CN116758423A - Power transmission line foreign matter detection method based on white point rate method - Google Patents
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Abstract
The invention discloses a transmission line foreign matter detection method based on a white point rate method, which comprises the following steps: 1, unmanned aerial vehicle inspection to obtain a power transmission line image of a target area; 2, the image preprocessing operation obtains a foreign matter identification early-stage image, and performs improved Otsu threshold segmentation and morphological closing operation; 3, obtaining an image of the power transmission line tending to be horizontal through inclination correction of the image; detecting straight lines of Hough transformation of the corrected image area, and screening out a power transmission line; 4, carrying out outline frame selection and screening on the corrected image through a minimum circumscribed rectangle; and 5, judging contour type information through the ordinate position of the contour of the power transmission line, counting the internal white point of the contour, and outputting the contour type of the corresponding foreign matter to the contour conforming to the white point rate. The invention can realize the distinguishing and identification of the foreign matters attached to the transmission line and the suspended foreign matters, thereby reducing the leakage error detection caused by the attachment of the foreign matters during the inspection and providing effective support for the inspection fault analysis of the transmission line.
Description
Technical Field
The invention relates to the field of image processing, in particular to a transmission line foreign matter detection method based on a white point rate method.
Background
The power transmission line is a main carrier for power transmission and plays an important role in the stable and safe operation of the power transmission system. The transmission line can be exposed to nature and receive various influences, and wherein the foreign matter on the transmission line can to a great extent influence the normal work of transmission line, and especially the foreign matter that hangs on the transmission line is short from ground more easily causes power failure or incident. It is therefore extremely important to identify foreign matter on the transmission line.
The existing foreign matter inspection method is mainly a manual line inspection method, however, with the development of high-voltage, high-power and long-distance transmission lines, the geographical environment of transmission network crossing is increasingly complex, and the foreign matter inspection by means of manual line inspection is becoming harder and harder. In order to reduce the working intensity and improve the working efficiency, in recent years, it has appeared that an image of a transmission line is acquired by an unmanned aerial vehicle carrying optical equipment by using an aircraft as a carrier, and a large amount of image data carried back by inspection is intelligently processed by a computer to determine whether a foreign matter exists on the line.
At present, the conventional image processing algorithm has the problems of high recognition error rate and poor detection of suspended foreign matters of the power transmission line in image foreign matter recognition when judging the foreign matters on the power transmission line.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a transmission line foreign matter detection method based on a white point rate method, so as to effectively identify the attached foreign matter and hanging foreign matter of a transmission line, reduce the leakage error detection caused by the attachment of the foreign matter during inspection, and provide effective support for inspection fault analysis of the transmission line.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the invention discloses a transmission line foreign matter detection method based on a white point rate method, which is characterized by comprising the following steps of:
step 1, carrying a camera and data transmission equipment by an unmanned aerial vehicle to patrol and examine a power transmission line, acquiring a power transmission line image of a target area, and transmitting the power transmission line image to a foreign matter detection system at the ground end;
step 2, after performing image preprocessing operation on the received power transmission line image of the target area by the foreign matter detection system, obtaining a foreign matter identification early-stage image, wherein the preprocessing operation comprises the following steps: weight gray scale processing and median filtering;
step 3, performing improved Otsu threshold segmentation on the early-stage foreign object identification image to obtain a binary image; performing morphological closing operation on the binary image to obtain a denoised binary image;
step 4, carrying out Hough transformation detection on the denoised binary image to obtain each power transmission line, and carrying out inclination correction on the denoised binary image by taking the rotation direction of the longest power transmission line as a standard to obtain a correction image of the power transmission line tending to be horizontal;
and 5, after Hough transformation is carried out on the corrected image, obtaining all straight line segments in the corrected image and carrying out straight line screening, wherein the operation of straight line segment screening comprises the following steps: the length and slope of the line;
step 6, carrying out ordinate statistics on the screened straight line segments, and defining a region between a minimum value and a maximum value of the ordinate as a power transmission line region;
step 7, after the communication area in the corrected image is subjected to frame selection of the minimum circumscribed rectangular outline, screening the framed outline, wherein the outline screening operation comprises the following steps: area of the profile and aspect ratio;
step 8, comparing the ordinate of the profile end point of the screened profile with the ordinate of the power transmission line region, if any one of the ordinate of the profile end points is in the range of the ordinate of the power transmission line region, the profile type is an adhesion profile, otherwise, the profile type is a suspension profile;
step 9, counting white points in the minimum circumscribed rectangular outline and then setting the number S of white points in the outline Fault Area S with outline cont Ratio between and act as white pointAnd setting different white point rates for the two divided outline types, and outputting the outline conforming to the corresponding white point rate to corresponding foreign matter types.
