CN110058096B - Multi-factor aging experiment method, system and device based on regional characteristics - Google Patents
Multi-factor aging experiment method, system and device based on regional characteristics Download PDFInfo
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Abstract
The invention provides a multi-factor aging experiment method based on regional characteristics, which is characterized in that a weather mode of a target region is determined by acquiring meteorological data of the target region, and different multi-factor aging experiment parameters are applied according to weather mode conditions of different target regions, so that a regional composite insulator aging result is obtained. The invention also provides a system and a device for the multi-factor aging experiment based on the regional characteristics. The method is used for carrying out the multi-factor aging experiment on the composite insulator based on regional characteristics, is simple to operate and strong in pertinence, provides more accurate results for identifying the operation years of the composite insulator in different regions, and provides certain help for prolonging the service life of the composite insulator in each region.
Description
Technical Field
The invention relates to the field of high-voltage external insulation, in particular to a multi-factor aging experiment method based on regional characteristics, a multi-factor aging experiment system based on regional characteristics and a multi-factor aging experiment device based on regional characteristics, which are used for performing multi-factor aging experiments on composite insulators based on regional characteristics.
Background
The composite insulator is one of the widely used devices in a power transmission system, plays an important role in electrical insulation and mechanical support, and the quality of the operation condition of the composite insulator is directly related to the stability and safety of the power transmission system. At present, more than 800 million composite insulators in an electric power system are in live-line operation and account for 55 percent of the total use amount of the insulators. However, as the operation period increases, the aging problem becomes more serious, and the normal operation of the composite insulator is influenced.
A great deal of research is carried out at home and abroad on the long-term aging problem of the composite insulator. Among these studies, the aging of the composite insulator is mostly concentrated on the one-factor aging, and the study of the multi-factor aging is relatively lacking. A5000 h multi-factor aging test method is proposed for the first time in IEC 61109: 1992. Many organizations have also attempted to propose different 5000h multifactorial test methods. For example, ENEL 5000h multifactor assay, EPRL 5000h multifactor assay, FGH 5000h multifactor assay. But IEC aging tests do not take into account the recovery and loss of hydrophobicity of the composite insulator. Salt fog is too heavy in an ENEL aging test, and no soluble salt exists. EPRLs are designed for the united states environment. The salt fog period of the FGH aging test is too long, and the ultraviolet time is short. The environmental parameters in the 5000h multifactor test are different from the environmental parameters of China, and the method cannot be directly used for the composite insulator in the domestic environment. On the other hand, the aging state of the composite insulator in different regions is greatly different due to large difference of environmental parameters in different regions, so that inaccurate results can be caused if the same multi-factor aging test is used in different regions, and thus the aging judgment of the composite insulator is greatly influenced. Therefore, a 5000h multifactor test design method for different regions needs to be provided.
Disclosure of Invention
In view of the above problems, the invention provides a multi-factor aging experimental method, system and device based on regional characteristics, provides an experimental method for composite insulator aging in different regional environments, improves the accuracy of composite insulator aging judgment, and helps to judge the operation age of a composite insulator applied in different regional environments.
The first aspect of the application provides a multi-factor aging experiment method based on regional characteristics, which is used for performing a multi-factor aging experiment on a composite insulator, and the method comprises the following steps:
creating and storing a corresponding relation table of aging factors and weather modes, wherein the weather modes comprise a sunny mode, a cloudy mode and a rainy mode in the corresponding relation table, the aging factors corresponding to the sunny mode comprise heating and ultraviolet rays, the aging factors corresponding to the cloudy mode comprise humidity and salt fog, and the aging factors corresponding to the rainy mode comprise rainfall;
acquiring meteorological data of a target area in each month from one month to twelve months, dividing four seasons of the target area according to the meteorological data of each month, and determining a characteristic month in each season;
acquiring meteorological data of each day in the characteristic month of each season, and determining a weather mode of each day in the characteristic month according to the meteorological data of each day, wherein the weather mode comprises a sunny mode, a cloudy mode and a rainy mode;
counting the distribution condition of each weather mode in the characteristic month according to the weather mode of each day in the characteristic month, and calculating the proportion of the total days of each weather mode in the characteristic month in the total days of all weather modes;
calculating the total hours of all weather patterns in each characteristic month, dividing the total hours of all weather patterns by an aging acceleration factor to obtain the total hours of each characteristic month in a multi-factor aging experiment, then calculating the total hours of each weather pattern in the multi-factor aging experiment according to the proportion of each weather pattern, and carrying out time distribution on each weather pattern in the multi-factor aging experiment according to the distribution condition of each weather pattern;
repeating the weather pattern distribution condition of each seasonal characteristic month in the multi-factor aging experiment for preset times, wherein the value of the preset times is equal to the value of the total number of months in the seasons, and obtaining the annual weather pattern in the multi-factor aging experiment;
and applying the corresponding aging factors according to the corresponding relation between the aging factors and the weather modes and the distribution condition of the weather modes in the multi-factor aging experiment, and carrying out the multi-factor aging test on the composite insulator to be tested.
Preferably, the weather data of each month of the target region includes an average air temperature of each month, the four seasons of the target region are divided according to the average air temperature of each month by using a weather method, and the method for determining the characteristic month of each of the four seasons of the target region includes: the month with the highest temperature is selected as the characteristic part in summer, and the month with the lowest temperature is selected as the characteristic month in spring, autumn and winter.
Preferably, the meteorological data of each month in the target region further includes an average precipitation of each month, and the method for determining the characteristic month in each season further includes: and in each season, selecting the month with the largest average precipitation as the characteristic month when the difference of the average temperature of the months is less than a preset value.
