CN113610830B - Detection system and method for lightning arrester - Google Patents
Detection system and method for lightning arrester Download PDFInfo
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Abstract
The invention discloses a detection system and a detection method for a lightning arrester, wherein the detection system comprises a reference information acquisition and storage module, a leakage current acquisition module, a comparison difference value judgment module, a cleaning analysis module and an alarm transmission module, wherein the reference information acquisition and storage module acquires an initial appearance image of the lightning arrester in advance as a reference image, the initial leakage current of the lightning arrester Is acquired in advance as a reference current Ic, the leakage current acquisition module acquires the leakage current Is of the lightning arrester at a certain moment, the comparison difference value judgment module calculates a comparison difference value Ib=is-Ic, compares the comparison difference value with a first difference value threshold and a second difference value threshold, judges that the lightning arrester works normally when the comparison difference value Ib Is smaller than the first difference value threshold and the comparison difference value Ib Is smaller than the second difference value threshold, and enables the cleaning analysis module to work when the comparison difference value Ib Is larger than the second difference value threshold and enables the alarm transmission module to work.
Description
Technical Field
The invention relates to the technical field of lightning arresters, in particular to a detection system and method for a lightning arrester.
Background
In a power system, electrical equipment is inevitably affected by overvoltage in the use process, and in order to ensure safe and stable operation of the electrical equipment in the power system, a lightning arrester is installed in the power system. The lightning arrester is an important overvoltage protection device in the power system, is connected in parallel near the protected equipment, and prevents the insulation of the lightning arrester from being damaged by lightning overvoltage or operation overvoltage. However, along with the operation of the lightning arrester, the surface of the lightning arrester can accumulate filth, and if the lightning arrester works under the indication of filth for a long time, the accuracy of the lightning arrester can be affected, and the lightning arrester is damaged easily.
Disclosure of Invention
The invention aims to provide a detection system and a detection method for a lightning arrester, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the detection system for the lightning arrester comprises a reference information acquisition and storage module, a leakage current acquisition module, a comparison difference value judgment module, a cleaning analysis module and an alarm transmission module, wherein the reference information acquisition and storage module acquires an initial appearance image of the lightning arrester in advance as a reference image, acquires an initial leakage current of the lightning arrester in advance as a reference current Ic, the leakage current acquisition module acquires the leakage current Is of the lightning arrester at a certain moment, the comparison difference value judgment module calculates comparison difference values Ib=is-Ic, compares the comparison difference values with a first difference value threshold and a second difference value threshold, judges that the lightning arrester works normally when the comparison difference value Ib Is smaller than the first difference value threshold, enables the cleaning analysis module to work when the comparison difference value Ib Is larger than the first difference value threshold and the comparison difference value Ib Is smaller than the second difference value threshold, and enables the alarm transmission module to work when the comparison difference value Ib Is larger than the second difference value threshold; the cleaning analysis module collects an additional image of the lightning arrester at the moment to be an image to be analyzed, compares the image to be analyzed with a reference image to judge whether the lightning arrester is to be cleaned or not, and the alarm transmission module is used for transmitting alarm information.
Further, the cleaning analysis module comprises an abnormal pixel point judgment module, a first ratio threshold comparison module, an abnormal pixel point area analysis module and a cleaning transmission reminding module, wherein the abnormal pixel point judgment module is used for comparing the pixel value of each pixel point in the image to be analyzed with the pixel value of the pixel point at the corresponding position in the reference image, the pixel difference value corresponding to a certain pixel point in the image to be analyzed is larger than a pixel difference threshold, the pixel point is set to be the abnormal pixel point, the first ratio threshold comparison module is used for collecting the ratio Ny of the number of the abnormal pixel points in the image to be analyzed and the number of all the pixel points in the image to be analyzed, when the ratio Ny is larger than or equal to the first ratio threshold, the cleaning transmission reminding module is enabled to work, when the ratio Ny is smaller than the first ratio threshold, the abnormal pixel point area analysis module is enabled to work, the abnormal pixel point area analysis module is used for analyzing the aggregation condition of the abnormal pixel points in the image to be analyzed, whether the cleaning transmission reminding module is enabled to work or not is enabled, and the cleaning transmission reminding module is enabled to be used for transmitting information to be used for a lightning arrester of a working staff.