The transmission line foreign matter detection method based on the white rate method is also characterized in that the improved Otsu threshold segmentation process in the step 3 comprises the following steps:
step A1: the gray value of the foreign matter identification early image is divided into two types, namely the gray level is [0, k ]]Foreground part C of (2) 1 The gray level is [ k+1, L-1 ]]Background part C of (2) 2 The method comprises the steps of carrying out a first treatment on the surface of the k represents a set threshold value, and L represents the gray level number of the image;
let p A And p B Respectively represent C 1 And C 2 The proportion of all pixels in the foreign matter identification earlier image is that p A +p B =1; wherein p is i Represent C 1 Or C 2 The number of pixels with a middle gray level of i;
calculation C 1 Is the gray level average value of (2)And C 2 Gray mean value of->
Step A2: find the foreground part C 1 Intra-class variance of (v)And background part C 2 Intra-class variance of (v)Solving intra-class variance of foreign matter identification earlier-stage image>m is the gray average value of the foreign object identification earlier-stage image;
step A3: calculating the foreground part C after adding the intra-class variance 1 Average gray value of (a)And background part C 2 Is>Calculating the average gray value (m) of the foreign matter identification early image after adding the intra-class variance * ) 2 ＝(m 2 +θ)/2；
Step A4: calculating an optimal threshold t by using the method (1) for segmenting the foreign object identification early-stage image, and obtaining a binary image:
t＝ArgMax[P A ×(m A * -m * ) 2 +P B ×(m B * -m * ) 2 ] (1)
in the formula (1), argMax represents an operation of obtaining the maximum value.
The screening in the step 5 is carried out according to the following process:
for any jth straight line segment l in the rectified image j Slope k of (2) i When k is i ∈[-δ,δ]When the jth straight line segment l is reserved j Otherwise, remove the jth straight line segment l j The method comprises the steps of carrying out a first treatment on the surface of the Wherein δ represents a slope screening threshold;
calculate the j-th straight line segment l j Length L of (2) j Screening by using the screening condition shown in the formula (2), if the formula (2) is satisfied, retaining the j-th straight line segment l j Otherwise, remove the jth straight line segment l j ；
In the formula (2), n represents the number of acquired straight-line segments.
The electronic device of the present invention includes a memory and a processor, wherein the memory is configured to store a program for supporting the processor to execute the transmission line foreign matter detection method, and the processor is configured to execute the program stored in the memory.
The invention relates to a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to execute the steps of the transmission line foreign matter detection method.
Compared with the prior art, the invention has the beneficial effects that:
1. the method provided by the invention can accurately identify the transmission line tending to the horizontal direction, and provides a new thought for detecting the position of the transmission line and foreign matter faults in power inspection.
2. The invention realizes the identification of the attached foreign matters and the suspended foreign matters under the complex background, provides a new solution for simultaneously identifying the two foreign matters of the power transmission line, perfects the intelligent inspection of the power transmission line and promotes the development of the detection and identification directions of the foreign matters of the power transmission line.
Drawings
Fig. 1 is a flowchart of a method for identifying foreign matters in a power transmission line according to the present invention.