Preferably, the weather data of each day in the characteristic month includes daily precipitation and sunshine hours, the weather pattern of the day is determined according to the daily precipitation and sunshine hours of the day, and the method for determining the weather pattern of the day according to the daily precipitation and sunshine hours of the day includes:
judging whether the daily precipitation of the day is larger than a preset precipitation threshold value;
if the daily rainfall is larger than the rainfall threshold, determining that the weather mode of the day is a rainy day mode;
if the daily rainfall is smaller than the rainfall threshold, further judging whether the sunshine hours of the day are larger than a preset sunshine time threshold;
if the sunshine hours of the day are larger than the sunshine time threshold value, determining that the weather mode of the day is sunny;
and if the sunshine hours of the day are less than the sunshine time threshold value, determining that the weather mode of the day is cloudy.
Preferably, the aging factors in the multi-factor aging experiment include temperature, ultraviolet rays, salt fog, humidity, rainfall and voltage, and the method further comprises the step of setting parameters of the aging factors applied to the tested composite insulator, wherein the temperature parameters in the aging factors are set as: in summer, setting the temperature in a sunny mode to be the highest daily temperature of the target area plus a preset upward floating value, in winter, setting the lowest daily temperature, and setting the rest time to be the highest normal daily temperature; setting the value of ultraviolet rays as the daily maximum radiance of the target area; the salt fog value is the concentration value of the dirt in the target area; the humidity value is the highest humidity value of the target area day; the numerical value of the rainfall is set to be a preset numerical value, and the preset numerical value is a rainfall numerical value capable of flushing dirt on the surface of the insulator; the numerical value of the voltage is the creepage distance ratio of the composite insulator to be tested, wherein the creepage distance ratio of the insulator is the ratio of the creepage distance of the insulator to the root mean square value of the highest running voltage borne on the insulator.
A second aspect of the present application provides a multi-factor aging experiment system based on regional characteristics, the system including:
the device comprises a setting module, a storage module and a display module, wherein the setting module is used for creating and storing a corresponding relation table of aging factors and weather modes, the weather modes comprise a sunny mode, a cloudy mode and a rainy mode in the corresponding relation table, the aging factors corresponding to the sunny mode comprise heating and ultraviolet rays, the aging factors corresponding to the cloudy mode comprise humidity and salt fog, and the aging factors corresponding to the rainy mode comprise rainfall;
the characteristic month determining module is used for acquiring meteorological data of each month from one month to twelve months of a target area, dividing four seasons of the target area according to the meteorological data of each month and determining a characteristic month in each season;
the weather mode determining module is used for acquiring weather data of each day in the characteristic month of each season and determining a weather mode of each day in the characteristic month according to the weather data of each day, wherein the weather mode comprises a sunny mode, a cloudy mode and a rainy mode;
the calculation module is used for counting the distribution condition of each weather mode in the characteristic month according to the weather mode of each day in the characteristic month and calculating the proportion of the total days of each weather mode in the characteristic month in the total days of all weather modes;
the distribution module is used for calculating the total hours of all the weather modes in each characteristic month, dividing the total hours of all the weather modes by an aging acceleration factor to obtain the total hours of each characteristic month in the multi-factor aging experiment, then calculating the total hours of each weather mode in the multi-factor aging experiment according to the proportion of each weather mode, and carrying out time distribution on each weather mode in the multi-factor aging experiment according to the distribution condition of each weather mode;
the all-year weather mode determining module is used for repeating the weather mode distribution condition of each seasonal characteristic month in the multi-factor aging experiment for preset times, wherein the value of the preset times is equal to the value of the total number of months in the seasons, so that the all-year weather mode in the multi-factor aging experiment is obtained; and
and the control module is used for applying the corresponding aging factors according to the corresponding relation between the aging factors and the weather modes and the distribution condition of the weather modes in the multi-factor aging experiment so as to carry out the multi-factor aging test on the composite insulator to be tested.
The third aspect of the present invention provides a multi-factor aging experimental apparatus based on regional characteristics, for performing an aging experiment on a composite insulator, the apparatus comprising: the aging factor applying device is used for applying an aging factor in a multi-factor aging experiment to the composite insulator; a processor; and the memory is stored with a plurality of program modules, and the program modules are loaded by the processor and execute the multi-factor aging experiment method based on the regional characteristics.
The multi-factor aging experiment method based on the regional characteristics sets different multi-factor aging experiment parameters based on different regional characteristics, so that a composite insulator aging result based on the regional characteristics is obtained, the operation is simple, the pertinence is strong, a more accurate structure is provided for identifying the operation age of the composite insulator in the region, and the service life of the composite insulator in each region is prolonged.
Drawings
Fig. 1 is a flowchart of a multi-factor aging test method based on regional characteristics according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a multi-factor aging experiment system based on regional characteristics according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a multi-factor aging experimental apparatus based on regional characteristics according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a detailed description of the present invention will be given below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention, and the described embodiments are merely a subset of the embodiments of the present invention, rather than a complete embodiment. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
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 terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
Referring to fig. 1, a flowchart of a multi-factor aging method based on geographical features according to an embodiment of the present invention is shown. The order of the steps in the flow chart may be changed and some steps may be omitted according to different needs. For convenience of explanation, only portions related to the embodiments of the present invention are shown.
As shown in fig. 1, the multi-factor aging test method for the composite insulator based on the regional characteristics includes the following steps.
Step S1, creating and storing a correspondence table between aging factors and weather patterns, where the weather patterns include, but are not limited to, a sunny pattern, a cloudy pattern, and a rainy pattern, the aging factors corresponding to the sunny pattern are heating and ultraviolet rays, the aging factors corresponding to the cloudy pattern are humidity and salt fog, and the aging factors corresponding to the rainy pattern are rainfall.
In the present embodiment, the aging factors are set to 6 factors of temperature, humidity, ultraviolet rays, dirt, rainfall, and electricity, with reference to the 5000-hour multifactor aging test method in IEC 61109: 1992.
Step S2, acquiring meteorological data of each month from one month to twelve months of the target area, dividing four seasons of the target area according to the meteorological data of each month, and determining the characteristic month in each season.
The target region is a region where a composite insulator to be tested is installed, for example, when the composite insulator to be tested is used in Hainan province, the target region may select a city of Hainan province, such as Haikou city of Hainan province. It should be noted that the target area may be any area where a composite insulator is used.