Further, the abnormal pixel point area analysis module comprises a square area division module, a first suspicious area selection module, a second suspicious area selection module, a fourth suspicious area selection module, an area comparison module, a superposition analysis area selection module and a pixel point distribution analysis module, wherein the square area division module is used for uniformly dividing an image to be analyzed into a plurality of square areas with equal size, the first suspicious area selection module respectively counts the ratio Nz of the number of abnormal pixel points in each square area to the number of all pixel points in the corresponding square area, when the ratio Nz is larger than a second ratio threshold, the square area is set as a first suspicious area, the second suspicious area selection module is set as a first suspicious area adjacent to a certain two first suspicious areas, the two first suspicious areas are combined as a second suspicious area, the fourth suspicious region selection module respectively obtains the distance between the centers of two second suspicious regions, if the distance between the centers of two second suspicious regions is smaller than or equal to a first distance threshold, then respectively selects one abnormal pixel point from each of the two second suspicious regions, and respectively selects the minimum value of the distance between one abnormal pixel point to be smaller than or equal to a second distance threshold, connects the key points of the two abnormal pixel points through a line segment, the pixel points which pass through the line segment except the two second suspicious regions are third suspicious regions, combines the two second suspicious regions and the third suspicious regions to obtain a fourth suspicious region, the region area comparison module is used for obtaining the areas of the second suspicious region and the fourth suspicious region, and when the area of the second suspicious region or the fourth suspicious region is larger than or equal to the first area threshold, and enabling the cleaning transmission reminding module to work, enabling the superposition analysis area selection module to work when the areas of all the second suspicious areas and the fourth suspicious areas are smaller than the first area threshold, and enabling the pixel distribution analysis module to analyze abnormal pixel distribution conditions of all the superposition analysis areas after setting the suspicious areas as the superposition analysis areas when the areas of the second suspicious areas or the fourth suspicious areas are larger than or equal to the second area threshold.
Further, the method comprises the steps of: the pixel distribution analysis module comprises a pixel classification module, a group classification module and a superposition duty ratio threshold comparison module, wherein the pixel classification module extracts abnormal pixel points in each superposition analysis area, compares the pixel values of each abnormal pixel point with the pixel values of the observation pixel points in the observation database, and if the difference between the pixel value of a certain abnormal pixel point and the pixel values of all the observation pixel points in the observation database is larger than a difference value, sets the abnormal pixel point as a post-fixed pixel point; if the difference between the pixel value of a certain abnormal pixel point and the pixel value of a certain observed pixel point in the observed database is smaller than or equal to the difference value, the abnormal pixel point is set as a front fixed pixel point, wherein when the certain pixel point is judged to be the abnormal pixel point, the abnormal pixel point is stored as the observed pixel point in the observed database; the group classification module sets any two front fixed pixel points in a certain superposition analysis area to form a group of observation groups, if only rear fixed pixel points exist on the connecting line of the centers of the two front fixed pixel points of a certain group of observation groups, the group of observation groups are set to be superposition groups, the superposition duty ratio threshold comparison module is used for judging whether the ratio between the number of the superposition groups and the number of the observation groups is greater than or equal to a superposition duty ratio threshold in the certain superposition analysis area, and the cleaning transmission reminding module works under the condition that the ratio is greater than or equal to the superposition duty ratio threshold.
A detection method for a lightning arrester, the detection method comprising the steps of:
pre-collecting an initial appearance image of the lightning arrester as a reference image, and pre-collecting initial leakage current of the lightning arrester as a reference current Ic;
collecting leakage current Is of the lightning arrester at a certain moment, calculating and comparing a difference value Ib=is-Ic,
if the comparison difference value Ib is smaller than the first difference value threshold value, judging that the lightning arrester works normally;
if the comparison difference value Ib is larger than the first difference value threshold value and the comparison difference value Ib is smaller than the second difference value threshold value, acquiring an additional image of the lightning arrester at the moment as an image to be analyzed, comparing the image to be analyzed with a reference image, and judging whether the lightning arrester is to be cleaned or not;
and if the comparison difference value Ib is larger than the second difference value threshold value, transmitting alarm information.
