noted that the length of the sliding window L is less than half of N, the sliding step is 1, and the first set threshold is 60 seconds.

[0043] Furthermore, creating a first matrix and reconstructing includes creating a first matrix for each component of the window data.

[0044] It should be noted that all window data {X(t) i ,X(t+1) i ,...,X(t+L) i} as the rows of the matrix to form the first matrix, and the first matrix is ​​decomposed by SVD as follows:

[0045]

[0046] Among them, U i and are the left and right singular vectors of the i-th component, ∑ i is the singular value matrix of the i-th component, and the singular values ​​in the singular value matrix are Sort and remove the smallest a% of all singular values and the left and right singular vectors, through the remaining singular values The left singular vector and the right singular vector reconstruct the first matrix of each component. After reconstruction, the first matrix of each component is expressed as:

[0047]

[0048] Among them, U i * and are the left and right singular vectors of the remaining i-th component, respectively.

[0049] It should also be noted that the calculation of a% is expressed as:

[0050]

[0051] Among them, TL is the length of time in a year when the wind speed at the dancing monitoring point is greater than the set level, and TA is the total time in a year.

[0052] S2: Calculate the Euclidean distance based on the reconstructed first matrix, and calculate the ice thickness and warning value based on the micrometeorological information time series.

[0053] Furthermore, calculating the Euclidean distance according to the reconstructed first matrix includes constructing a second matrix.

[0054] It should be noted that each row of the first matrix of each component after reconstruction is taken from top to bottom, and all the taken rows are padded with 0 at the beginning and end, m-1 0s are padded before the first element of the mth row, and NL 0s are padded after the Lth element of the mth row. All the rows after 0 padded are sequentially formed into rows of the second matrix, and each column of the second matrix is ​​averaged to reconstruct the line dancing time series data of each component. Calculate the Euclidean distance of each eigenmode component before and after reconstruction, expressed as:

[0055]

[0056] Among them, R i is the Euclidean distance of the eigenmode component, t is the time point, t≤N.

[0057] Furthermore, the ice thickness and warning value are calculated based on the time series of micro-meteorological information, including obtaining the temperature time series of the line sway monitoring point.

[0058] It should be noted that the time points below zero degrees Celsius in the temperature time series of the dancing monitoring point are extracted, and the micro-meteorological information time series at the time points below zero degrees Celsius is obtained. The ice thickness at the time points below zero degrees Celsius is calculated based on the micro-meteorological information time series, which is expressed as:

[0059]

[0060] Where j is the time variable, P(j) is the process precipitation at time j, K is the unit adjustment coefficient, ρ i is the density of rime, V(j) is the horizontal wind speed perpendicular to the conductor at time j, W(j) is the liquid water content at time j, and the warning weight coefficient at the time point is calculated. The warning weight coefficient at the time point below zero degrees Celsius is expressed as:

[0061]

[0062] Among them, T max is the maximum ice thickness, and the warning value at time t is calculated, which is expressed as:

[0063] Al i (t) = R i(t)*β(t)

[0064] Among them, Al i (t) is the warning value at time t. If the warning value is greater than the preset threshold, the time is marked as the warning point.

[0065] It should also be noted that for time points below zero degrees Celsius, β(t)=1.

[0066] Furthermore, calculating ice thickness and warning values ​​based on the micro-meteorological information time series also includes extracting time points above zero degrees Celsius in the temperature time series of the dancing monitoring point.

[0067] It should be noted that the time series of micro-meteorological information at the time point above zero degrees Celsius is obtained, and the ice thickness at the time point above zero degrees Celsius is calculated based on the time series of micro-meteorological information, which is expressed as:

[0068]

[0069]

[0070] Where τ is the ice reflectivity, S is the average solar radiation intensity, ∈ is the emissivity of ice, λ is the Stefan-Boltzmann constant, and T s is the temperature of ice, T a is the temperature of the surrounding air, h c is the heat transfer coefficient, L 1 is the melting heat of ice, t 0 is the starting time when the temperature is above zero degrees, and the warning weight coefficient of the icing impact time point is calculated.

