CN111307267A - Conductor galloping monitoring method based on concentric circle detection - Google Patents

Conductor galloping monitoring method based on concentric circle detection Download PDF

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CN111307267A
CN111307267A CN201910811064.2A CN201910811064A CN111307267A CN 111307267 A CN111307267 A CN 111307267A CN 201910811064 A CN201910811064 A CN 201910811064A CN 111307267 A CN111307267 A CN 111307267A
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concentric circle
connected domain
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ith frame
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夏娜
徐思
吴振昊
何梦花
于洋
吴成
洪韵晴
江惠鹏
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Anhui Kampers Navigation Information Technology Co ltd
Intelligent Manufacturing Institute of Hefei University Technology
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    • G01H9/00—Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by using radiation-sensitive means, e.g. optical means
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Abstract

The invention discloses a conductor galloping monitoring method based on concentric circle detection, which comprises the steps of fixing a concentric circle object on a power transmission conductor, acquiring a video image containing the concentric circle object in real time by a camera, and calculating the central coordinate of the concentric circle object by identifying concentric circles in the image; the track of conductor galloping can be obtained by recording the change of the central coordinate, and the maximum amplitude of the conductor galloping and the main frequency of the conductor galloping are further calculated, so that the effect of dynamically monitoring the conductor galloping condition in real time is achieved.

Description

Conductor galloping monitoring method based on concentric circle detection
Technical Field
The invention belongs to the field of target detection on transmission conductors, and particularly relates to a conductor galloping monitoring method based on concentric circle detection, so that the galloping condition of the transmission conductors is obtained.
Background
The galloping of the transmission line conductor is a serious disaster which endangers the safe and stable operation of the transmission line, the galloping is a low-frequency and large-amplitude self-excited vibration generated under the excitation of wind when the conductor generates eccentric icing, and serious accidents such as tripping, hardware and insulator damage, strand breakage and wire breakage of the conductor, loosening and falling of a pole tower bolt, tower material damage, foundation damage, even tower falling and the like can be caused by the galloping, so that the safe operation of a power grid is seriously threatened.
The existing waving monitoring method is mainly based on an environment monitoring sensing network constructed by a wireless sensing technology, and has the defects of high power consumption, complex operation and the like, so that the existing waving monitoring method needs a battery or a direct-current power supply for power supply. This not only increases the cost, but is also limited by the battery life and is not suitable for long-term environmental monitoring.
Disclosure of Invention
The invention provides a conductor galloping monitoring method based on concentric circle detection to solve the defects in the prior art, so that the galloping condition of a transmission conductor can be automatically monitored, and the monitoring accuracy and effectiveness are ensured.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the invention relates to a conductor galloping monitoring method based on concentric circle detection, which is characterized by comprising the following steps of:
step 1, fixing a concentric circle object on a power transmission wire;
step 2, installing a camera on the electric power iron tower or the tower footing for acquiring the concentric circlesThe video image set of the object is denoted as T ═ T1,T2,…,Ti,…TN}，TiRepresenting the ith frame image; i is an element of [1, N ∈]N represents the total number of image frames;
step 3, processing a video image set containing the object in the shape of the concentric circle, detecting the target concentric circle, and calculating the center coordinate of the target concentric circle;
step 3.1, initializing i to 1;
step 3.2, the ith frame image TiConverting the RGB chromaticity diagram into an ith frame GRAY grayscale diagram;
3.3, performing median filtering processing on the I frame GRAY GRAY image to obtain a de-noised I frame GRAY image;
step 3.4, carrying out binarization processing on the i-th frame gray level image after denoising to obtain an i-th frame binary image Ti′；
3.5, repairing the image defect by using a graph expansion repairing algorithm;
defining a template E as a square or a circle with a reference point; the template E and the ith frame binary image T are combinedi' performing convolution processing to calculate the binary image T of the template E in the ith framei' maximum value of pixel point of middle coverage area, and assigning the maximum value of pixel point to binary image T of reference point in ith frameiPixels covered on, thereby obtaining a restored i-th frame binary image Ti″；