Further, the determining whether to overhaul the lightning arrester includes:
comparing the pixel difference value between the pixel value of each pixel point in the image to be analyzed and the pixel value of the pixel point at the corresponding position in the reference image, and if the pixel difference value corresponding to a certain pixel point in the image to be analyzed is larger than a pixel difference threshold value, the pixel point is an abnormal pixel point;
collecting the ratio Ny of the number of abnormal pixel points in the image to be analyzed and the number of all pixel points in the image to be analyzed, and if the ratio Ny is greater than or equal to a first ratio threshold value, transmitting information to clean the lightning arrester;
if the ratio Ny is smaller than the first ratio threshold, uniformly dividing the image to be analyzed into a plurality of square areas with equal size,
respectively counting the ratio Nz of the number of abnormal pixel points in each square area to the number of all pixel points in the corresponding square area, if the ratio Nz is larger than a second ratio threshold value, the square area is a first suspicious area,
if some two first in-doubt areas are adjacent first in-doubt areas, merging the two first in-doubt areas into a second in-doubt area;
respectively obtaining the distance between the centers of every two second suspicious regions, if the distance between the centers of two second suspicious regions is smaller than or equal to a first distance threshold value, respectively selecting one abnormal pixel point from each of the two second suspicious regions,
if the minimum value of the distance between each selected abnormal pixel point is smaller than or equal to a second distance threshold value, connecting the key points of the two abnormal pixel points through a line segment, taking the pixel points which pass through the line segment except the two second suspicious regions as a third suspicious region, merging the two second suspicious regions with the third suspicious region to obtain a fourth suspicious region,
the areas of the second suspicious region and the fourth suspicious region are respectively obtained, and if the areas of the second suspicious region or the fourth suspicious region are larger than or equal to a first area threshold value, the lightning arrester is cleaned by transmitting information;
otherwise, if the area of the second suspicious region or the fourth suspicious region is larger than or equal to the second area threshold, setting the suspicious regions as superposition analysis regions, and analyzing the abnormal pixel point distribution condition of each superposition analysis region
Further, the analyzing the abnormal pixel distribution of the overlapping analysis area includes:
extracting abnormal pixel points in each superposition analysis area, comparing the pixel value of each abnormal pixel point with the pixel value of an observation pixel point in an observation database, and if the difference between the pixel value of a certain abnormal pixel point and the pixel values of all the observation pixel points in the observation database is larger than a difference value, setting the abnormal pixel point as a post-fixed pixel point; if the difference between the pixel value of a certain abnormal pixel point and the pixel value of a certain observed pixel point in the observed database is smaller than or equal to the difference value, the abnormal pixel point is set as a front fixed pixel point, wherein when the certain pixel point is judged to be the abnormal pixel point, the abnormal pixel point is stored as the observed pixel point in the observed database;
if the ratio of the number of the superposition groups to the number of the observation groups in a certain superposition analysis zone is greater than or equal to a superposition duty ratio threshold, the lightning arrester is cleaned by transmitting information;
in a certain superposition analysis area, any two front fixed pixel points form a group of observation groups, and if only rear fixed pixel points exist on a connecting line of centers of the two front fixed pixel points of a certain group of observation groups, the group of observation groups is a superposition group.
Further, the detection method further comprises: and when the cleaning lightning arrester is detected, the observation pixel points stored in the observation database are emptied.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, through detection and analysis of the leakage current of the lightning arrester, when the detected leakage current is higher than the leakage current under normal conditions, the appearance image of the lightning arrester is analyzed, and whether the leakage current is relatively higher or not is judged by analysis because of the pollution on the lightning arrester, so that the pollution on the lightning arrester is cleaned in time, and the accuracy and the service life of the lightning arrester are prolonged.
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The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic block diagram of a detection system for a lightning arrester according to the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: the detection system for the lightning arrester comprises a reference information acquisition and storage module, a leakage current acquisition module, a comparison difference value judgment module, a cleaning analysis module and an alarm transmission module, wherein the reference information acquisition and storage module acquires an initial appearance image of the lightning arrester in advance as a reference image, acquires an initial leakage current of the lightning arrester in advance as a reference current Ic, the leakage current acquisition module acquires the leakage current Is of the lightning arrester at a certain moment, the comparison difference value judgment module calculates comparison difference values Ib=is-Ic, compares the comparison difference values with a first difference value threshold and a second difference value threshold, judges that the lightning arrester works normally when the comparison difference value Ib Is smaller than the first difference value threshold, enables the cleaning analysis module to work when the comparison difference value Ib Is larger than the first difference value threshold and the comparison difference value Ib Is smaller than the second difference value threshold, and enables the alarm transmission module to work when the comparison difference value Ib Is larger than the second difference value threshold; the cleaning analysis module collects an additional image of the lightning arrester at the moment to be an image to be analyzed, compares the image to be analyzed with a reference image to judge whether the lightning arrester is to be cleaned or not, and the alarm transmission module is used for transmitting alarm information.
The cleaning analysis module comprises an abnormal pixel point judgment module, a first ratio threshold comparison module, an abnormal pixel point area analysis module and a cleaning transmission reminding module, wherein the abnormal pixel point judgment module is used for comparing pixel differences between pixel values of all pixel points in an image to be analyzed and pixel values of pixel points at corresponding positions in a reference image, the pixel differences corresponding to a certain pixel point in the image to be analyzed are larger than a pixel difference threshold, the pixel point is set to be the abnormal pixel point, the first ratio threshold comparison module is used for collecting the ratio Ny of the number of the abnormal pixel points in the image to be analyzed to the number of all pixel points in the image to be analyzed, when the ratio Ny is larger than or equal to the first ratio threshold, the cleaning transmission reminding module is enabled to work, when the ratio Ny is smaller than the first ratio threshold, the abnormal pixel point area analysis module is enabled to work, the abnormal pixel point area analysis module is used for analyzing the aggregation condition of the abnormal pixel points in the image to be analyzed, whether the cleaning transmission reminding module is enabled to work or not is judged, and the cleaning transmission reminding module is enabled to remind a working staff of a cleaner.