[0071] It should also be noted that the time series of micrometeorological information includes wind speed perpendicular to the conductor, rime density, process precipitation and freezing rain time; the line dancing time series data includes the position of the dancing monitoring point, the acceleration of the dancing monitoring point and the speed of the dancing monitoring point.

[0072] S3: If the newly received line dancing time series data exceeds the sliding window, cache the data and perform status analysis.

[0073] Furthermore, buffering the data and performing status analysis includes if the number of newly received line dancing time series data exceeds L and is less than m·L.

[0074] It should be noted that (m-1)·L of the newly received line dancing time series data are intercepted, and the remaining line dancing time series data are cached, the intercepted (m-1)·L line dancing time series data are processed by constructing the first matrix and the second matrix to obtain the reconstructed (m-1)·L line dancing time series data, the (m-1)·L line dancing time series data before reconstruction are added to the original line dancing time series data before reconstruction in chronological order, the reconstructed (m-1)·L line dancing time series data are added to the original line dancing time series data after reconstruction in chronological order, and the warning point time is marked by calculating the warning value.

[0075] Example 2

[0076] An embodiment of the present invention provides a three-dimensional state analysis method for line dancing taking into account weather conditions. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0077] A power transmission line located under different meteorological conditions was selected, and multiple dancing monitoring points were installed. The dancing time series data and micro-meteorological information were recorded respectively. A comparative experiment was carried out using the method of the present invention and the existing line dancing monitoring method. In the experimental preparation stage, representative meteorological conditions were first selected, namely sunny days, light icing weather and severe icing weather. High-precision GNSS equipment and temperature and humidity sensors were installed at the line dancing monitoring points to ensure that real-time dancing time series data and micro-meteorological information could be accurately obtained. The experimental design adopted the sliding window technology to process the time series data in segments in order to better identify the vibration mode of the line.

[0078] The method of the present invention is used to collect line dancing time series data in real time. 20 sets of data are collected under each meteorological condition, and the data collection interval is 1 second. During the collection process, the dancing parameters such as the monitoring point position, acceleration and speed are recorded, and these data are preliminarily processed in the form of a matrix. The collected data are used to create a first matrix, and then the matrix is ​​decomposed by the singular value decomposition (SVD) method to remove noise and outliers and retain the main vibration mode. The comparative experiment directly uses the original data for analysis without noise filtering. The data after SVD processing is reconstructed. The reconstructed data can more truly reflect the actual situation of line dancing than the original data. At the same time, the ice thickness is calculated in combination with micro-meteorological data through the method of the present invention, and the warning value at each time point is calculated. The reconstructed data is compared with the data obtained by the traditional method, focusing on the dancing state of the line under different weather conditions, the change of the warning value, and the corresponding line safety analysis results.

[0079] As shown in Table 1, under sunny conditions, the amplitude of the line galloping is small and the frequency is relatively stable. Since there is no icing, the warning value remains at a low level. This shows that when there is no icing, the galloping has little impact on the safety of the line. At this time, the line galloping analysis method of the present invention can accurately identify and confirm that the line is in a safe state. Under light icing conditions, due to the increase in the weight of the line caused by icing, the vibration amplitude increases significantly and the vibration frequency decreases. Through the analysis method of the present invention, the increase in the warning value can be clearly seen, especially when the ice layer is thick, the warning value is significantly higher than the warning value of the traditional analysis method. Under severe icing conditions, the vibration amplitude is further increased and the vibration frequency is further reduced, reflecting that the mechanical load on the line increases sharply and the risk increases significantly. The method of the present invention combines the comprehensive analysis of vibration mode, micrometeorological information and ice thickness, and the calculated warning value is significantly higher than that of other methods, and the change of the warning value is more stable and reliable, which shows the efficient risk identification ability of the present invention under severe icing conditions, and also reflects the superiority and practicality in dealing with extreme weather conditions.