Detailed Description
In this embodiment, referring to fig. 1, a method for detecting a foreign object on a power transmission line based on a white point rate method includes the following steps:
step A: the foreign matter detection system is used for carrying a camera and data transmission equipment by the unmanned aerial vehicle to patrol the power transmission line, acquiring a power transmission line image of a target area and transmitting the power transmission line image to the ground end;
and (B) step (B): the foreign matter detection system performs image preprocessing operation on the received power transmission line image of the target area to obtain a foreign matter identification early-stage image, wherein the preprocessing operation comprises the following steps: weight gray scale processing and median filtering;
in this embodiment, the weighted gray scale processing is to convert an image from an RGB image to a gray scale image, as shown in formula (3):
I(x,y)＝0.299R(x,y)+0.578G(x,y)+0.144B(x,y) (3)
in the formula (3), I (x, y) represents a gray value, and R (x, y), G (x, y) and B (x, y) represent values of three channels of red, green and blue of the pixel, respectively, and the values range from 0 to 255.
The method for processing the median filtering image comprises the following steps:
a fixed size window kernel is selected, typically with a median filtered window size that is odd, e.g., 3 x 3,5 x 5 squares, etc. And sequencing the pixel points in the window kernel range, and taking the intermediate value as the gray value of the pixel.
Step C: performing improved Otsu threshold segmentation on the early-stage foreign object identification image to obtain a binary image; performing morphological closing operation on the binary image to obtain a denoised binary image;
step C1: the gray value of the foreign matter identification early image is divided into two types, namely the gray level is [0, k ]]Foreground part C of (2) 1 The gray level is [ k+1, L-1 ]]Background part C of (2) 2 The method comprises the steps of carrying out a first treatment on the surface of the k represents a set threshold value, and L represents the gray level number of the image;
let p A And p B Respectively represent C 1 And C 2 The proportion of all pixels in the foreign matter identification earlier image is that p A +p B =1; wherein p is i Represent C 1 Or C 2 The number of pixels with a middle gray level of i;
calculation C 1 Is the gray level average value of (2)And C 2 Gray mean value of->
Step C2: find the foreground part C 1 Intra-class variance of (v)And background part C 2 Intra-class variance of (v)Solving intra-class variance of foreign matter identification earlier-stage image>m is the gray average value of the foreign object identification earlier-stage image;
step C3: calculating the foreground part C after adding the intra-class variance 1 Average gray value of (a)And background part C 2 Is>Calculating the average gray value (m) of the foreign matter identification early image after adding the intra-class variance * ) 2 ＝(m 2 +θ)/2；
Step C4: calculating an optimal threshold t by using the method (1) for segmenting the foreign object identification early-stage image, and obtaining a binary image:
t＝ArgMax[P A ×(m A * -m * ) 2 +P B ×(m B * -m * ) 2 ] (1)
in the formula (1), argMax represents an operation of obtaining the maximum value.
The morphological closing operation is shown in formula (4):
in the formula (4), a is a pre-processing image, and B is a processing structural element.
In the specific implementation, the expansion operation of the structural element B is performed on the original image, then the corrosion operation of the same structural element B is performed, and the structural element B is a flat disc structure with the radius of 3.
Step D: performing Hough transformation detection on the denoised binary image to obtain each power transmission line, and performing inclination correction on the denoised binary image by taking the rotation direction of the longest power transmission line as a standard to obtain a correction image of which the power transmission line tends to be horizontal;
the specific inclination correction method in the step D comprises the following steps:
step D1: carrying out Canny edge detection on the binary image to obtain an edge map of the image;
step D2: detecting a power transmission line in the image through Hough transformation;
step D3: and (3) taking the rotation direction of the longest transmission line as a standard, and performing inclination correction on the denoised binary image.
Step E: after Hough transformation is carried out on the corrected image, all straight line segments in the corrected image are obtained, and straight line screening is carried out, wherein the operation of straight line segment screening comprises the following steps: the length and slope of the line;
the straight line segment screening is carried out according to the following process:
e1: for any jth straight line segment l in the rectified image j Slope k of (2) i When k is i ∈[-δ,δ]When the jth straight line segment l is reserved j Otherwise, remove the jth straight line segment l j The method comprises the steps of carrying out a first treatment on the surface of the Wherein δ represents a slope screening threshold; in this embodiment, δ=0.2;
e2: calculate the j-th straight line segment l j Length L of (2) j Screening by using the screening condition shown in the formula (2), if the formula (2) is satisfied, retaining the j-th straight line segment l j Otherwise, remove the jth straight line segment l j ；
In the formula (2), n represents the number of acquired straight-line segments.