The abnormal pixel point area analysis module comprises a square area division module, a first in-doubt area selection module, a second in-doubt area selection module, a fourth in-doubt area selection module, an area comparison module, a superposition analysis area selection module and a pixel point distribution analysis module, wherein the square area division module is used for uniformly dividing an image to be analyzed into a plurality of square areas with equal size, the first in-doubt area selection module respectively counts the ratio Nz of the number of abnormal pixels in each square area to the number of all pixels in the corresponding square area, when the ratio Nz is larger than a second ratio threshold, the square area is set as a first in-doubt area, the second in-doubt area selection module is set as a first in-doubt area adjacent to the first in-doubt area, the two first in-doubt areas are combined as a second in-doubt area, the fourth suspicious region selection module respectively obtains the distance between the centers of two second suspicious regions, if the distance between the centers of two second suspicious regions is smaller than or equal to a first distance threshold, then respectively selects one abnormal pixel point from each of the two second suspicious regions, and respectively selects the minimum value of the distance between one abnormal pixel point to be smaller than or equal to a second distance threshold, connects the key points of the two abnormal pixel points through a line segment, the pixel points which pass through the line segment except the two second suspicious regions are third suspicious regions, combines the two second suspicious regions and the third suspicious regions to obtain a fourth suspicious region, the region area comparison module is used for obtaining the areas of the second suspicious region and the fourth suspicious region, and when the area of the second suspicious region or the fourth suspicious region is larger than or equal to the first area threshold, and enabling the cleaning transmission reminding module to work, enabling the superposition analysis area selection module to work when the areas of all the second suspicious areas and the fourth suspicious areas are smaller than the first area threshold, and enabling the pixel distribution analysis module to analyze abnormal pixel distribution conditions of all the superposition analysis areas after setting the suspicious areas as the superposition analysis areas when the areas of the second suspicious areas or the fourth suspicious areas are larger than or equal to the second area threshold.
The pixel distribution analysis module comprises a pixel classification module, a group classification module and a superposition duty ratio threshold comparison module, wherein the pixel classification module extracts abnormal pixel points in each superposition analysis area, compares the pixel values of each abnormal pixel point with the pixel values of the observation pixel points in the observation database, and if the difference between the pixel value of a certain abnormal pixel point and the pixel values of all the observation pixel points in the observation database is larger than a difference value, sets the abnormal pixel point as a post-fixed pixel point; if the difference between the pixel value of a certain abnormal pixel point and the pixel value of a certain observed pixel point in the observed database is smaller than or equal to the difference value, the abnormal pixel point is set as a front fixed pixel point, wherein when the certain pixel point is judged to be the abnormal pixel point, the abnormal pixel point is stored as the observed pixel point in the observed database; the group classification module sets any two front fixed pixel points in a certain superposition analysis area to form a group of observation groups, if only rear fixed pixel points exist on the connecting line of the centers of the two front fixed pixel points of a certain group of observation groups, the group of observation groups are set to be superposition groups, the superposition duty ratio threshold comparison module is used for judging whether the ratio between the number of the superposition groups and the number of the observation groups is greater than or equal to a superposition duty ratio threshold in the certain superposition analysis area, and the cleaning transmission reminding module works under the condition that the ratio is greater than or equal to the superposition duty ratio threshold.
A detection method for a lightning arrester, the detection method comprising the steps of:
pre-collecting an initial appearance image of the lightning arrester as a reference image, and pre-collecting initial leakage current of the lightning arrester as a reference current Ic;
collecting leakage current Is of the lightning arrester at a certain moment, calculating and comparing a difference value Ib=is-Ic,
if the comparison difference value Ib is smaller than the first difference value threshold value, judging that the lightning arrester works normally;
if the comparison difference value Ib is larger than the first difference value threshold value and the comparison difference value Ib is smaller than the second difference value threshold value, acquiring an appearance image of the lightning arrester at the moment as an image to be analyzed, comparing the image to be analyzed with a reference image, and judging whether the lightning arrester is to be cleaned or not; when the surface of the lightning arrester is polluted, the voltage distribution on the surface of the lightning arrester is affected, so that the leakage current of the lightning arrester is increased, and whether the lightning arrester is to be cleaned or not is judged according to the leakage current.