Step 3.6, defining ith frame image TiThe number of the target concentric circles finally detected in the process is miAnd initializing mi＝0；
Step 3.7, extracting the repaired ith frame binary image Ti"and form n closed regions, each of which is called a connected domain, and all connected domains are denoted as the ith connected domain set
Figure BDA0002185055100000021
Figure BDA0002185055100000022
Representing the i-th frame binaryImage Ti"the r-th connected domain;
step 3.7.1, initializing r to 1;
step 3.7.2, drawing the r-th connected domain
Figure BDA0002185055100000023
Minimum circumscribed rectangle of
Figure BDA0002185055100000024
Step 3.7.3, calculating the r-th connected domain according to the formula (1)
Figure BDA0002185055100000025
At its smallest circumscribed rectangle
Figure BDA0002185055100000026
Filling rate of
Figure BDA0002185055100000027
Figure BDA0002185055100000028
In the formula (1), the reaction mixture is,
Figure BDA0002185055100000029
is the r-th connected domain
Figure BDA00021850551000000210
The area of (a) is,
Figure BDA00021850551000000211
is the r-th connected domain
Figure BDA00021850551000000212
The area of the minimum circumscribed rectangle of (2);
step 3.7.4, judging the r-th connected domain by using the formula (2)
Figure BDA00021850551000000213
Whether the candidate concentric circle is determined;if equation (2) is satisfied, the r-th connected domain is retained
Figure BDA00021850551000000214
As candidate concentric circles, and performs step 3.7.5; otherwise, the r-th connected domain
Figure BDA00021850551000000215
After rejection, go to step 3.7.7;
Figure BDA00021850551000000216
in the formula (2), muiFor the restored ith frame binary image Ti"fill ratio tolerance factor;
step 3.7.5, calculating the r-th connected domain according to the formula (3)
Figure BDA00021850551000000217
Minimum circumscribed rectangle of
Figure BDA00021850551000000218
Aspect ratio of
Figure BDA00021850551000000219
Figure BDA00021850551000000220
In the formula (3), the reaction mixture is,
Figure BDA00021850551000000221
is the r-th connected domain
Figure BDA00021850551000000222
Is the length of the smallest circumscribed rectangle of (a),
Figure BDA00021850551000000223
is the r-th connected domain
Figure BDA00021850551000000224
The width of the minimum bounding rectangle of (a);
step 3.7.6, judging the r-th connected domain according to the formula (4)
Figure BDA0002185055100000031
Whether it is a target concentric circle; if equation (4) is satisfied, it indicates the r-th connected domain
Figure BDA0002185055100000032
Is a target concentric circle, mi+1 assignment to mi(ii) a Otherwise, the r-th connected domain
Figure BDA0002185055100000033
Removing;
SCi∈[1-νi,1+νi](4)
in the formula (4), viFor the restored ith frame binary image Ti"aspect ratio tolerance coefficient;
step 3.7.7, assigning r +1 to r, and judging whether r is greater than n; if yes, the method represents the repaired ith frame binary image TiIn which m is obtainediExecuting step 3.8 for the target concentric circles corresponding to the connected domains; otherwise, returning to the step 3.7.2;
step 3.8, utilizing game tolerance coefficient strategies shown in the formulas (5), (6) and (7) to repair the ith frame binary image Ti"fill ratio tolerance factor muiAnd an aspect ratio tolerance coefficient viPerforming dynamic adjustment to obtain the (i + 1) th frame binary image Ti+1"fill ratio tolerance factor mui+1And an aspect ratio tolerance coefficient vi+1；
μi+1＝μi+I(·)·Θμ(5)
vi+1＝vi+I(·)·Θν(6)
Figure BDA0002185055100000034
In the formulae (5), (6) and (7), thetaμIs a fill rate tolerance factor delta，ΘνIs the aspect ratio tolerance coefficient increment, I (-) is for the ith frame image TiNumber m of concentric circles of middle targetiThe sign function of (a); t is the number of circles contained in the concentric circle shape object;
step 3.9, calculating the center of the concentric circle;
respectively restoring the ith frame of binary image Ti"middle miThe center of the minimum circumscribed rectangle of the connected domain corresponding to each target concentric circle is used as the center of the marker, so that m is obtainediCenter coordinate of
Figure BDA0002185055100000037
Wherein (x)f,yf) Representing the repaired i-th frame binary image Ti"center coordinates of the f-th concentric circle; f is an element of [1, m ]i]；
Obtaining the repaired ith frame binary image T by using the formula (8)i"the average value of the center coordinates of all the target concentric circles and is used as the repaired i-th frame binary image Ti"center coordinates of the corresponding concentric markers, noted
Figure BDA0002185055100000036
Figure BDA0002185055100000035
Step 3.10, assigning i +1 to i, and judging whether i is greater than N; if yes, the center coordinate set of the concentric circle markers corresponding to the N frames of restored binary images is obtained
Figure BDA0002185055100000041
And executing the step 4; otherwise, returning to the step 3.2;
step 4, calculating the conductor galloping track;
using filtering algorithm to collect central coordinate