The meteorological data of each month in the target area comprise the average air temperature and the average precipitation of each month. In an embodiment of the present invention, the weather data of each month in the target area is average weather data of each month in the year. In other embodiments, the weather data of each month in the target area may also be average weather data of each month in a certain year.
In the present embodiment, the four seasons of the target region are divided by the monthly average air temperature of each month by the climate method. In the waiting method, the average temperature (one in every five days) is less than 10 ℃ in winter, the average temperature is greater than 22 ℃ in summer, and the average temperature is between 10 ℃ and 22 ℃ in spring and autumn respectively. The climate average temperature is a weighted average of daily average temperatures for 5 consecutive days, and is an important index for dividing four seasons in the climate method.
In this embodiment, the method for determining the characteristic month of each of the four seasons of the target area includes: the month with the highest temperature is selected as the characteristic part in summer, and the month with the lowest temperature is selected as the characteristic month in spring, autumn and winter.
Further, the method for determining the characteristic month in each season further comprises the following steps: in each season, when the difference of the average temperature of the months is less than a preset value (for example, 0.5 ℃), the month with the largest average precipitation is selected as the characteristic month.
For example, taking Haikou City of Hainan province as an example, the following table 1 shows the average temperature and the average precipitation in each month of the years in Hainan Haikou City. According to the average air temperature of each month in the following table, the seasonal division of the Haikou market can be obtained by the temperature waiting method: the summer is 4-11 months, and the spring and autumn are 12-3 months. In summer, the months with the highest temperature and the difference of the average air temperature less than the preset value (0.5 ℃) are 6 and 7 months, wherein the precipitation of the 6 months is greater than that of the 7 months, and then the 6 months are determined as the characteristic months in summer. In spring and autumn, if the temperature of 1 month is the lowest, the 1 month is determined as the characteristic month of spring and autumn.
| Moon cake | Rainfall of each month of the year (0.1mm) | Average temperature of each month of the year (0.1 deg.C) |
| 1 | 195 | 177 |
| 2 | 350 | 187 |
| 3 | 506 | 218 |
| 4 | 1002 | 252 |
| 5 | 1814 | 274 |
| 6 | 2270 | 285 |
| 7 | 2181 | 286 |
| 8 | 2356 | 281 |
| 9 | 2441 | 272 |
| 10 | 2244 | 253 |
| 11 | 813 | 223 |
| 12 | 349 | 190 |
TABLE 1
In this embodiment, the weather data of each month in the target area may be acquired from a chinese weather data network, a chinese international exchange station ground climate standard value month data set, a NASA official network of the national aeronautics and astronautics authority of the united states, and the like.
Step S3, acquiring meteorological data of each day in the characteristic month of each season, and determining a weather mode of each day in the characteristic month according to the meteorological data of each day, wherein the weather mode comprises a sunny mode, a cloudy mode and a rainy mode.
In the first embodiment of the present invention, the weather data of each day in the characteristic month includes daily precipitation and sunshine hours, and the weather pattern of the day is determined according to the daily precipitation and sunshine hours of the day.
Specifically, the method for determining the weather pattern of the day according to the daily precipitation and the sunshine hours of the day comprises the following steps:
1) judging whether the daily precipitation of the day is larger than a preset precipitation threshold (for example, 15 millimeters);
2) if the daily rainfall is larger than the rainfall threshold, determining that the weather mode of the day is a rainy day mode;
wherein, the effect of rain washing pollution on the composite insulator exceeds the effect of ultraviolet on the composite insulator, so when the daily rainfall is more than 15 mm, the rainy day mode is taken as the main mode;
3) if the daily rainfall is smaller than the rainfall threshold, further judging whether the sunshine hours on the day are larger than a preset sunshine time threshold (for example, 6 hours);
if the sunshine hours of the day are larger than the sunshine time threshold value, determining that the weather mode of the day is sunny;
and if the sunshine hours of the day are less than the sunshine time threshold value, determining that the weather mode of the day is cloudy.
For example, in the case where the precipitation threshold value is 15 mm and the sunshine duration threshold value is 6 hours, a method of determining the weather pattern of the day according to the daily precipitation and the sunshine hours of the day can be represented by the following table 2.
TABLE 2
Further, the method further comprises: and judging whether the weather data of each day exceeds a preset normal range, if so, determining that the weather data of the day is wrong, removing the weather data of the day, not judging the weather mode, and if not, judging the weather mode of the day. Wherein the preset normal range may be preset and stored in a preset storage location. For example, the normal range of the weather data may be that the daily precipitation is 0-3000 mm, and if the daily precipitation exceeds 3000 mm, it is determined that the weather data of the day is incorrect, and the weather mode is not determined.
In an embodiment of the present invention, the daily precipitation and the sunshine hours may be meteorological data of the characteristic month in a certain year, for example, meteorological data of each day in 6 months of 2018. In other embodiments of the present invention, the daily precipitation and the number of sunshine hours may be an average of the weather data of each day of the characteristic month in a plurality of historical years, for example, an average of the weather data of each day of 6 months in the past 10 years.
The invention will now be illustrated by way of example in Haikou City, Hainan province. As described above, the 6 months in the summer season of the haikou city are characteristic months, and the weather data (including the daily precipitation and the number of sunshine hours) for each day in the 6 months and the weather pattern determined based on the weather data for each day in the 6 months are shown in the following table 3, in which "1" represents a sunny day, "2" represents a cloudy day, "3" represents a rainy day, and "/" represents that the weather data is erroneous. For example, in the weather data of day 1/6, the daily rainfall is 3.3 mm, the sunshine hours is 9.3 hours, and according to the determination rule in table 2, if the daily rainfall is less than the rainfall threshold value by 15 mm and the sunshine hours is greater than 6 hours, it is determined that day 1/6 is a clear day. And in the meteorological data of 22 days in 6 months, the daily rainfall is 22.7 millimeters and is larger than the daily rainfall threshold value by 15 millimeters, the weather mode of each day in 6 months and 22 days is determined, and the like, the weather mode of each day in 6 months is determined. And for the weather data of the two days of 19 days in 6 months and 28 days in 6 months, because the daily precipitation is 3270 mm which exceeds the preset normal range by 3000 mm, the weather data of the two days are recorded as wrong, and the weather mode is not determined.
