CN117851414B - Lightning arrester aging test data storage method and system - Google Patents
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Abstract
The invention relates to the technical field of data processing, in particular to a lightning arrester aging test data storage method and system, comprising the following steps: obtaining a historical current regularity index according to the historical current data sequence; obtaining a historical relevance index according to the historical current data sequence and the historical voltage data sequence; obtaining a current regularity index and a current relevance index according to the current data sequence and the current voltage data sequence; and obtaining a current reliability index according to the historical current regularity index, the current regularity index, the historical relevance index and the current relevance index, obtaining a voltage reliability index as well, and carrying out storage analysis according to the current reliability index and the voltage reliability index. The abnormality analysis method is used for realizing abnormality detection by analyzing whether the change characteristics and the associated characteristics of the data accord with the change characteristics and the associated characteristics of the normal data, and has obvious advantages for abnormality analysis of the data with larger change.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a lightning arrester aging test data storage method and system.
Background
The lightning arrester aging test database is established, so that the characteristics of the insulation structure of the lightning arrester can be analyzed in a multi-dimensional manner, and guidance is provided for the design of the external insulation of the lightning arrester and the reliability diagnosis of equipment.
In the aging test process of the lightning arrester, the collected test data of the lightning arrester are abnormal due to the change of the test environment or improper operation of test personnel, and the abnormal data are stored in an aging test database of the lightning arrester, so that the subsequent data analysis is not helped, and the accuracy of the analysis result is disturbed. Therefore, in order to make the constructed lightning arrester aging test database better provide assistance for subsequent lightning arrester aging analysis, anomaly analysis needs to be performed on lightning arrester aging test data before the lightning arrester aging test data are stored in the lightning arrester aging test database.
The conventional anomaly analysis method generally performs anomaly analysis according to the difference characteristics between data, wherein the difference between the anomaly data and normal data is large, and the difference between the normal data is small, so as to realize anomaly determination. And because the normal lightning arrester aging test data also have larger difference, the abnormality judgment of the lightning arrester aging test data is difficult to be completed by using the traditional abnormality analysis algorithm.
Disclosure of Invention
In order to solve the problems, the invention provides a lightning arrester aging test data storage method and a lightning arrester aging test data storage system.
The invention relates to a lightning arrester aging test data storage method and a lightning arrester aging test data storage system, which adopt the following technical scheme:
one embodiment of the invention provides a lightning arrester aging test data storage method, which comprises the following steps:
acquiring a historical current data sequence, a historical voltage data sequence, a current data sequence and a current voltage data sequence of the lightning arrester;
analyzing the periodic condition of the historical current data sequence to obtain a historical current periodic parameter; analyzing the related condition of self data in the historical current data sequence to obtain a historical current autocorrelation parameter; analyzing the fluctuation condition of the historical current data sequence to obtain historical current fluctuation parameters; obtaining a historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter; obtaining historical voltage regularity indexes, current regularity indexes and current voltage regularity indexes according to the historical voltage data sequence, the current data sequence and the current voltage data sequence; obtaining a historical relevance index according to the ratio of the historical current data sequence to the position data of the historical voltage data sequence; obtaining a current relevance index according to the current data sequence and the current voltage data sequence;
obtaining a current reliability index according to the current regularity index, the historical relevance index and the current relevance index, and obtaining a voltage reliability index according to the historical voltage regularity index, the current voltage regularity index, the historical relevance index and the current relevance index;
And carrying out anomaly analysis according to the current reliability index and the voltage reliability index to obtain an anomaly analysis result, and carrying out storage processing according to the anomaly analysis result.
Preferably, the analyzing the cycle condition of the historical current data sequence to obtain the historical current cycle parameter includes the following specific steps:
performing Fourier transform on the historical current data sequence to obtain frequency spectrum data, acquiring the amplitude corresponding to each frequency in the frequency spectrum data, and acquiring the maximum whole amplitude from the amplitudes of all frequencies, and recording the maximum amplitude as the periodic parameter of the historical current.