Figure BDA0002185055100000042
The smoothing process is carried out to carry out the smoothing process,thereby obtaining the conductor galloping track (X, Y);
step 5, calculating the maximum amplitude of conductor galloping;
calculating all coordinate points of the conductor galloping track (X, Y) and the reference coordinate (X) of the concentric circle shape object0,y0) The Euclidean distance between the two conductors is selected, and the maximum distance is used as the maximum amplitude of conductor galloping;
step 6, calculating the main frequency of conductor galloping;
performing data processing on all coordinate points of the conductor galloping track (X, Y) by adopting fast Fourier transform to obtain the dominant frequency of coordinate change, and taking the dominant frequency as the dominant frequency of conductor galloping; therefore, the monitoring of conductor galloping is realized.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention provides an image expansion repairing algorithm (IEIA) aiming at the defects of concentric circles on an image to repair the characteristic information of the concentric circle image, thereby improving the recognition rate of concentric circle shape objects.
2. Aiming at the problem of concentric circle image deformation caused by different shooting angles of a camera, the invention provides a Game Tolerance Coefficient (GTCS) strategy, which realizes dynamic screening of concentric circle structures and further improves the recognition rate of concentric circle morphological objects.
3. The invention makes full use of the geometrical characteristics of the concentric circle morphology objects to judge the concentric circles for many times, thereby improving the accuracy of concentric circle identification.
5. Compared with the traditional sensor measuring mode, the invention has the characteristics of high monitoring dynamic property, high detection precision and the like.
6. According to the invention, the concentric circle form object is arranged on the lead, and the movement track of the concentric circle is detected by an image recognition method, so that the galloping information of the lead is obtained. The shape object adopts black and white concentric circles in structure, so that the image detection is easy, and the method is suitable for the environment with poor light and complex image background.
Drawings
FIG. 1 is a schematic diagram of the monitoring system of the present invention;
FIG. 2 is a schematic view of a first class of concentric circles of the present invention;
FIG. 3 is a schematic view of a second type of concentric circles of the present invention;
FIG. 4 is a schematic diagram of the graph expansion repair algorithm (IEIA) of the present invention;
FIG. 5 is a flow chart of the method of the present invention;
reference numbers in the figures: 1 denotes a concentric circle shape object, 2 denotes a camera, 3 denotes a calculation module, 4 denotes a wireless communication module, and 5 denotes a remote monitoring center.
Detailed Description
In this embodiment, as shown in fig. 5, a conductor galloping monitoring method based on concentric circle detection is to install concentric circle form objects on a conductor and identify concentric circle structures in the form objects, and then grasp information such as a conductor galloping track, a maximum amplitude, a main frequency and the like by calculating a center coordinate of the conductor, so that a power transmission conductor is always within a monitoring range, and once the conductor galloping has an abnormal condition, the conductor galloping monitoring method can report in time, specifically, the method includes the following steps:
step 1, as shown in figure 1, fixing a concentric circle object on a transmission conductor, and suggesting to be arranged on a conductor sag point; the markers are concentric circles with black and white, such as a first kind of concentric circles as shown in fig. 2 and a second kind of concentric circles as shown in fig. 3;
step 2, installing a camera on the electric power iron tower or the tower footing and recording a video image set containing concentric circle objects as T ═ T1,T2,…,Ti,…TN}，TiRepresenting the ith frame image; i is an element of [1, N ∈]N represents the total number of image frames;
step 3, processing a video image set containing the object in the shape of the concentric circle, detecting the target concentric circle, and calculating the center coordinate of the target concentric circle;
step 3.1, initializing i to 1;
step 3.2, the ith frame image TiConverting the RGB chromaticity diagram into an ith frame GRAY grayscale diagram, wherein the grayscale range is 0-255;
3.3, performing median filtering processing on the I frame GRAY GRAY image to obtain a de-noised I frame GRAY image; the specific filtering process is as follows:
(1) a 3 x 3 template is roamed in the image, and the center of the template is superposed with a certain pixel of the image;
(2) arranging the corresponding gray values on the template into a line from small to large;
(3) assigning the intermediate value of these gray values to the pixel at the center position of the template;
(4) the template moves to the next position.