TABLE 3
Similarly, the weather pattern of each day in the spring and autumn section of Haikou city in the characteristic month 1 month can be obtained according to the method.
It is to be understood that, in other embodiments of the present invention, the acquired weather data of each day in each seasonal feature month may also directly include weather forecast conditions of each day, for example, when the weather in the weather forecast acquired from the weather website is clear, the weather mode is determined as a clear day mode; when the weather in the weather forecast is cloudy, determining that the weather mode is a cloudy mode; and when the weather in the weather forecast is rain and snow, determining that the weather mode is a rainy day mode.
Step S4, counting the distribution situation of each weather pattern in the characteristic month according to the weather pattern of each day in the characteristic month, and calculating the proportion of the total days of each weather pattern in the total days of all weather patterns.
Specifically, the total number of days of each weather pattern in the characteristic month is calculated, and then the total number of days of each weather pattern is divided by the total number of days of all weather patterns in the characteristic month, so that the occupation ratio of each weather pattern in the whole characteristic month is calculated. Wherein the days determined to be incorrect are deducted during the calculation, since the weather data for several days in the characteristic month may be determined to be incorrect because of being out of the normal range.
For example, continuing with the weather data for the 6 th month of Haikou City as described above, there are a total of 30 days in the 6 th month, wherein the number of days for which it is determined that precipitation is recorded as being incorrect is 2 days, and the 2 days for which incorrect data is deducted, so that the total number of days for all weather patterns is 28 days. Wherein the total days of the sunny mode is 25 days, namely the proportion of the sunny mode is 25/28; the total days of the cloudy mode is 2 days, namely the cloudy mode proportion is 2/28; the total number of days in the rainy day mode is 1 day, i.e., the rainy day mode ratio is 1/28. Similarly, the proportion of each weather pattern in the characteristic month 1 of spring and autumn can be calculated.
Step S5, calculating the total hours of all weather patterns in each characteristic month, dividing the total hours of all weather patterns by an aging acceleration factor to obtain the total hours of each characteristic month in the multi-factor aging experiment, then calculating the total hours of each weather pattern in the multi-factor aging experiment according to the proportion of each weather pattern, and distributing time for each weather pattern in the multi-factor aging experiment according to the distribution condition of each weather pattern.
The value of the aging acceleration factor may be set according to experimental needs, which is not specifically limited in the present invention. In the present embodiment, the value of the aging acceleration factor is 16. In other embodiments of the present invention, the aging acceleration factor may have other values.
Continuing with the example of the aforementioned haikou city, in the present embodiment, the total number of days of all the weather patterns in the characteristic month of summer 6 months is 28 days, and then the total number of hours of all the weather patterns is 28 × 24 — 672 (hours), and then the total number of hours 672 of all the weather patterns is divided by the aging acceleration factor 16 to obtain the total number of hours of the characteristic month in summer in the multi-factor aging experiment, which is 42 hours, wherein in the 42 hours, the proportion of the fine day pattern is 25/28, the total number of hours of the fine day pattern in the multi-factor aging experiment is 37.5 hours, and similarly, the cloudy day pattern is 3 hours, and the rainy day is 1.5 hours. Referring to the distribution of each weather pattern in month 6, the result of assigning each weather pattern can be simplified as follows: after 37.5h of sunny days, 1.5h of cloudy days are experienced, and then after 1.5h of rainy days, 1.5h of cloudy days are experienced.
And step S6, repeating the weather pattern distribution condition of each seasonal characteristic month in the multi-factor aging experiment for a preset number of times, wherein the value of the preset number of times is equal to the value of the total number of months in the seasons, so as to obtain the annual weather pattern in the multi-factor aging experiment.
For example, as described above, if the total number of summer months in the haikou city is 9 months, and the total number of spring and autumn months is 3 months, the allocation of the weather pattern in the characteristic summer month of 6 months is repeated 9 times, that is, the weather pattern in the characteristic summer month of 1.5 hours is repeated 9 times after going through a sunny day of 37.5 hours and then going through a cloudy day of 1.5 hours after going through a rainy day of 1.5 hours, and similarly, the allocation of the weather pattern in the characteristic summer month of 1 month and autumn is repeated 3 times, so that the allocation of the weather pattern in the multi-factor aging test for the whole year is obtained.
And S7, applying corresponding aging factors according to the corresponding relation between the aging factors and the weather modes and the distribution conditions of the weather modes in the multi-factor aging experiment, and carrying out multi-factor aging test on the composite insulator to be tested.
Continuing with the example of the haikou city as described above, applying the corresponding aging factor to the composite insulator to be tested according to the distribution condition of each weather pattern in the multi-factor aging test determined in step S5, for example, the aging factor corresponding to month 6 may be applied according to the following table 4: the aging factors corresponding to the sunny mode are heating and ultraviolet rays, the duration time is 37.5 hours, and then the heating device and the ultraviolet ray applying device are started for 37.5 hours in a multi-factor aging experiment to simulate the environment state of the composite insulator in sunny days; and then starting the salt spray application device corresponding to the salt spray as the aging factor corresponding to the cloudy mode for 1.5 hours to simulate the environmental state of the composite insulator in the cloudy time, then starting the rainfall application device corresponding to the rainfall as the aging factor corresponding to the rainy mode for 1.5 hours to simulate the environmental state of the composite insulator in the rainy time, and finally starting the salt spray application device corresponding to the salt spray as the aging factor corresponding to the cloudy mode for 1.5 hours to simulate the environmental state of the composite insulator in the cloudy time. In the present embodiment, the aging factors are set to 6 factors of temperature, humidity, ultraviolet rays, dirt, rainfall, and voltage, with reference to the 5000-hour multifactor aging test method in IEC 61109: 1992. Wherein the voltage and humidity are applied continuously throughout the experiment, for example, 6 months for an aging experiment where the voltage and humidity are applied for 42 hours. In the following table "- -" means no aging factor was applied.