Preferably, the analyzing the correlation condition of the self data in the historical current data sequence to obtain the historical current autocorrelation parameter includes the following specific steps:
wherein, Representing the nth historical current data in the sequence of historical current data,/>Representing the average of all historical current data in a sequence of historical current data,/>Representing the n+k-th historical current data in the historical current data sequence,/>Represents the N-k historical current data in the historical current data sequence, N represents the number of the historical current data in the historical current data sequence,/>Representing historical current autocorrelation parameters,/>Representing a function taking the maximum value.
Preferably, the analyzing the fluctuation condition of the historical current data sequence to obtain the historical current fluctuation parameter includes the following specific steps:
And acquiring variances and average values of all the historical current data in the historical current data sequence, and acquiring historical current fluctuation parameters according to the variances and average values of the historical current data, wherein the historical current fluctuation parameters are positively correlated with the variances and positively correlated with the average values.
Preferably, the obtaining the historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter includes the following specific steps:
And obtaining a historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter, wherein the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current regularity index are positively correlated, and the historical current volatility parameter and the historical current regularity index are negatively correlated.
Preferably, the historical relevance index is obtained according to the ratio of the historical current data sequence to the position data of the historical voltage data sequence; the current relevance index is obtained according to the current data sequence and the current voltage data sequence, and the method comprises the following specific steps:
Recording the ratio of each historical voltage data in the historical voltage data sequence to the historical current data at the same position in the historical current data sequence as a first ratio; recording the difference value of each first ratio and the previous first ratio as fluctuation degree, and taking the average value of all fluctuation degrees as a historical relevance index;
and obtaining a current relevance index according to the current data sequence and the current voltage data sequence.
Preferably, the current reliability index is obtained according to the current regularity index, the historical relevance index and the current relevance index, and the voltage reliability index is obtained according to the historical voltage regularity index, the current voltage regularity index, the historical relevance index and the current relevance index, comprising the following specific steps:
wherein, Representing the current regularity index,/>Index of historical current regularity,/>Representing historical relevance index,/>Representing the current relevance index,/>Representing a linear normalization process,/>A current reliability index is represented;
And acquiring a voltage reliability index.
Preferably, the performing the anomaly analysis according to the current reliability index and the voltage reliability index to obtain an anomaly analysis result includes the specific steps of:
obtaining a current data sequence to be analyzed according to the current data sequence;
Comparing the current reliability index of the current data sequence to be analyzed with a preset reliability threshold, wherein when the current reliability index of the current data sequence to be analyzed is larger than the preset reliability threshold U, no abnormality exists in the current data sequence to be analyzed, and when the current reliability index of the current data sequence to be analyzed is smaller than or equal to the preset reliability threshold U, no abnormality exists in the current data sequence to be analyzed;
and obtaining an abnormal analysis result of the voltage according to the voltage reliability index.
Preferably, the storing process according to the result of the anomaly analysis includes the specific steps of:
when the current data sequence to be analyzed is abnormal, the current data sequence to be analyzed is coded and compressed by using a run-length coding algorithm to obtain a coding sequence, the coding sequence is stored in a block chain of a database, and when the current data sequence to be analyzed is abnormal, the current data sequence to be analyzed cannot be stored in the database;
And carrying out storage processing according to the abnormal analysis result of the voltage.
The lightning arrester aging test data storage system comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor realizes the steps of the lightning arrester aging test data storage method when executing the computer program.
The technical scheme of the invention has the beneficial effects that: and obtaining a historical current regularity index by describing a historical current data sequence change rule. Obtaining a historical relevance index according to the relevance between the historical current data sequence and the historical voltage data sequence; obtaining a current regularity index and a current relevance index according to the current data sequence and the current voltage data sequence; and comparing the current correlation index with the historical correlation index to obtain the current reliability by comparing the historical current regularity with the current regularity index. Voltage reliability is also obtained. By the method, abnormal analysis is performed, and abnormal erroneous judgment is not caused by interference of fluctuation of data of the system. Abnormal current data and abnormal current voltage data can be screened out more accurately. Thereby preventing the introduction of abnormal data in the database.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of steps of a lightning arrester aging test data storage method according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of a lightning arrester aging test data storage method and system according to the invention, which are specific embodiments, structures, features and effects thereof, with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a lightning arrester aging test data storage method and a system specific scheme by combining a drawing.