And 3.4, performing binarization processing on the denoised ith frame gray level image, wherein a formula is shown as a formula (1), and obtaining an ith frame binary image Ti′；
Figure BDA0002185055100000051
In the formula (1), src (x, y) is the gray value of each pixel point of the gray map, and the value is 0 to 255; m is a binary threshold value, and a proper value can be determined through experiments; dst (x, y) is the gray value of each pixel after binarization, and the value is 0 or 255. Because the form object adopts black and white concentric circles on the image, the outline is clear and the form is clear after binarization, and most dark backgrounds in the image are changed into black, so that the form of the concentric circles is highlighted.
3.5, repairing the image defect by using a graph expansion repairing algorithm;
aiming at the condition that the concentric circles in the binarized Image are possibly defective and broken, a graph expansion repairing algorithm (IEIA) is provided for restoring the forms of the concentric circles, and the specific steps are as follows:
defining a template E as a square or a circle with a reference point; the template E and the ith frame binary image Ti' performing convolution processing to calculate the template E in the ith frame of the binary image Ti' maximum value of pixel point of middle coverage area, and assigning the maximum value of pixel point to binary image T of reference point in ith frameiPixels covered thereby obtaining a repaired i-th frame binaryMaking images Ti″：
Figure BDA0002185055100000061
T in formula (2)i"is to binary image Ti' image after repair. The reference point in the template E is compared with the binary image Ti' if T, each pixel point is compared one by onei' intersection with E, then the binary image TiThe edge of' may be expanded to the boundary of the template E. The graph expansion repair process is shown in FIG. 4, in which the left side is a binary image Ti' and a template E with a reference point, and obtaining a right-side repaired image T after the expansion repairing processi″。
After the processing of the graph expansion repairing algorithm (IEIA), the fracture part of the concentric circle in the image can be repaired to obtain a complete concentric circle structure, and the quality of other local pictures in the image can be kept unaffected.
Step 3.6, defining ith frame image TiThe number of the target concentric circles finally detected in the process is miAnd initializing mi＝0；
Step 3.7, extracting the repaired ith frame binary image Ti"and form n closed regions, each of which is called a connected domain, and all connected domains are denoted as the ith connected domain set
Figure BDA0002185055100000062
Figure BDA0002185055100000063
Representing the i-th frame binary image Ti"the r-th connected domain;
step 3.7.1, initializing r to 1;
step 3.7.2, drawing the r-th connected domain
Figure BDA0002185055100000064
Minimum circumscribed rectangle of
Figure BDA0002185055100000065
Step 3.7.3, calculating the r-th connected domain according to the formula (3)
Figure BDA0002185055100000066
At its smallest circumscribed rectangle
Figure BDA0002185055100000067
Filling rate of
Figure BDA0002185055100000068
Figure BDA0002185055100000069
In the formula (3), the reaction mixture is,
Figure BDA00021850551000000610
is the r-th connected domain
Figure BDA00021850551000000611
The area of (a) is,
Figure BDA00021850551000000612
is the r-th connected domain
Figure BDA00021850551000000613
The area of the minimum circumscribed rectangle of (2);
step 3.7.4, judging the r-th connected domain by using the formula (4)
Figure BDA00021850551000000614
Whether the candidate concentric circle is determined; if equation (4) is satisfied, the r-th connected domain is retained
Figure BDA0002185055100000071
As candidate concentric circles, and performs step 3.7.5; otherwise, the r-th connected domain
Figure BDA0002185055100000072
After the removal of the waste water, the waste water is removed,step 3.7.7 is executed;
Figure BDA0002185055100000073
in the formula (4), muiFor the restored ith frame binary image Ti"fill ratio tolerance factor;
step 3.7.5, calculating the r-th connected domain according to the formula (5)
Figure BDA0002185055100000074
Minimum circumscribed rectangle of
Figure BDA0002185055100000075
Aspect ratio of
Figure BDA0002185055100000076
Figure BDA0002185055100000077
In the formula (5), the reaction mixture is,
Figure BDA0002185055100000078
is the r-th connected domain
Figure BDA0002185055100000079
Is the length of the smallest circumscribed rectangle of (a),