TABLE 4
In this embodiment, before step S7, the method further includes a step of setting parameters of an aging factor applied to the composite insulator under test, wherein the temperature parameters of the aging factor are set as: in summer, the temperature in the sunny mode is set to be the highest daily temperature plus a preset floating value (for example, the preset floating value is 11 ℃), in winter, the lowest daily temperature is set, and the rest time is the highest normal daily temperature. Setting the value of ultraviolet rays as the daily maximum radiance of a target area; the salt fog value is the concentration value of the filth in the target area. And the humidity value is the highest humidity value of the target area day. The numerical value of rainfall sets up to predetermined numerical value, predetermined numerical value is the rainfall numerical value that can wash insulator surface filth, reach the washing effect. The numerical value of the voltage is the creepage distance ratio of the composite insulator to be tested, wherein the creepage distance ratio of the insulator is the ratio of the creepage distance of the insulator to the root mean square value of the highest running voltage borne on the insulator. The data of the highest daily temperature, the lowest daily temperature, the highest daily radiance, the pollution condition, the highest daily humidity and the like of the target area can be obtained from a meteorological department database of the target area or can be obtained through measurement. The setting rule of the specific parameters can refer to the following table 5:
TABLE 5
The multi-factor aging experiment method based on the regional characteristics sets different multi-factor aging experiment parameters based on different regional characteristics, so that a composite insulator aging result based on the regional characteristics is obtained, the operation is simple, the pertinence is strong, a more accurate structure is provided for identifying the operation age of the composite insulator in the region, and certain help is provided for prolonging the service life of the composite insulator in each region.
Fig. 2 is a structural diagram of a multi-factor aging experiment system based on regional characteristics according to an embodiment of the present invention.
In some embodiments, the system 200 may include a plurality of functional modules composed of program code segments. The program codes of the program segments in the multi-factor aging experiment system 200 based on the regional characteristics may be stored in a memory of the computer device and executed by at least one processor in the computer device to implement the multi-factor aging experiment function of the composite insulator based on the regional characteristics.
Referring to fig. 2, in the present embodiment, the multi-factor aging experiment system 200 based on the regional characteristics may be divided into a plurality of functional modules according to the functions performed by the system, where each functional module is configured to perform each step in the corresponding embodiment of fig. 1, so as to implement the multi-factor aging experiment function of the composite insulator based on the regional characteristics. In this embodiment, the functional modules of the multi-factor aging experiment system 200 based on the geographic characteristics include: a setting module 201, a characteristic month determination module 202, a weather mode determination module 203, a calculation module 204, an allocation module 205, a year round weather mode determination module 206, and a control module 207. The functions of the respective functional blocks will be described in detail in the following embodiments.
The setting module 201 is configured to, in step S1, create and store a correspondence table between aging factors and weather patterns, where the weather patterns include, but are not limited to, a sunny pattern, a cloudy pattern, and a rainy pattern in the correspondence table, the aging factors corresponding to the sunny pattern are heating and ultraviolet light, the aging factors corresponding to the cloudy pattern are humidity and salt fog, and the aging factors corresponding to the rainy pattern are rainfall.
The characteristic month determination module 202 is configured to obtain meteorological data of each month from one month to twelve months in a target area, divide four seasons of the target area according to the meteorological data of each month, and determine a characteristic month in each season.
The target region is a region where a composite insulator to be tested is installed, for example, when the composite insulator to be tested is used in Hainan province, the target region may select a city of Hainan province, such as Haikou city of Hainan province. It should be noted that the target area may be any area where a composite insulator is used.
The meteorological data of each month in the target area comprise the average air temperature and the average precipitation of each month. In an embodiment of the present invention, the weather data of each month in the target area is average weather data of each month in the year. In other embodiments, the weather data of each month in the target area may also be average weather data of each month in a certain year.
In the present embodiment, the four seasons of the target region are divided by the monthly average air temperature of each month by the climate method. In the waiting method, the average temperature (one in every five days) is less than 10 ℃ in winter, the average temperature is greater than 22 ℃ in summer, and the average temperature is between 10 ℃ and 22 ℃ in spring and autumn respectively. The climate average temperature is a weighted average of daily average temperatures for 5 consecutive days, and is an important index for dividing four seasons in the climate method.
In this embodiment, the method for determining the characteristic month of each of the four seasons of the target region by the characteristic month determination module 202 is as follows: the month with the highest temperature is selected as the characteristic part in summer, and the month with the lowest temperature is selected as the characteristic month in spring, autumn and winter.
Further, the method for determining the characteristic month in each season by the characteristic month determination module 202 further includes: in each season, when the difference of the average temperature of the months is less than a preset value (for example, 0.5 ℃), the month with the largest average precipitation is selected as the characteristic month.
For example, taking Haikou City in Hainan province as an example, after the average temperature in each month of the years of the Haikou City in Hainan province is obtained, determining that the average temperature is more than 22 ℃ in 4-11 months, and then determining that 4-11 months are summer; determining the average air temperature between 10 ℃ and 22 ℃ in 12-3 months, and determining spring and autumn of Haikou city to be 12-3 months. And in summer, the months with the highest temperature and the difference of the average air temperature less than the preset value (0.5 ℃) are 6 months and 7 months, wherein the precipitation of the 6 months is greater than that of the 7 months, and then the 6 months are determined as the characteristic months in summer. In spring and autumn, if the temperature of 1 month is the lowest, the 1 month is determined as the characteristic month of spring and autumn.
In this embodiment, the weather data of each month in the target area may be acquired from a chinese weather data network, a chinese international exchange station ground climate standard value month data set, a NASA official network of the national aeronautics and astronautics authority of the united states, and the like.
The weather mode determining module 203 is configured to obtain weather data of each day in the characteristic month of each season, and determine a weather mode of each day in the characteristic month according to the weather data of each day, where the weather mode includes a sunny mode, a cloudy mode, and a rainy mode.