Step F: carrying out ordinate statistics on the screened straight line segments, and defining a region between a minimum value and a maximum value of the ordinate as a power transmission line region; the extraction of the ordinate of the straight line segment comprises the following steps:
f1: taking a two-dimensional image with the size of M x N as a rectangular coordinate system with an origin at the upper left corner;
f2: extracting the straight line segment l of each power transmission line i Endpoint coordinates (x) i ,y i ) Is y of the ordinate of (2) i ；
F3: the ordinate y of the power line in the image is calculated i The range between the minimum value to the maximum value of (c) is defined as the transmission line area.
Step G: after the communication area in the corrected image is subjected to frame selection of the minimum circumscribed rectangular outline, the selected outline is screened, and the outline screening operation comprises the following steps: area and aspect ratio of the profile;
the screening step of the circumscribed rectangular outline in the step G is as follows:
g1: area S is carried out on each minimum circumscribed rectangular outline cont And according to the screening condition, 1500.ltoreq.S cont Screening is carried out at a speed of less than or equal to 35000, and only the minimum circumscribed rectangular outline meeting the conditions is reserved;
and G2: and then calculating the width-to-length ratio w/h of each minimum circumscribed rectangular outline, and screening according to the width-to-length ratio screening condition that w/h is more than or equal to 0 and less than or equal to 7.
Step H: the ordinate y of the contour endpoint of the contour after screening cont Counting, comparing the ordinate value with the ordinate of the power transmission line region, if any one of the ordinate values of the four endpoints of the profile is in the range of the ordinate of the power transmission line region, indicating that the type of the corresponding profile is an adhesion type profile, otherwise, indicating that the type of the corresponding profile is a suspension type profile;
step I: after counting the white points in the minimum external rectangular outline, obtaining the statistic value S of the white pixel points in the outline Fault The method comprises the steps of carrying out a first treatment on the surface of the Setting the number S of white pixel points in the outline Fault Area S with outline cont Ratio S between Fault /S cont And as white point rate, setting different white point rates for the two contour types after division, wherein the white point rate judgment condition of the suspended foreign matter is set to be more than or equal to 0.35, and the suspended foreign matter is attached to the two contour typesThe white point rate judgment condition of the foreign matter is set to be more than or equal to 0.15; and outputting the outline conforming to the corresponding white point rate to corresponding foreign matter types, otherwise, deleting the corresponding outline.
In this embodiment, an electronic device includes a memory for storing a program supporting the processor to execute the above method, and a processor configured to execute the program stored in the memory.
In this embodiment, a computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method described above.