Figure BDA00021850551000000710
is the r-th connected domain
Figure BDA00021850551000000711
The width of the minimum bounding rectangle of (a);
step 3.7.6, determining the r-th connected domain according to the formula (6)
Figure BDA00021850551000000712
Whether it is a target concentric circle; when equation (6) is satisfied, it indicates the r-th connected domain
Figure BDA00021850551000000713
Is a target concentric circle, mi+1 assignment to mi(ii) a Otherwise, the r-th connected domain
Figure BDA00021850551000000714
Removing;
SCi∈[1-νi,1+νi](6)
in the formula (6), viFor the restored ith frame binary image Ti"aspect ratio tolerance coefficient;
step 3.7.7, assigning r +1 to r, and judging whether r is greater than n; if yes, the method represents the repaired ith frame binary image TiIn which m is obtainediExecuting step 3.8 for the target concentric circles corresponding to the connected domains; otherwise, returning to the step 3.7.2;
and 3.8, aiming at the problem of concentric circle image deformation caused by different shooting angles of the camera, providing a Game Tolerance Coefficient (GTCS) strategy to realize dynamic screening of concentric circle structures. Utilizing game tolerance coefficient strategies shown in the formulas (7), (8) and (9) to carry out the repairing on the ith frame binary image Ti"fill ratio tolerance factor muiAnd an aspect ratio tolerance coefficient viPerforming dynamic adjustment to obtain the (i + 1) th frame binary image Ti+1"fill ratio tolerance factor mui+1And an aspect ratio tolerance coefficient vi+1；
μi+1＝μi+I(·)·Θμ(7)
vi+1＝vi+I(·)·Θν(8)
Figure BDA00021850551000000715
In the formulae (7), (8) and (9), thetaμIs the fill ratio tolerance factor delta, ΘνIs the aspect ratio tolerance coefficient increment, I (-) is for the ith frame image TiNumber m of concentric circles of middle targetiThe sign function of (a); t is a circle included in the concentric circle form objectThe number of (a) is, for example, 3 as shown in fig. 2; concentric circles, T-4, are shown in fig. 3.
When m isiWhen T, the ith frame binary image Ti"fill ratio tolerance factor muiAnd an aspect ratio tolerance coefficient viNo adjustment will be made; when m isiWhen < T, mu is indicatediV and viThe setting of (A) is too harsh, and from the perspective of objective game, mu should be increased properlyiV and vi(ii) a When m isiWhen > T, it indicates thatiV and viThe setting of (1) is too loose, and from the perspective of objective game, mu should be properly reducediV and vi。
Step 3.9, calculating the center of the concentric circle;
respectively restoring the ith frame of binary image Ti"middle miThe center of the minimum circumscribed rectangle of the connected domain corresponding to each target concentric circle is used as the center of the marker, so that m is obtainediCenter coordinate of
Figure BDA0002185055100000085
Wherein (x)f,yf) Representing the repaired i-th frame binary image Ti"center coordinates of the f-th concentric circle; f is an element of [1, m ]i]；
Obtaining the repaired i frame binary image T by using the formula (10)i"the average value of the center coordinates of all the target concentric circles and is used as the repaired i-th frame binary image Ti"center coordinates of the corresponding concentric markers, noted
Figure BDA0002185055100000081
Figure BDA0002185055100000082
Step 3.10, assigning i +1 to i, and judging whether i is greater than N; if yes, the center coordinate set of the concentric circle markers corresponding to the N frames of restored binary images is obtained
Figure BDA0002185055100000083
And executing the step 4; otherwise, returning to the step 3.2;
step 4, calculating the conductor galloping track;
using filtering algorithm to collect central coordinate
Figure BDA0002185055100000084
Performing smoothing treatment to obtain conductor galloping tracks (X, Y);
step 5, calculating the maximum amplitude of conductor galloping;
calculating all coordinate points of the conductor galloping track (X, Y) and the reference coordinate (X) of the concentric circle shape object0,y0) The euclidean distance between them, and the maximum distance is selected as the maximum amplitude of wire waving (GMA);
step 6, calculating the main frequency of conductor galloping;
performing data processing on all coordinate points of the wire Galloping track (X, Y) by adopting fast Fourier transform to obtain a main frequency of coordinate change, and using the main frequency as a GMF (Galloping main frequency); therefore, the monitoring of conductor galloping is realized.