Referring to fig. 1, a flowchart of steps of a lightning arrester aging test data storage method according to an embodiment of the present invention is shown, the method includes the steps of:
s1, acquiring a historical current data sequence, a historical voltage data sequence, a current data sequence and a current voltage data sequence of the lightning arrester.
All current data and corresponding voltage data are extracted from a memory of the lightning arrester aging test equipment and are respectively recorded as historical current data and historical voltage data, the extracted historical current data form a historical current data sequence according to time sequence, and the extracted historical voltage data form a historical voltage data sequence according to time sequence.
The lightning arrester aging test equipment is used for collecting current data and voltage data at L moments and recording the current data and the current voltage data as current data and current voltage data respectively, the current data is formed into a current data sequence according to time sequence, and the current voltage data is formed into a current voltage data sequence according to time sequence. L represents a preset acquisition duration, the embodiment is described by taking L as 100 as an example, other embodiments can take other values, and the embodiment is not particularly limited.
It should be noted that the number of present current data and present voltage data is much smaller than the number of historical current data and historical voltage data.
S2, obtaining a historical current regularity index and a historical voltage regularity index according to the historical current data sequence and the historical voltage data sequence, and obtaining a historical relevance index according to the historical current data sequence and the historical voltage data sequence.
S201, obtaining a historical current regularity index and a historical voltage regularity index according to the historical current data sequence and the historical voltage data sequence.
It should be noted that, because the data size of the historical current data is large and the abnormal historical current data generally occupies a relatively small area, the overall data rule of the historical current data mainly shows the normal data rule. Therefore, the historical current data can be used as a comparison object to analyze whether the current data has abnormality. The same current voltage data can also be used as a comparison object to analyze whether the current voltage data has abnormality or not.
It should be further noted that, in order to analyze whether the current data or the current voltage data has an abnormality, the historical current data or the historical voltage data needs to be analyzed.
Firstly, obtaining a historical current periodic parameter according to a historical current data sequence.
As an example, a method for acquiring a historical current periodicity parameter includes: performing Fourier transform on the historical current data sequence to obtain frequency spectrum data, acquiring the amplitude corresponding to each frequency in the frequency spectrum data, and acquiring the maximum whole amplitude from the amplitudes of all frequencies, and recording the maximum amplitude as the periodic parameter of the historical current.
In the prior art, the reciprocal of the frequency is equal to the period, and the amplitude of the frequency reflects the content of the information including the frequency in the historical current data sequence, so the amplitude of the frequency may also reflect the content of the information including the period corresponding to the frequency in the historical current data sequence. Thus, the historical current periodicity parameter can reflect the periodicity of the data in the historical current data sequence, and the larger the value is, the more data containing periodicity rules in the historical current data sequence.
And then obtaining the historical current autocorrelation parameters according to the historical current data sequence.
As an example, the calculation formula of the historical current autocorrelation parameter is:
wherein, Representing the nth historical current data in the sequence of historical current data,/>Representing the average of all historical current data in a sequence of historical current data,/>Representing the n+k-th historical current data in the historical current data sequence,/>Represents the N-k th historical current data in the historical current data sequence, and N represents the number of the historical current data in the historical current data sequence. /(I)Representing historical current autocorrelation parameters. /(I)Representing a function taking the maximum value.
It should be noted that, the autocorrelation parameter adopts the existing autocorrelation coefficient calculation method, and thus, a detailed description is omitted here. Wherein the autocorrelation parameter reflects the correlation between the historical current data in the historical current data sequence, and the larger the value is, the larger the correlation between the historical current data in the historical current data sequence is, and thus the stronger the regularity of variation in the historical current data sequence is.