And if the comparison difference value Ib is larger than the second difference value threshold value, transmitting alarm information.
Said determining whether to service the arrester comprises:
comparing the pixel difference value between the pixel value of each pixel point in the image to be analyzed and the pixel value of the pixel point at the corresponding position in the reference image, and if the pixel difference value corresponding to a certain pixel point in the image to be analyzed is larger than a pixel difference threshold value, the pixel point is an abnormal pixel point; because the lightning arrester is composed of multiple parts, the lightning arrester can be divided into multiple components when the image of the lightning arrester is collected for analysis, and the components are collected and analyzed respectively;
collecting the ratio Ny of the number of abnormal pixel points in the image to be analyzed and the number of all pixel points in the image to be analyzed, and if the ratio Ny is greater than or equal to a first ratio threshold value, transmitting information to clean the lightning arrester;
if the ratio Ny is smaller than a first ratio threshold value, uniformly dividing an image to be analyzed into a plurality of square areas with equal size, judging whether the surface of the lightning arrester is polluted by comparing pixel values of pixel points, directly reminding a worker to clean under the condition that the abnormal pixel points are more, namely the pollution on the surface of the lightning arrester is more, and judging whether the pollution on the surface of the lightning arrester is more scattered or more concentrated under the condition that the abnormal pixel points are less;
respectively counting the ratio Nz of the number of abnormal pixel points in each square area to the number of all pixel points in the corresponding square area, if the ratio Nz is larger than a second ratio threshold value, the square area is a first suspicious area,
if some two first in-doubt areas are adjacent first in-doubt areas, merging the two first in-doubt areas into a second in-doubt area;
respectively obtaining the distance between the centers of every two second suspicious regions, if the distance between the centers of two second suspicious regions is smaller than or equal to a first distance threshold value, respectively selecting one abnormal pixel point from each of the two second suspicious regions,
if the minimum value of the distance between every two selected abnormal pixel points is smaller than or equal to a second distance threshold value, connecting the key points of the two abnormal pixel points through a line segment, wherein the pixel points which pass through the line segment and are except for the two second suspicious regions are the third suspicious region, merging the two second suspicious regions and the third suspicious region to obtain a fourth suspicious region, and further judging whether the two second suspicious regions are clustered or not through the distance between the abnormal pixel points on the two second suspicious regions on the basis of comparing the distance between the centers of the two second suspicious regions with the first distance threshold value, so that the accuracy of judging whether the two suspicious regions are clustered or not is improved;
the areas of the second suspicious region and the fourth suspicious region are respectively obtained, and if the areas of the second suspicious region or the fourth suspicious region are larger than or equal to a first area threshold value, the lightning arrester is cleaned by transmitting information; if the less dirt is distributed and dispersed on the surface of the lightning arrester, the voltage on the surface of the lightning arrester is uniformly distributed, and the voltage difference between all places is smaller; if the dirt is concentrated on a certain place on the surface of the lightning arrester, the voltage difference between the place and other places is easily caused to be too large, the lightning arrester is more easily damaged,
otherwise, if the area of the second suspicious region or the fourth suspicious region is larger than or equal to the second area threshold, the suspicious regions are set as superposition analysis regions, and abnormal pixel point distribution conditions of each superposition analysis region are analyzed.
The analysis of the abnormal pixel point distribution of the superposition analysis area comprises the following steps:
extracting abnormal pixel points in each superposition analysis area, comparing the pixel value of each abnormal pixel point with the pixel value of an observation pixel point in an observation database, and if the difference between the pixel value of a certain abnormal pixel point and the pixel values of all the observation pixel points in the observation database is larger than a difference value, setting the abnormal pixel point as a post-fixed pixel point; if the difference between the pixel value of a certain abnormal pixel point and the pixel value of a certain observed pixel point in the observed database is smaller than or equal to the difference value, the abnormal pixel point is set as a front fixed pixel point, wherein when the certain pixel point is judged to be the abnormal pixel point, the abnormal pixel point is stored as the observed pixel point in the observed database;
if the ratio of the number of the superposition groups to the number of the observation groups in a certain superposition analysis zone is greater than or equal to a superposition duty ratio threshold, the lightning arrester is cleaned by transmitting information;
in a certain superposition analysis area, any two front fixed pixel points form a group of observation groups, and if only rear fixed pixel points exist on a connecting line of the centers of the two front fixed pixel points of a certain group of observation groups, the group of observation groups are superposition groups; judging whether the front fixed pixel point and the rear fixed pixel point are in a mixed position relationship or not through the position relationship between the front fixed pixel point and the rear fixed pixel point, further judging whether the surface of the lightning arrester is accumulated with multiple layers of dirt or not, and further judging whether the surface of the lightning arrester is to be cleaned or not;