In the first embodiment of the present invention, the weather data of each day in the characteristic month includes daily precipitation and sunshine hours, and the weather pattern of the day is determined according to the daily precipitation and sunshine hours of the day.
Specifically, the weather mode determining module 203 determines the weather mode of the day according to the daily precipitation and the sunshine hours of the day, including:
1) judging whether the daily precipitation of the day is larger than a preset precipitation threshold (for example, 15 millimeters);
2) if the daily rainfall is larger than the rainfall threshold, determining that the weather mode of the day is a rainy day mode;
wherein, the effect of rain washing pollution on the composite insulator exceeds the effect of ultraviolet on the composite insulator, so when the daily rainfall is more than 15 mm, the rainy day mode is taken as the main mode;
3) if the daily rainfall is smaller than the rainfall threshold, further judging whether the sunshine hours on the day are larger than a preset sunshine time threshold (for example, 6 hours);
if the sunshine hours of the day are larger than the sunshine time threshold value, determining that the weather mode of the day is sunny;
and if the sunshine hours of the day are less than the sunshine time threshold value, determining that the weather mode of the day is cloudy.
For example, in the case where the precipitation threshold value is 15 mm and the sunshine duration threshold value is 6 hours, a method of determining the weather pattern of the day according to the daily precipitation and the sunshine hours of the day can be represented by the following table.
Further, the weather pattern determination module 203 is further configured to: and judging whether the weather data of each day exceeds a preset normal range, if so, determining that the weather data of the day is wrong, removing the weather data of the day, not judging the weather mode, and if not, judging the weather mode of the day. Wherein the preset normal range may be preset and stored in a preset storage location. For example, the normal range of the weather data may be that the daily precipitation is 0-3000 mm, and if the daily precipitation exceeds 3000 mm, it is determined that the weather data of the day is incorrect, and the weather mode is not determined.
In an embodiment of the present invention, the daily precipitation and the sunshine hours may be meteorological data of the characteristic month in a certain year, for example, meteorological data of each day in 6 months of 2018. In other embodiments of the present invention, the daily precipitation and the number of sunshine hours may be an average of the weather data of each day of the characteristic month in a plurality of historical years, for example, an average of the weather data of each day of 6 months in the past 10 years.
It is to be understood that, in other embodiments of the present invention, the acquired weather data of each day in each seasonal feature month may also directly include weather forecast conditions of each day, for example, when the weather in the weather forecast acquired from the weather website is clear, the weather mode is determined as a clear day mode; when the weather in the weather forecast is cloudy, determining that the weather mode is a cloudy mode; and when the weather in the weather forecast is rain and snow, determining that the weather mode is a rainy day mode.
The calculating module 204 is configured to count a distribution of each weather pattern in the feature month according to the weather pattern of each day in the feature month, and calculate a ratio of the total number of days of each weather pattern to the total number of days of all weather patterns.
Specifically, the calculating module 204 calculates the total number of days of each weather pattern in the characteristic month, and then divides the total number of days of each weather pattern by the total number of days of all weather patterns in the characteristic month, so as to calculate the occupation ratio of each weather pattern in the whole characteristic month. Wherein the days determined to be incorrect are deducted during the calculation, since the weather data for several days in the characteristic month may be determined to be incorrect because of being out of the normal range.
For example, taking the meteorological data for 6 months in Haikou City as an example, there are 30 total days in 6 months, wherein the number of days for which it is determined that precipitation is recorded wrongly is 2 days, and the 2 days with wrong data are deducted, so that the total number of days for all weather patterns is 28 days. Wherein the total days of the sunny mode is 25 days, namely the proportion of the sunny mode is 25/28; the total days of the cloudy mode is 2 days, namely the cloudy mode proportion is 2/28; the total number of days in the rainy day mode is 1 day, i.e., the rainy day mode ratio is 1/28. Similarly, the proportion of each weather pattern in the characteristic month 1 of spring and autumn can be calculated.
The experiment time allocation module 205 is configured to calculate the total hours of all the weather patterns in each feature month, divide the total hours of all the weather patterns by the aging acceleration factor to obtain the total hours of each feature month in the multi-factor aging experiment, then calculate the total hours of each weather pattern in the multi-factor aging experiment according to the duty ratio of each weather pattern, and perform time allocation on each weather pattern in the multi-factor aging experiment according to the distribution of each weather pattern.
The value of the aging acceleration factor may be set according to experimental needs, which is not specifically limited in the present invention. In the present embodiment, the value of the aging acceleration factor is 16. In other embodiments of the present invention, the aging acceleration factor may have other values.
Continuing with the example of the aforementioned haikou city, in the present embodiment, the total number of days of all the weather patterns in the characteristic month of summer 6 months is 28 days, and then the total number of hours of all the weather patterns is 28 × 24 — 672 (hours), and then the total number of hours 672 of all the weather patterns is divided by the aging acceleration factor 16 to obtain the total number of hours of the characteristic month in summer in the multi-factor aging experiment, which is 42 hours, wherein in the 42 hours, the proportion of the fine day pattern is 25/28, the total number of hours of the fine day pattern in the multi-factor aging experiment is 37.5 hours, and similarly, the cloudy day pattern is 3 hours, and the rainy day is 1.5 hours. Referring to the distribution of each weather pattern in month 6, the result of assigning each weather pattern can be simplified as follows: after 37.5h of sunny days, 1.5h of cloudy days are experienced, and then after 1.5h of rainy days, 1.5h of cloudy days are experienced.
The all-year weather pattern determining module 206 is configured to repeat the weather pattern allocation condition of each seasonal characteristic month in the multi-factor aging experiment for a preset number of times, where a value of the preset number of times is equal to a value of a total number of months in the season, so as to obtain an all-year weather pattern in the multi-factor aging experiment.
For example, if the total number of summer months in Haikou city is 9 months and the total number of spring and autumn months is 3 months, the weather pattern allocation situation of the characteristic month in summer of 6 months is repeated 9 times, and similarly, the weather pattern allocation situation of the characteristic month in spring and autumn of 1 month is repeated 3 times, so that the weather pattern allocation situation of a whole year in the multi-factor aging experiment is obtained.