Claims (1)

1. A conductor galloping monitoring method based on concentric circle detection is characterized by comprising the following steps:
step 1, fixing a concentric circle object on a power transmission wire;
step 2, installing a camera on the electric power iron tower or the tower footing and obtaining a video image set containing the concentric circle form object as T ═ T { (T {)1,T2,…,Ti,…TN}，TiRepresenting the ith frame image; i is an element of [1, N ∈]N represents the total number of image frames;
step 3, processing a video image set containing the object in the shape of the concentric circle, detecting the target concentric circle, and calculating the center coordinate of the target concentric circle;
step 3.1, initializing i to 1;
step 3.2, the ith frame image TiFrom RGB chromaticity diagramsForming an ith frame GRAY GRAY level image;
3.3, performing median filtering processing on the I frame GRAY GRAY image to obtain a de-noised I frame GRAY image;
step 3.4, carrying out binarization processing on the i-th frame gray level image after denoising to obtain an i-th frame binary image Ti′；
3.5, repairing the image defect by using a graph expansion repairing algorithm;
defining a template E as a square or a circle with a reference point; the template E and the ith frame binary image T are combinedi' performing convolution processing to calculate the binary image T of the template E in the ith framei' maximum value of pixel point of middle coverage area, and assigning the maximum value of pixel point to binary image T of reference point in ith frameiPixels covered on, thereby obtaining a restored i-th frame binary image Ti″；
Step 3.6, defining ith frame image TiThe number of the target concentric circles finally detected in the process is miAnd initializing mi＝0；
Step 3.7, extracting the repaired ith frame binary image Ti"and form n closed regions, each of which is called a connected domain, and all connected domains are denoted as the ith connected domain set
Figure FDA0002185055090000011
Figure FDA0002185055090000012
Representing the i-th frame binary image Ti"the r-th connected domain;
step 3.7.1, initializing r to 1;
step 3.7.2, drawing the r-th connected domain
Figure FDA0002185055090000013
Minimum circumscribed rectangle of
Figure FDA0002185055090000014
Step 3.7.3, calculating the r-th connected domain according to the formula (1)
Figure FDA0002185055090000015
At its smallest circumscribed rectangle
Figure FDA0002185055090000016
Filling rate of
Figure FDA0002185055090000017
Figure FDA0002185055090000018
In the formula (1), the reaction mixture is,
Figure FDA0002185055090000019
is the r-th connected domain
Figure FDA00021850550900000110
The area of (a) is,
Figure FDA00021850550900000111
is the r-th connected domain
Figure FDA00021850550900000112
The area of the minimum circumscribed rectangle of (2);
step 3.7.4, judging the r-th connected domain by using the formula (2)
Figure FDA00021850550900000113
Whether the candidate concentric circle is determined; if equation (2) is satisfied, the r-th connected domain is retained
Figure FDA0002185055090000021
As candidate concentric circles, and performs step 3.7.5; otherwise, the r-th connected domain
Figure FDA0002185055090000022
After rejection, go to step 3.7.7;
Figure FDA0002185055090000023
in the formula (2), muiFor the restored ith frame binary image Ti"fill ratio tolerance factor;
step 3.7.5, calculating the r-th connected domain according to the formula (3)
Figure FDA0002185055090000024
Minimum circumscribed rectangle of
Figure FDA0002185055090000025
Aspect ratio of
Figure FDA0002185055090000026
Figure FDA0002185055090000027
In the formula (3), the reaction mixture is,
Figure FDA0002185055090000028
is the r-th connected domain
Figure FDA0002185055090000029
Is the length of the smallest circumscribed rectangle of (a),
Figure FDA00021850550900000210
is the r-th connected domain
Figure FDA00021850550900000211
The width of the minimum bounding rectangle of (a);
step 3.7.6, judging the r-th connected domain according to the formula (4)
Figure FDA00021850550900000212
Whether it is a target concentric circle; if equation (4) is satisfied, it indicates the r-th connected domain
Figure FDA00021850550900000213
Is a target concentric circle, mi+1 assignment to mi(ii) a Otherwise, the r-th connected domain
Figure FDA00021850550900000214