the observation database is used for storing abnormal pixel points acquired after a certain cleaning of the lightning arrester, and when the cleaning of the lightning arrester is detected, the observation pixel points stored in the observation database are emptied; and the subsequent comparison is convenient to judge whether the multi-layer dirt is accumulated on the lightning arrester.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. The detection system for the lightning arrester Is characterized by comprising a reference information acquisition and storage module, a leakage current acquisition module, a comparison difference value judgment module, a cleaning analysis module and an alarm transmission module, wherein the reference information acquisition and storage module acquires an initial appearance image of the lightning arrester in advance as a reference image, acquires an initial leakage current of the lightning arrester in advance as a reference current Ic, the leakage current acquisition module acquires the leakage current Is of the lightning arrester at a certain moment, the comparison difference value judgment module calculates a comparison difference value Ib=is-Ic, compares the comparison difference value with a first difference value threshold and a second difference value threshold, judges that the lightning arrester works normally when the comparison difference value Ib Is smaller than the first difference value threshold and the comparison difference value Ib Is smaller than the second difference value threshold, and enables the cleaning analysis module to work when the comparison difference value Ib Is larger than the second difference value threshold and enables the alarm transmission module to work; the cleaning analysis module acquires an additional image of the lightning arrester at the moment as an image to be analyzed, compares the image to be analyzed with a reference image, judges whether the lightning arrester is to be cleaned or not, and the alarm transmission module is used for transmitting alarm information;
the cleaning analysis module comprises an abnormal pixel point judgment module, a first ratio threshold comparison module, an abnormal pixel point area analysis module and a cleaning transmission reminding module, wherein the abnormal pixel point judgment module is used for comparing pixel differences between pixel values of each pixel point in an image to be analyzed and pixel values of pixel points at corresponding positions in a reference image, the pixel differences corresponding to a certain pixel point in the image to be analyzed are larger than a pixel difference threshold, the pixel point is set to be the abnormal pixel point, the first ratio threshold comparison module is used for collecting the ratio Ny of the number of the abnormal pixel points in the image to be analyzed and the number of all the pixel points in the image to be analyzed, when the ratio Ny is larger than or equal to the first ratio threshold, the cleaning transmission reminding module is enabled to work, and when the ratio Ny is smaller than the first ratio threshold, the abnormal pixel point area analysis module is enabled to work, the abnormal pixel point area analysis module is used for analyzing the aggregation condition of the abnormal pixel points in the image to be analyzed and judging whether the cleaning transmission reminding module is enabled to work or not, and the cleaning transmission module is enabled to remind a worker of a cleaner by using the cleaning transmission information;
the abnormal pixel point area analysis module comprises a square area division module, a first in-doubt area selection module, a second in-doubt area selection module, a fourth in-doubt area selection module, an area comparison module, a superposition analysis area selection module and a pixel point distribution analysis module, wherein the square area division module is used for uniformly dividing an image to be analyzed into a plurality of square areas with equal size, the first in-doubt area selection module respectively counts the ratio Nz of the number of abnormal pixels in each square area to the number of all pixels in the corresponding square area, when the ratio Nz is larger than a second ratio threshold, the square area is set as a first in-doubt area, the second in-doubt area selection module is set as a first in-doubt area adjacent to the first in-doubt area, the two first in-doubt areas are combined as a second in-doubt area, the fourth suspicious region selection module respectively obtains the distance between the centers of two second suspicious regions, if the distance between the centers of two second suspicious regions is smaller than or equal to a first distance threshold, then respectively selects one abnormal pixel point from each of the two second suspicious regions, and respectively selects the minimum value of the distance between one abnormal pixel point to be smaller than or equal to a second distance threshold, connects the key points of the two abnormal pixel points through a line segment, the pixel points which pass through the line segment except the two second suspicious regions are third suspicious regions, combines the two second suspicious regions and the third suspicious regions to obtain a fourth suspicious region, the region area comparison module is used for obtaining the areas of the second suspicious region and the fourth suspicious region, and when the area of the second suspicious region or the fourth suspicious region is larger than or equal to the first area threshold, and enabling the cleaning transmission reminding module to work, enabling the superposition analysis area selection module to work when the areas of all the second suspicious areas and the fourth suspicious areas are smaller than the first area threshold, and enabling the pixel distribution analysis module to analyze abnormal pixel distribution conditions of all the superposition analysis areas after setting the suspicious areas as the superposition analysis areas when the areas of the second suspicious areas or the fourth suspicious areas are larger than or equal to the second area threshold.