The control module 207 is configured to control the aging factor applying device to apply the corresponding aging factor to the composite insulator to be tested according to the corresponding relationship between the aging factor and the weather pattern and according to the distribution condition of the weather pattern in the multi-factor aging test, and perform the multi-factor aging test on the composite insulator to be tested.
In this embodiment, the control module 207 is further configured to perform parameter setting on an aging factor applied to the composite insulator under test, where a temperature parameter of the aging factor is set as: in summer, the temperature in the sunny mode is set to be the highest daily temperature plus a preset floating value (for example, the preset floating value is 11 ℃), in winter, the lowest daily temperature is set, and the rest time is the highest normal daily temperature. Setting the value of ultraviolet rays as the daily maximum radiance of a target area; the salt fog value is the concentration value of the filth in the target area. And the humidity value is the highest humidity value of the target area day. The numerical value of rainfall sets up to predetermined numerical value, predetermined numerical value is the rainfall numerical value that can wash insulator surface filth, reach the washing effect. The numerical value of the voltage is the creepage distance ratio of the composite insulator to be tested, wherein the creepage distance ratio of the insulator is the ratio of the creepage distance of the insulator to the root mean square value of the highest running voltage borne on the insulator. The data of the highest daily temperature, the lowest daily temperature, the highest daily radiance, the pollution condition, the highest daily humidity and the like of the target area can be obtained from a meteorological department database of the target area or can be obtained through measurement.
Fig. 3 is a functional module diagram of a multi-factor aging testing apparatus based on regional characteristics according to an embodiment of the present invention. The multi-factor aging experimental device 10 based on geographic characteristics at least comprises an aging factor applying device 11, a memory 12, a processor 13 and a computer program 14 stored in the memory 12 and operable on the processor 13, such as a multi-factor aging experimental program based on geographic characteristics. The processor 13 executes the computer program 14 to implement the steps of the multi-factor aging experiment method based on regional characteristics in the above method embodiment. Alternatively, the processor 13 executes the computer program 14 to implement the functions of the modules/units in the above system embodiments, such as the module 201 and 204 in fig. 2.
Illustratively, the computer program 14 may be partitioned into one or more modules/units that are stored in the memory 12 and executed by the processor 13 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 14 in the multi-factor aging experimental apparatus 10 based on regional characteristics. For example, the computer program 14 may be partitioned into modules 201 and 207 in FIG. 2.
It will be understood by those skilled in the art that the schematic diagram 3 is merely an example of the multi-factor aging experimental apparatus 10 based on geographic characteristics, and does not constitute a limitation to the multi-factor aging experimental apparatus 10 based on geographic characteristics, and the multi-factor aging experimental apparatus 10 based on geographic characteristics may include more or less components than those shown in the drawings, or combine some components, or different components, for example, the multi-factor aging experimental apparatus 10 based on geographic characteristics may further include input and output devices, and the like.
The aging factor applying device 11 is used for applying an aging factor in a multi-factor aging experiment to the composite insulator to be tested under the control of the processor 13. Specifically, the aging factor applying means may include, but is not limited to: a temperature applying device for applying temperature, an ultraviolet ray applying device for applying ultraviolet rays, a salt fog applying device for applying salt fog, a humidity applying device for applying humidity, an artificial rainfall applying device for applying rainfall, and a voltage applying device for applying voltage.
The Processor 13 may be a Central Processing Unit (CPU), and may include other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, and the processor 13 is a control center of the geographic characteristic-based multi-factor aging tester 10, and various interfaces and lines are used to connect various parts of the entire geographic characteristic-based multi-factor aging tester 10.
The memory 12 may be used to store the computer program 14 and/or the modules/units, and the processor 13 implements various functions of the multi-factor aging experimental apparatus 10 based on the geographic characteristics by running or executing the computer program and/or the modules/units stored in the memory 12 and calling data stored in the memory 12. The storage 12 may include an external storage medium, and may also include a memory. Further, the memory 12 may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The integrated modules/units of the multi-factor aging experimental device 10 based on regional characteristics can be stored in a computer readable storage medium if they are implemented in the form of software functional units and sold or used as independent products. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. The units or computer means recited in the computer means claims may also be implemented by the same unit or computer means, either in software or in hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and 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 modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (9)
1. A multi-factor aging experiment method based on regional characteristics is used for carrying out a multi-factor aging experiment on a composite insulator, and is characterized by comprising the following steps:
creating and storing a corresponding relation table of aging factors and weather modes, wherein the weather modes comprise a sunny mode, a cloudy mode and a rainy mode in the corresponding relation table, the aging factors corresponding to the sunny mode comprise heating and ultraviolet rays, the aging factors corresponding to the cloudy mode comprise humidity and salt fog, and the aging factors corresponding to the rainy mode comprise rainfall;
acquiring meteorological data of a target area in each month from one month to twelve months, dividing four seasons of the target area according to the meteorological data of each month, and determining a characteristic month in each season;
acquiring meteorological data of each day in the characteristic month of each season, and determining a weather mode of each day in the characteristic month according to the meteorological data of each day, wherein the weather mode comprises a sunny mode, a cloudy mode and a rainy mode;
counting the distribution condition of each weather mode in the characteristic month according to the weather mode of each day in the characteristic month, and calculating the proportion of the total days of each weather mode in the characteristic month in the total days of all weather modes;
calculating the total hours of all weather patterns in each characteristic month, dividing the total hours of all weather patterns by an aging acceleration factor to obtain the total hours of each characteristic month in a multi-factor aging experiment, then calculating the total hours of each weather pattern in the multi-factor aging experiment according to the proportion of each weather pattern, and carrying out time distribution on each weather pattern in the multi-factor aging experiment according to the distribution condition of each weather pattern;
repeating the weather pattern distribution condition of each seasonal characteristic month in the multi-factor aging experiment for preset times, wherein the value of the preset times is equal to the value of the total number of months in the seasons, and obtaining the annual weather pattern in the multi-factor aging experiment;
and applying the corresponding aging factors according to the corresponding relation between the aging factors and the weather modes in the corresponding relation table and the weather mode distribution condition of each seasonal characteristic month in the multi-factor aging test, and carrying out the multi-factor aging test on the composite insulator to be tested.