And then obtaining the historical current fluctuation parameter according to the historical current data sequence.
As one example, the historical current volatility parameter is calculated as:
wherein, Representing the variance of all historical current data in a sequence of historical current data, a larger value indicating that the historical current data varies more significantly,/>Representing the average of all the historical current data in the sequence of historical current data. /(I)Representing historical current volatility parameters.
Finally, obtaining a historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter.
As an example, the calculation formula of the historical current regularity index is:
wherein, Representing historical current periodicity parameter,/>Representing historical current autocorrelation parameters,/>Representing historical current volatility parameters,/>Representing a logarithmic function based on natural constants,/>Indicating historical current regularity index. The historical current regularity index is a description of the data change rule of the historical current data sequence.
And similarly, obtaining the historical voltage regularity index according to the historical voltage data sequence.
S202, obtaining a historical relevance index according to the historical current data sequence and the historical voltage data sequence.
Zinc oxide elements are often used in lightning arresters, and these elements are subject to discharge under overvoltage conditions. Aging can cause changes in the physical and chemical properties of the zinc oxide element, such as disruption of the crystal structure, changes in chemical composition, and in turn, increases in resistance, which can be reflected in the ratio of voltage to current. While the ageing of the arrester is generally a gradual process, i.e. the change in resistance should be gradual, not abrupt. And the ratio of voltage to current is suddenly changed due to abnormality caused by improper test environment and manual operation. Thus, as a comparison object, it is also necessary to analyze the variation of the ratio of the historical voltage data and the historical current data.
As one example, the historical relevance index calculation formula is:
wherein, Representing the nth historical voltage data in the sequence of historical voltage data,/>Representing the nth historical current data in the sequence of historical current data,/>Represents the n-1 th historical voltage data in the historical voltage data sequence,/>Represents the n-1 th historical current data in the historical current data sequence. N represents the number of historical current data in the historical current data sequence and also represents the number of historical voltage data in the historical voltage data sequence. /(I)The resistance at the nth history time is reflected,The resistance at the n-1 th historic moment is reflected. By/>Reflecting the resistance fluctuations at all historic times. /(I)Representing the historical relevance index.
S3, obtaining a current regularity index, a current voltage regularity index and a current relevance index according to the current data sequence and the current voltage data sequence, and obtaining a current reliability index and a voltage reliability index according to the current regularity index, the current voltage regularity index, the current relevance index, the historical current regularity index, the historical voltage regularity index and the historical relevance index.
S301, obtaining a current regularity index, a current voltage regularity index and a current relevance index according to a current data sequence and a current voltage data sequence.
And analyzing the current data sequence according to the historical current regularity index acquisition method to obtain the current regularity index. And similarly, obtaining the current voltage regularity index according to the current voltage data sequence.
And analyzing the current data sequence and the current voltage data sequence according to a historical relevance index acquisition method to obtain a current relevance index.
S302, obtaining a current reliability index and a voltage reliability index according to the current regularity index, the current voltage regularity index, the current relevance index, the historical current regularity index, the historical voltage regularity index and the historical relevance index.
As an example, the calculation formula of the current reliability index is:
wherein, The current regulation index is represented, and the larger the value is, the more obvious the current regulation is, so that no abnormal data damage regulation exists in the current data sequence, and the reliability of the current data is higher. /(I)Index of historical current regularity,/>Representing historical relevance index,/>The larger the value is, the larger the resistance change at the current moment is, and the possible abnormal data in the current data is indicated, so that the ratio change of the current voltage data and the current data is larger, and the reliability of the current data is smaller. /(I)A linear normalization process is represented. /(I)Indicating a current reliability indicator.
And obtaining the voltage reliability index by the same method.
S4, carrying out abnormality judgment according to the current reliability index and the voltage reliability index, and carrying out storage processing according to an abnormality judgment result.
It should be noted that, the current data is time stamped, and each current data is collected by sharing time to the verifier through the time system.