2. A detection system for a lightning arrester according to claim 1, wherein: the pixel distribution analysis module comprises a pixel classification module, a group classification module and a superposition duty ratio threshold comparison module, wherein the pixel classification module extracts abnormal pixel points in each superposition analysis area, compares the pixel values of each abnormal pixel point with the pixel values of the observation pixel points in the observation database, and if the difference between the pixel value of a certain abnormal pixel point and the pixel values of all the observation pixel points in the observation database is larger than a difference value, sets the abnormal pixel point as a post-fixed pixel point; if the difference between the pixel value of a certain abnormal pixel point and the pixel value of a certain observed pixel point in the observed database is smaller than or equal to the difference value, the abnormal pixel point is set as a front fixed pixel point, wherein when the certain pixel point is judged to be the abnormal pixel point, the abnormal pixel point is stored as the observed pixel point in the observed database; the group classification module sets any two front fixed pixel points in a certain superposition analysis area to form a group of observation groups, if only rear fixed pixel points exist on the connecting line of the centers of the two front fixed pixel points of a certain group of observation groups, the group of observation groups are set to be superposition groups, the superposition duty ratio threshold comparison module is used for judging whether the ratio between the number of the superposition groups and the number of the observation groups is greater than or equal to a superposition duty ratio threshold in the certain superposition analysis area, and the cleaning transmission reminding module works under the condition that the ratio is greater than or equal to the superposition duty ratio threshold.
3. A detection method for a lightning arrester is characterized by comprising the following steps: the detection method comprises the following steps:
pre-collecting an initial appearance image of the lightning arrester as a reference image, and pre-collecting initial leakage current of the lightning arrester as a reference current Ic;
collecting leakage current Is of the lightning arrester at a certain moment, calculating and comparing a difference value Ib=is-Ic,
if the comparison difference value Ib is smaller than the first difference value threshold value, judging that the lightning arrester works normally;
if the comparison difference value Ib is larger than the first difference value threshold value and the comparison difference value Ib is smaller than the second difference value threshold value, acquiring an additional image of the lightning arrester at the moment as an image to be analyzed, comparing the image to be analyzed with a reference image, and judging whether the lightning arrester is to be cleaned or not;
if the comparison difference value Ib is larger than the second difference value threshold value, transmitting alarm information;
said determining whether to clean the arrester comprises:
comparing the pixel difference value between the pixel value of each pixel point in the image to be analyzed and the pixel value of the pixel point at the corresponding position in the reference image, and if the pixel difference value corresponding to a certain pixel point in the image to be analyzed is larger than a pixel difference threshold value, the pixel point is an abnormal pixel point;
collecting the ratio Ny of the number of abnormal pixel points in the image to be analyzed and the number of all pixel points in the image to be analyzed, and if the ratio Ny is greater than or equal to a first ratio threshold value, transmitting information to clean the lightning arrester;
if the ratio Ny is smaller than the first ratio threshold, uniformly dividing the image to be analyzed into a plurality of square areas with equal size,
respectively counting the ratio Nz of the number of abnormal pixel points in each square area to the number of all pixel points in the corresponding square area, if the ratio Nz is larger than a second ratio threshold value, the square area is a first suspicious area,
if some two first in-doubt areas are adjacent first in-doubt areas, merging the two first in-doubt areas into a second in-doubt area;
respectively obtaining the distance between the centers of every two second suspicious regions, if the distance between the centers of two second suspicious regions is smaller than or equal to a first distance threshold value, respectively selecting one abnormal pixel point from each of the two second suspicious regions,
if the minimum value of the distance between each selected abnormal pixel point is smaller than or equal to a second distance threshold value, connecting the key points of the two abnormal pixel points through a line segment, taking the pixel points which pass through the line segment except the two second suspicious regions as a third suspicious region, merging the two second suspicious regions with the third suspicious region to obtain a fourth suspicious region,
the areas of the second suspicious region and the fourth suspicious region are respectively obtained, and if the areas of the second suspicious region or the fourth suspicious region are larger than or equal to a first area threshold value, the lightning arrester is cleaned by transmitting information;
otherwise, if the second suspicious region or the fourth suspicious region is larger than or equal to the second area threshold, setting the suspicious regions as superposition analysis regions, and analyzing abnormal pixel point distribution conditions of each superposition analysis region;
the analysis of the abnormal pixel point distribution of the superposition analysis area comprises the following steps:
extracting abnormal pixel points in each superposition analysis area, comparing the pixel value of each abnormal pixel point with the pixel value of an observation pixel point in an observation database, and if the difference between the pixel value of a certain abnormal pixel point and the pixel values of all the observation pixel points in the observation database is larger than a difference value, setting the abnormal pixel point as a post-fixed pixel point; if the difference between the pixel value of a certain abnormal pixel point and the pixel value of a certain observed pixel point in the observed database is smaller than or equal to the difference value, the abnormal pixel point is set as a front fixed pixel point, wherein when the certain pixel point is judged to be the abnormal pixel point, the abnormal pixel point is stored as the observed pixel point in the observed database;
if the ratio of the number of the superposition groups to the number of the observation groups in a certain superposition analysis zone is greater than or equal to a superposition duty ratio threshold, the lightning arrester is cleaned by transmitting information;
in a certain superposition analysis area, any two front fixed pixel points form a group of observation groups, and if only rear fixed pixel points exist on a connecting line of centers of the two front fixed pixel points of a certain group of observation groups, the group of observation groups is a superposition group.