2. The method of claim 1, wherein the weather data for each month of the target area includes an average air temperature for each month, the four seasons of the target area are divided according to the average air temperature for each month by using a weather method, and the characteristic month for each of the four seasons of the target area is determined by: the month with the highest temperature is selected as the characteristic part in summer, and the month with the lowest temperature is selected as the characteristic month in spring, autumn and winter.
3. The multi-factor aging experimental method based on regional characteristics as claimed in claim 2, wherein the meteorological data of each month of the target region further includes an average precipitation of each month, and the method for determining the characteristic month in each season further includes: and in each season, selecting the month with the largest average precipitation as the characteristic month when the difference of the average temperature of the months is less than a preset value.
4. The multi-factor aging experimental method based on regional characteristics as claimed in claim 1, wherein the weather data of each day in the characteristic month includes daily precipitation and sunshine hours, the weather pattern of the day is determined according to the daily precipitation and sunshine hours of the day, and the method for determining the weather pattern of the day according to the daily precipitation and sunshine hours of the day comprises:
judging whether the daily precipitation of the day is larger than a preset precipitation threshold value;
if the daily rainfall is larger than the rainfall threshold, determining that the weather mode of the day is a rainy day mode;
if the daily rainfall is smaller than the rainfall threshold, further judging whether the sunshine hours of the day are larger than a preset sunshine time threshold;
if the sunshine hours of the day are larger than the sunshine time threshold value, determining that the weather mode of the day is sunny;
and if the sunshine hours of the day are less than the sunshine time threshold value, determining that the weather mode of the day is cloudy.
5. The multi-factor aging experimental method based on regional characteristics as claimed in claim 4, wherein the method further comprises: judging whether the meteorological data of each day exceeds a preset range, if so, determining that the meteorological data of the day is wrong, excluding the meteorological data of the day, and not judging the weather mode; and if the weather pattern does not exceed the preset range, judging the weather pattern on the day.
6. The multi-factor aging test method based on regional characteristics as claimed in claim 1, wherein the aging factors in the multi-factor aging test include temperature, ultraviolet rays, salt fog, humidity, rainfall and voltage, and the method further comprises setting parameters of the aging factors applied to the tested composite insulator, wherein the temperature parameters in the aging factors are set as: in summer, setting the temperature in a sunny mode to be the highest daily temperature of the target area plus a preset upward floating value, in winter, setting the lowest daily temperature, and setting the rest time to be the highest normal daily temperature; setting the value of ultraviolet rays as the daily maximum radiance of the target area; the salt fog value is the concentration value of the dirt in the target area; the humidity value is the highest humidity value of the target area day; the numerical value of the rainfall is set to be a preset numerical value, and the preset numerical value is a rainfall numerical value capable of flushing dirt on the surface of the insulator; the numerical value of the voltage is the creepage distance ratio of the composite insulator to be tested, wherein the creepage distance ratio of the insulator is the ratio of the creepage distance of the insulator to the root mean square value of the highest running voltage borne on the insulator.
7. The multi-factor aging experimental method based on geographical features as claimed in claim 1, wherein the value of the aging acceleration factor is 16.
8. A multi-factor aging experiment system based on regional characteristics is characterized in that the system comprises:
the device comprises a setting module, a storage module and a display module, wherein the setting module is used for creating and storing a corresponding relation table of aging factors and weather modes, the weather modes comprise a sunny mode, a cloudy mode and a rainy mode in the corresponding relation table, the aging factors corresponding to the sunny mode comprise heating and ultraviolet rays, the aging factors corresponding to the cloudy mode comprise humidity and salt fog, and the aging factors corresponding to the rainy mode comprise rainfall;
the characteristic month determining module is used for acquiring meteorological data of each month from one month to twelve months of a target area, dividing four seasons of the target area according to the meteorological data of each month and determining a characteristic month in each season;
the weather mode determining module is used for acquiring weather data of each day in the characteristic month of each season and determining a weather mode of each day in the characteristic month according to the weather data of each day, wherein the weather mode comprises a sunny mode, a cloudy mode and a rainy mode;
the calculation module is used for counting the distribution condition of each weather mode in the characteristic month according to the weather mode of each day in the characteristic month and calculating the proportion of the total days of each weather mode in the characteristic month in the total days of all weather modes;
the distribution module is used for calculating the total hours of all the weather modes in each characteristic month, dividing the total hours of all the weather modes by an aging acceleration factor to obtain the total hours of each characteristic month in the multi-factor aging experiment, then calculating the total hours of each weather mode in the multi-factor aging experiment according to the proportion of each weather mode, and carrying out time distribution on each weather mode in the multi-factor aging experiment according to the distribution condition of each weather mode;
the all-year weather mode determining module is used for repeating the weather mode distribution condition of each seasonal characteristic month in the multi-factor aging experiment for preset times, wherein the value of the preset times is equal to the value of the total number of months in the seasons, so that the all-year weather mode in the multi-factor aging experiment is obtained; and
and the control module is used for applying corresponding aging factors according to the corresponding relation between the aging factors and the weather modes in the corresponding relation table and the weather mode distribution condition of each seasonal characteristic month in the multi-factor aging experiment so as to carry out multi-factor aging test on the composite insulator to be tested.
9. The utility model provides an ageing experimental apparatus of multifactor based on regional characteristics for carry out ageing experiments to composite insulator, a serial communication port, the device includes:
the aging factor applying device is used for applying an aging factor in a multi-factor aging experiment to the composite insulator;
a processor; and
a memory having stored therein a plurality of program modules that are loaded by the processor and execute the method of the multi-factor aging test based on regional characteristics as claimed in any one of claims 1 to 7.
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