It should be further noted that, when the lightning arrester aging test device collects current data, the device state is preset. And displaying the corresponding equipment state under each piece of current data acquired simultaneously.
And acquiring the time stamp of each piece of current data, sharing the current data with the time stamp to a verifier, and verifying the current data by the verifier according to the sharing time and the time stamp of each piece of current data to obtain a time stamp verification result of each piece of current data. When the time stamp verification result is wrong, a tampered alarm is sent out, and all current data are deleted. And thus no storage of the present current data is required.
And acquiring a preset device state and the device state of each piece of current data. And recording the preset equipment states of the current data as target preset equipment states, comparing the equipment states of each current data with the target preset equipment states, and when the equipment states are different from the target preset equipment states, indicating that the current data acquired in other preset equipment states are misplaced in the current data sequence in the target preset equipment states. And storing the current data into a current data sequence in a preset equipment state corresponding to the equipment state, deleting the current data from the current data sequence, sequentially moving the current data in the back forward, and supplementing the upper free data position to obtain the processed current data sequence. Comparing the equipment state of each current data with the target preset equipment state, and when the equipment state is the same as the target preset equipment state, indicating that the problem of misplacement of all current data in the current data sequence does not exist. And recording the current data sequence without the misplaced current data as a misplaced discharge stream data sequence. For convenience of description, the processed current data sequence and the error-free discharge flow data sequence are collectively called as a current data sequence to be analyzed.
Comparing the current reliability index of the current data sequence to be analyzed with a preset reliability threshold, wherein when the current reliability index of the current data sequence to be analyzed is larger than the preset reliability threshold U, no abnormality exists in the current data sequence to be analyzed, and when the current reliability index of the current data sequence to be analyzed is smaller than or equal to the preset reliability threshold U, no abnormality exists in the current data sequence to be analyzed. When the current data sequence to be analyzed is not abnormal, the current data sequence to be analyzed is subjected to coding compression by using a run-length coding algorithm to obtain a coding sequence, and the coding sequence is stored in a block chain of a database. When there is an abnormality in the current data sequence to be analyzed, it cannot be stored in the database.
And similarly, completing the storage analysis of the current voltage data sequence.
In this embodiment, U is taken as 0.75 as an example, and other values may be taken in other embodiments, which is not particularly limited.
The embodiment provides a lightning arrester aging test data storage system, which comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor realizes steps S1 to S4 when executing the computer program.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (8)
1. The lightning arrester aging test data storage method is characterized by comprising the following steps of:
acquiring a historical current data sequence, a historical voltage data sequence, a current data sequence and a current voltage data sequence of the lightning arrester;
analyzing the periodic condition of the historical current data sequence to obtain a historical current periodic parameter; analyzing the related condition of self data in the historical current data sequence to obtain a historical current autocorrelation parameter; analyzing the fluctuation condition of the historical current data sequence to obtain historical current fluctuation parameters; obtaining a historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter; obtaining historical voltage regularity indexes, current regularity indexes and current voltage regularity indexes according to the historical voltage data sequence, the current data sequence and the current voltage data sequence; obtaining a historical relevance index according to the ratio of the historical current data sequence to the position data of the historical voltage data sequence; obtaining a current relevance index according to the current data sequence and the current voltage data sequence;
obtaining a current reliability index according to the current regularity index, the historical relevance index and the current relevance index, and obtaining a voltage reliability index according to the historical voltage regularity index, the current voltage regularity index, the historical relevance index and the current relevance index;
performing exception analysis according to the current reliability index and the voltage reliability index to obtain an exception analysis result, and performing storage processing according to the exception analysis result;
The method comprises the specific steps of obtaining a current reliability index according to a current regularity index, a historical relevance index and a current relevance index, and obtaining a voltage reliability index according to a historical voltage regularity index, a current voltage regularity index, a historical relevance index and a current relevance index, wherein the specific steps are as follows:
wherein, Representing the current regularity index,/>Index of historical current regularity,/>Representing historical relevance index,/>Representing the current relevance index,/>Representing a linear normalization process,/>A current reliability index is represented;
Acquiring a voltage reliability index;
the abnormal analysis is carried out according to the current reliability index and the voltage reliability index to obtain an abnormal analysis result, and the method comprises the following specific steps:
obtaining a current data sequence to be analyzed according to the current data sequence;
Comparing the current reliability index of the current data sequence to be analyzed with a preset reliability threshold, wherein when the current reliability index of the current data sequence to be analyzed is larger than the preset reliability threshold U, no abnormality exists in the current data sequence to be analyzed, and when the current reliability index of the current data sequence to be analyzed is smaller than or equal to the preset reliability threshold U, no abnormality exists in the current data sequence to be analyzed;
and obtaining an abnormal analysis result of the voltage according to the voltage reliability index.