[0080] Table 1 Experimental data table

[0081] time Vibration Amplitude Vibration frequency Ice thickness Warning value sunny 0 seconds 0.1m 0.5 Hz 0 mm 0.05 sunny 1 second 0.15m 0.48 Hz 0 mm 0.06 sunny 2 seconds 0.12m 0.49 Hz 0 mm 0.05 sunny 3 seconds 0.1m 0.47 Hz 0 mm 0.05 sunny 4 seconds 0.11m 0.46 Hz 0 mm 0.05 sunny 5 seconds 0.13m 0.45 Hz 0 mm 0.06 Light ice cover 0 seconds 0.3m 0.4 Hz 2 mm 0.12 Light ice cover 1 second 0.32m 0.38 Hz 2 mm 0.13 Light ice cover 2 seconds 0.31m 0.37 Hz 2 mm 0.13 Light ice cover 3 seconds 0.33m 0.35 Hz 2 mm 0.14 Light ice cover 4 seconds 0.34m 03 Hz 2 mm 0.15 Light ice cover 5 seconds 0.35m 0.34 Hz 2 mm 0.15 Severe icing 0 seconds 0.45m 0.3 Hz 5 mm 0.25 Severe icing 1 second 0.47m 0.28 Hz 5 mm 0.26 Severe icing 2 seconds 0.49m 0.26 Hz 5 mm 0.27 Severe icing 3 seconds 0.48m 0.24 Hz 5 mm 0.26 Severe icing 4 seconds 0.5m 0.22 Hz 5 mm 0.28 Severe icing 5 seconds 0.52m 0.2 Hz 5 mm 0.29

[0082] Example 3

[0083] Reference Figure 2 , which is an embodiment of the present invention, provides a three-dimensional state analysis system for line dancing taking into account weather conditions, including: a collection and construction module, an early warning calculation module, and a cache analysis module.

[0084] The acquisition and construction module is used to collect line dancing time series data in real time, create the first matrix and reconstruct it; the warning calculation module is used to calculate the Euclidean distance based on the reconstructed first matrix, and calculate the ice thickness and warning value based on the micro-meteorological information time series; the cache analysis module is used to cache the data and perform status analysis if the newly received line dancing time series data exceeds the sliding window.

[0085] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it 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 the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0086] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0087] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0088] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0089] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A three-dimensional state analysis method for line galloping taking into account weather, characterized in that: include: Collect line dancing time series data in real time, create the first matrix and reconstruct it; The Euclidean distance is calculated based on the reconstructed first matrix, and the ice thickness and warning value are calculated based on the time series of micro-meteorological information; If the newly received line dancing time series data exceeds the sliding window, the data is cached and status analysis is performed.

2. The method for analyzing the three-dimensional state of line movement taking into account weather conditions as claimed in claim 1, characterized in that: The real-time collection of line dancing time series data includes obtaining window data, collecting line dancing time series data {X(0), X(1), ..., X(N)}, when N is greater than a first set threshold, setting a sliding window L, sliding the sliding window from the beginning of the time series data to obtain values, and obtaining window data {X(t), X(t+1), ..., X(t+L)} each time the sliding value is obtained.

3. The method for analyzing the three-dimensional state of line movement taking into account weather conditions as claimed in claim 2, characterized in that: The creating and reconstructing of the first matrix includes creating a first matrix for each component of the window data, and reconstructing all the window data {X(t) i ,X(t+1) i ,...,X(t+L) i } as the rows of the matrix to form the first matrix, and the first matrix is ​​decomposed by SVD as follows: Among them, U i and are the left and right singular vectors of the i-th component, ∑ i is the singular value matrix of the i-th component, and the singular values ​​in the singular value matrix are Sort and remove the smallest a% of all singular values and the left and right singular vectors, through the remaining singular values The left singular vector and the right singular vector reconstruct the first matrix of each component. After reconstruction, the first matrix of each component is expressed as: Among them, U i * and are the left and right singular vectors of the remaining i-th component, respectively.