Claims (5)
1. The method for detecting the foreign matters of the power transmission line based on the white point rate method is characterized by comprising the following steps of:
step 1, carrying a camera and data transmission equipment by an unmanned aerial vehicle to patrol and examine a power transmission line, acquiring a power transmission line image of a target area, and transmitting the power transmission line image to a foreign matter detection system at the ground end;
step 2, after performing image preprocessing operation on the received power transmission line image of the target area by the foreign matter detection system, obtaining a foreign matter identification early-stage image, wherein the preprocessing operation comprises the following steps: weight gray scale processing and median filtering;
step 3, performing improved Otsu threshold segmentation on the early-stage foreign object identification image to obtain a binary image; performing morphological closing operation on the binary image to obtain a denoised binary image;
step 4, carrying out Hough transformation detection on the denoised binary image to obtain each power transmission line, and carrying out inclination correction on the denoised binary image by taking the rotation direction of the longest power transmission line as a standard to obtain a correction image of the power transmission line tending to be horizontal;
and 5, after Hough transformation is carried out on the corrected image, obtaining all straight line segments in the corrected image and carrying out straight line screening, wherein the operation of straight line segment screening comprises the following steps: the length and slope of the line;
step 6, carrying out ordinate statistics on the screened straight line segments, and defining a region between a minimum value and a maximum value of the ordinate as a power transmission line region;
step 7, after the communication area in the corrected image is subjected to frame selection of the minimum circumscribed rectangular outline, screening the framed outline, wherein the outline screening operation comprises the following steps: area of the profile and aspect ratio;
step 8, comparing the ordinate of the profile end point of the screened profile with the ordinate of the power transmission line region, if any one of the ordinate of the profile end points is in the range of the ordinate of the power transmission line region, the profile type is an adhesion profile, otherwise, the profile type is a suspension profile;
step 9, counting white points in the minimum circumscribed rectangular outline and then setting the number S of white points in the outline Fault Area S with outline cont And setting different white point rates for the two divided outline types as white point rates, and outputting the outline conforming to the corresponding white point rate to corresponding foreign matter types.
2. The method for detecting foreign matter on a transmission line based on the white-rate method according to claim 1, wherein the improved Otsu threshold segmentation process in step 3 includes the steps of:
step A1: the gray value of the foreign matter identification early image is divided into two types, namely the gray level is [0, k ]]Foreground part C of (2) 1 The gray level is [ k+1, L-1 ]]Background part C of (2) 2 The method comprises the steps of carrying out a first treatment on the surface of the k represents a set threshold value, and L represents the gray level number of the image;
let p A And p B Respectively represent C 1 And C 2 The proportion of all pixels in the foreign matter identification earlier image is that p A +p B ＝1The method comprises the steps of carrying out a first treatment on the surface of the Wherein p is i Represent C 1 Or C 2 The number of pixels with a middle gray level of i;
calculation C 1 Is the gray level average value of (2)And C 2 Gray mean value of->
Step A2: find the foreground part C 1 Intra-class variance of (v)And background part C 2 Intra-class variance of (v)Solving intra-class variance of foreign matter identification earlier-stage image>m is the gray average value of the foreign object identification earlier-stage image;
step A3: calculating the foreground part C after adding the intra-class variance 1 Average gray value of (a)And background part C 2 Is>Calculating the average gray value (m) of the foreign matter identification early image after adding the intra-class variance * ) 2 ＝(m 2 +θ)/2；
Step A4: calculating an optimal threshold t by using the method (1) for segmenting the foreign object identification early-stage image, and obtaining a binary image:
t＝ArgMax[P A ×(m A * -m * ) 2 +P B ×(m B * -m * ) 2 ] (1)
in the formula (1), argMax represents an operation of obtaining the maximum value.
3. The method for detecting foreign matters in a power transmission line based on the white point rate method according to claim 1, wherein the screening in the step 5 is performed according to the following procedures:
for any jth straight line segment l in the rectified image j Slope k of (2) i When k is i ∈[-δ,δ]When the jth straight line segment l is reserved j Otherwise, remove the jth straight line segment l j The method comprises the steps of carrying out a first treatment on the surface of the Wherein δ represents a slope screening threshold;
calculate the j-th straight line segment l j Length L of (2) j Screening by using the screening condition shown in the formula (2), if the formula (2) is satisfied, retaining the j-th straight line segment l j Otherwise, remove the jth straight line segment l j ；
In the formula (2), n represents the number of acquired straight-line segments.
4. An electronic device comprising a memory and a processor, wherein the memory is configured to store a program supporting the processor to execute the transmission line foreign matter detection method of any one of claims 1 to 3, the processor being configured to execute the program stored in the memory.
5. A computer readable storage medium having a computer program stored thereon, characterized in that the computer program when executed by a processor performs the steps of the transmission line foreign matter detection method of any one of claims 1 to 3.
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| CN117315515B (en) * | 2023-11-29 | 2024-03-15 | 深圳市大易电气实业有限公司 | Visual auxiliary inspection method and system for distribution line |
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