2. The lightning arrester aging test data storage method according to claim 1, wherein the analyzing the periodic condition of the historical current data sequence to obtain the historical current periodic parameter comprises the following specific steps:
performing Fourier transform on the historical current data sequence to obtain frequency spectrum data, acquiring the amplitude corresponding to each frequency in the frequency spectrum data, and acquiring the maximum whole amplitude from the amplitudes of all frequencies, and recording the maximum amplitude as the periodic parameter of the historical current.
3. The method for storing aging test data of lightning arrester according to claim 1, wherein the analyzing the correlation condition of self data in the historical current data sequence to obtain the historical current autocorrelation parameter comprises the following specific steps:
wherein, Representing the nth historical current data in the sequence of historical current data,/>Representing the average of all historical current data in a sequence of historical current data,/>Representing the n+k-th historical current data in the historical current data sequence,/>Represents the N-k historical current data in the historical current data sequence, N represents the number of the historical current data in the historical current data sequence,/>Representing historical current autocorrelation parameters,/>Representing a function taking the maximum value.
4. The lightning arrester aging test data storage method according to claim 1, wherein the analysis of the fluctuation condition of the historical current data sequence to obtain the historical current fluctuation parameter comprises the following specific steps:
And acquiring variances and average values of all the historical current data in the historical current data sequence, and acquiring historical current fluctuation parameters according to the variances and average values of the historical current data, wherein the historical current fluctuation parameters are positively correlated with the variances and positively correlated with the average values.
5. The method for storing aging test data of lightning arrester according to claim 1, wherein the step of obtaining the historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter comprises the following specific steps:
And obtaining a historical current regularity index according to the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current volatility parameter, wherein the historical current periodicity parameter, the historical current autocorrelation parameter and the historical current regularity index are positively correlated, and the historical current volatility parameter and the historical current regularity index are negatively correlated.
6. The lightning arrester aging test data storage method according to claim 1, wherein the historical relevance index is obtained according to the ratio of the historical current data sequence to the position data of the historical voltage data sequence; the current relevance index is obtained according to the current data sequence and the current voltage data sequence, and the method comprises the following specific steps:
Recording the ratio of each historical voltage data in the historical voltage data sequence to the historical current data at the same position in the historical current data sequence as a first ratio; recording the difference value of each first ratio and the previous first ratio as fluctuation degree, and taking the average value of all fluctuation degrees as a historical relevance index;
and obtaining a current relevance index according to the current data sequence and the current voltage data sequence.
7. The lightning arrester aging test data storage method according to claim 1, wherein the storing process according to the result of the anomaly analysis comprises the specific steps of:
when the current data sequence to be analyzed is abnormal, the current data sequence to be analyzed is coded and compressed by using a run-length coding algorithm to obtain a coding sequence, the coding sequence is stored in a block chain of a database, and when the current data sequence to be analyzed is abnormal, the current data sequence to be analyzed cannot be stored in the database;
And carrying out storage processing according to the abnormal analysis result of the voltage.
8. A lightning arrester ageing test data storage system comprising a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor, when executing the computer program, carries out the steps of a lightning arrester ageing test data storage method according to any of claims 1-7.
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