4. The method for analyzing the three-dimensional state of line movement taking into account weather conditions as claimed in claim 3, characterized in that: The calculation of the Euclidean distance according to the reconstructed first matrix includes constructing a second matrix, taking out each row of the reconstructed first matrix of each component from top to bottom, padding all the taken rows with 0 at the beginning and end, padding m-1 0s before the first element of the mth row, padding NL 0s after the Lth element of the mth row, and forming all the rows after the 0 padding into rows of the second matrix in order, and averaging each column of the second matrix to reconstruct the line dancing time series data of each component. Calculate the Euclidean distance of each eigenmode component before and after reconstruction, expressed as: Among them, R i is the Euclidean distance of the eigenmode component, t is the time point, t≤N.

5. The method for analyzing the three-dimensional state of line movement taking into account weather conditions as claimed in claim 4, characterized in that: The calculation of ice thickness and warning value according to the micro-meteorological information time series includes obtaining the temperature time series of the line dancing monitoring point, extracting the time points below zero degrees Celsius in the dancing monitoring point temperature time series, obtaining the micro-meteorological information time series at the time points below zero degrees Celsius, and calculating the ice thickness at the time points below zero degrees Celsius according to the micro-meteorological information time series, which is expressed as: Where j is the time variable, P(j) is the process precipitation at time j, K is the unit adjustment coefficient, ρ i is the density of rime, V(j) is the horizontal wind speed perpendicular to the conductor at time j, W(j) is the liquid water content at time j, and the warning weight coefficient at the time point is calculated. The warning weight coefficient at the time point below zero degrees Celsius is expressed as: Among them, T max is the maximum ice thickness, and the warning value at time t is calculated, which is expressed as: Al i (t)=R i (t)*β(t) Among them, Al i (t) is the warning value at time t. If the warning value is greater than the preset threshold, the time is marked as the warning point.

6. The method for analyzing the three-dimensional state of line galloping taking into account weather conditions as claimed in claim 5, characterized in that: The calculation of ice thickness and warning value according to the micro-meteorological information time series also includes extracting the time point above zero degrees Celsius in the dancing monitoring point temperature time series, obtaining the micro-meteorological information time series at the time point above zero degrees Celsius, and calculating the ice thickness at the time point above zero degrees Celsius according to the micro-meteorological information time series, which is expressed as: Where τ is the ice reflectivity, S is the average solar radiation intensity, ∈ is the emissivity of ice, λ is the Stefan-Boltzmann constant, and T s is the temperature of ice, T a is the temperature of the surrounding air, h c is the heat transfer coefficient, L1 is the melting heat of ice, t0 is the starting time when the temperature is above zero degrees, and the warning weight coefficient of the icing impact time point is calculated.

7. The method for analyzing the three-dimensional state of line movement taking into account weather conditions as claimed in claim 6, characterized in that: The caching of data and performing status analysis includes if the newly received line dancing time series data exceeds L and is less than m·L, then intercepting (m-1)·L of the newly received line dancing time series data, and caching the remaining line dancing time series data, processing the intercepted (m-1)·L line dancing time series data by constructing a first matrix and a second matrix to obtain reconstructed (m-1)·L line dancing time series data, adding the (m-1)·L line dancing time series data before reconstruction to the original line dancing time series data before reconstruction in chronological order, adding the reconstructed (m-1)·L line dancing time series data to the original line dancing time series data after reconstruction in chronological order, and marking the warning point time by calculating the warning value.

8. A system using the weather-sensitive line galloping three-dimensional state analysis method as claimed in any one of claims 1 to 7, characterized in that: It includes collection construction module, early warning calculation module and cache analysis module; The acquisition and construction module is used to acquire line dancing time series data in real time, create a first matrix and reconstruct it; The warning calculation module is used to calculate the Euclidean distance according to the reconstructed first matrix, and calculate the ice thickness and the warning value according to the micro-meteorological information time series; The buffer analysis module is used to buffer the data and perform status analysis if the newly received line dancing time series data exceeds the sliding window.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method for analyzing the three-dimensional state of line galloping taking into account weather according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for analyzing the three-dimensional state of line galloping taking into account weather according to any one of claims 1 to 7 are implemented.

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