Removing;
SCi∈[1-νi,1+νi](4)
in the formula (4), viFor the restored ith frame binary image Ti"aspect ratio tolerance coefficient;
step 3.7.7, assigning r +1 to r, and judging whether r is greater than n; if yes, the method represents the repaired ith frame binary image TiIn which m is obtainediExecuting step 3.8 for the target concentric circles corresponding to the connected domains; otherwise, returning to the step 3.7.2;
step 3.8, utilizing game tolerance coefficient strategies shown in the formulas (5), (6) and (7) to repair the ith frame binary image Ti"fill ratio tolerance factor muiAnd an aspect ratio tolerance coefficient viPerforming dynamic adjustment to obtain the (i + 1) th frame binary image Ti+1"fill ratio tolerance factor mui+1And an aspect ratio tolerance coefficient vi+1；
μi+1＝μi+I(·)·Θμ(5)
vi+1＝vi+I(·)·Θν(6)
Figure FDA00021850550900000215
In the formulae (5), (6) and (7), thetaμIs the fill ratio tolerance factor delta, ΘνIs the aspect ratio tolerance coefficient increment, I (-) is for the ith frame image TiNumber m of concentric circles of middle targetiThe sign function of (a); t is contained in the concentric formThe number of circles;
step 3.9, calculating the center of the concentric circle;
respectively restoring the ith frame of binary image Ti"middle miThe center of the minimum circumscribed rectangle of the connected domain corresponding to each target concentric circle is used as the center of the marker, so that m is obtainediCenter coordinate of
Figure FDA0002185055090000031
Wherein (x)f,yf) Representing the repaired i-th frame binary image Ti"center coordinates of the f-th concentric circle; f is an element of [1, m ]i]；
Obtaining the repaired ith frame binary image T by using the formula (8)i"the average value of the center coordinates of all the target concentric circles and is used as the repaired i-th frame binary image Ti"center coordinates of the corresponding concentric markers, noted
Figure FDA0002185055090000032
Figure FDA0002185055090000033
Step 3.10, assigning i +1 to i, and judging whether i is greater than N; if yes, the center coordinate set of the concentric circle markers corresponding to the N frames of restored binary images is obtained
Figure FDA0002185055090000034
And executing the step 4; otherwise, returning to the step 3.2;
step 4, calculating the conductor galloping track;
using filtering algorithm to collect central coordinate
Figure FDA0002185055090000035
Performing smoothing treatment to obtain conductor galloping tracks (X, Y);
step 5, calculating the maximum amplitude of conductor galloping;
calculating all coordinate points of the conductor galloping track (X, Y) and the reference coordinate (X) of the concentric circle shape object0,y0) The Euclidean distance between the two conductors is selected, and the maximum distance is used as the maximum amplitude of conductor galloping;
step 6, calculating the main frequency of conductor galloping;
performing data processing on all coordinate points of the conductor galloping track (X, Y) by adopting fast Fourier transform to obtain the dominant frequency of coordinate change, and taking the dominant frequency as the dominant frequency of conductor galloping; therefore, the monitoring of conductor galloping is realized.
CN201910811064.2A 2019-08-30 2019-08-30 Conductor galloping monitoring method based on concentric circle detection Pending CN111307267A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112284287A (en) * 2020-09-24 2021-01-29 哈尔滨工业大学 Stereoscopic vision three-dimensional displacement measurement method based on structural surface gray scale characteristics
CN114219696A (en) * 2021-11-09 2022-03-22 国网江苏省电力有限公司盐城供电分公司 Line galloping real-time video monitoring system based on FPGA and DSP

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112284287A (en) * 2020-09-24 2021-01-29 哈尔滨工业大学 Stereoscopic vision three-dimensional displacement measurement method based on structural surface gray scale characteristics
CN112284287B (en) * 2020-09-24 2022-02-11 哈尔滨工业大学 Stereoscopic vision three-dimensional displacement measurement method based on structural surface gray scale characteristics
CN114219696A (en) * 2021-11-09 2022-03-22 国网江苏省电力有限公司盐城供电分公司 Line galloping real-time video monitoring system based on FPGA and DSP

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