4. A method of detecting a lightning arrester according to claim 3, wherein: the detection method further comprises the following steps: and when the cleaning lightning arrester is detected, the observation pixel points stored in the observation database are emptied.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101487866A (en) * | 2008-11-06 | 2009-07-22 | 姚建刚 | On-line detection method for AC power transmission line porcelain zero resistance insulator based on infrared thermal imaging |
| CN105184791A (en) * | 2015-09-02 | 2015-12-23 | 国网吉林省电力有限公司电力科学研究院 | Power transmission line video image insulator positioning method |
| CN106771806A (en) * | 2016-12-13 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | A kind of Voltage for Insulators on HV Lines surface filth state remote viewing method of telemetering and system |
| WO2019000653A1 (en) * | 2017-06-30 | 2019-01-03 | 清华大学深圳研究生院 | Image target identification method and apparatus |
| CN109324223A (en) * | 2018-07-30 | 2019-02-12 | 宜宾志源高压电器有限公司 | A kind of plateau type Zinc-Oxide Arrester on-line monitoring method |
| CN109900366A (en) * | 2019-03-22 | 2019-06-18 | 国网重庆市电力公司电力科学研究院 | A kind of method and device detecting arrester temperature anomaly point |
| CN111833312A (en) * | 2020-06-22 | 2020-10-27 | 国网江苏省电力有限公司电力科学研究院 | Ultraviolet image diagnosis method and system for detecting discharge of fault insulator |
| CN112578311A (en) * | 2020-12-01 | 2021-03-30 | 国网山东省电力公司电力科学研究院 | Lightning arrester leakage current detection device and method |
| CN112800886A (en) * | 2021-01-16 | 2021-05-14 | 江苏霆善科技有限公司 | Face recognition system and method based on machine vision |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6880950B2 (en) * | 2017-04-05 | 2021-06-02 | 村田機械株式会社 | Depression detection device, transfer device, and recess detection method |
-
2021
- 2021-08-18 CN CN202110947871.4A patent/CN113610830B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101487866A (en) * | 2008-11-06 | 2009-07-22 | 姚建刚 | On-line detection method for AC power transmission line porcelain zero resistance insulator based on infrared thermal imaging |
| CN105184791A (en) * | 2015-09-02 | 2015-12-23 | 国网吉林省电力有限公司电力科学研究院 | Power transmission line video image insulator positioning method |
| CN106771806A (en) * | 2016-12-13 | 2017-05-31 | 国网山东省电力公司电力科学研究院 | A kind of Voltage for Insulators on HV Lines surface filth state remote viewing method of telemetering and system |
| WO2019000653A1 (en) * | 2017-06-30 | 2019-01-03 | 清华大学深圳研究生院 | Image target identification method and apparatus |
| CN109324223A (en) * | 2018-07-30 | 2019-02-12 | 宜宾志源高压电器有限公司 | A kind of plateau type Zinc-Oxide Arrester on-line monitoring method |
| CN109900366A (en) * | 2019-03-22 | 2019-06-18 | 国网重庆市电力公司电力科学研究院 | A kind of method and device detecting arrester temperature anomaly point |
| CN111833312A (en) * | 2020-06-22 | 2020-10-27 | 国网江苏省电力有限公司电力科学研究院 | Ultraviolet image diagnosis method and system for detecting discharge of fault insulator |
| CN112578311A (en) * | 2020-12-01 | 2021-03-30 | 国网山东省电力公司电力科学研究院 | Lightning arrester leakage current detection device and method |
| CN112800886A (en) * | 2021-01-16 | 2021-05-14 | 江苏霆善科技有限公司 | Face recognition system and method based on machine vision |
Non-Patent Citations (2)
| Title |
|---|
| 基于EEMD阈值的MOA避雷器泄漏电流去噪的研究;赵腾;姚毅;周芯竹;;科学技术与工程(第31期);全文 * |
| 输电线路绝缘子污闪预警与自动观测系统研制;刘晓华等;仪器仪表与分析监测(第3期);第1-2节 * |
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