CN113744197A - Cable fault detection method based on red and ultraviolet composite imaging - Google Patents
Cable fault detection method based on red and ultraviolet composite imaging Download PDFInfo
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- CN113744197A CN113744197A CN202110908868.1A CN202110908868A CN113744197A CN 113744197 A CN113744197 A CN 113744197A CN 202110908868 A CN202110908868 A CN 202110908868A CN 113744197 A CN113744197 A CN 113744197A
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- 230000009466 transformation Effects 0.000 claims description 9
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- 238000003708 edge detection Methods 0.000 claims description 4
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Abstract
The invention relates to a cable fault detection method based on red and ultraviolet composite imaging, which adopts a red and ultraviolet composite flame detector to acquire images of a cable line, decomposes the images into a red and ultraviolet image and a visible light shadow image, screens the red and ultraviolet image, synthesizes the red and ultraviolet image and the visible light shadow image, and screens the images again to obtain a suspected fault cable line image; noise reduction and gray processing are carried out through an improved Roberts operator, a fractional Fourier transform in Matlab is used for processing, an accurate cable fault position point image is obtained, the technical scheme is adopted, the image acquisition is prevented from being influenced by field factors such as solar radiation, the fault position is more accurately determined, and fault identification and detection are carried out on cable lines in various underground environments and environments where personnel cannot easily reach.
Description
Technical Field
The invention relates to the technical field of cable detection, in particular to a cable fault detection method based on red and ultraviolet composite imaging.
Background
At present, the infrared thermal imaging technology and the visible light imaging technology are increasingly widely applied in electric power systems in China, and become necessary means for carrying out state inspection on electrical equipment. However, when the infrared detection of the electrical equipment is performed on the spot, the deviation between the measured fault point position and the actual fault point position is large due to the influence of the spot factors, such as solar radiation and the like.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the cable fault detection method based on the infrared and ultraviolet composite imaging, which can more accurately determine the position of the fault point, and can meet the requirements of fault identification and detection of cable lines in various underground environments and environments which are not easy to reach by personnel.
The invention discloses a cable fault detection method based on red and ultraviolet composite imaging, which comprises the following steps:
s1: the method comprises the following steps that a plurality of red and ultraviolet composite flame detectors which are uniformly distributed on a cable line section to be detected acquire images of the cable line to obtain a plurality of cable line images, and the cable line images are decomposed into red and ultraviolet images and visible light shadow images;
s2: screening the red-purple image to select a red-purple image of the cable line with obvious red-purple brightness;
s3, synthesizing the cable line red-purple image and the corresponding visible light image by using an image feature point matching method, and further screening the cable line image with obvious red-purple brightness to obtain a suspected fault cable line image;
s4: processing the suspected fault cable line image through an improved Roberts operator edge detection method to obtain a suspected fault cable line gradient value image;
s5: comparing the gradient threshold values of the suspected fault cable line gradient value image and the normal cable line gradient value image point by point and judging whether the cable line is in fault or not;
s6: and performing inverse transformation on the image of the cable line with the fault by using a fractional Fourier transform method to obtain an accurate image of the cable fault position point.
Further, in the step S3, a cable line image with a bright magenta color is further screened, the position of each 2 pixels is taken as a coordinate, the position of each 2 pixels is recorded and is subtracted from the next 2 pixels, the obtained temperature difference value is recorded as 1K1, all the pixels are searched, 3 pixels are taken as a group of data, a pixel S larger than 1K1 is searched, when the continuous groups of data are larger than 1K1, the region is determined as a position with a high temperature, and a suspected fault cable line image is obtained.
Further, the step S4 includes:
s4-1, adding noise on the basis of the suspected fault cable line image to obtain a suspected fault cable line image containing the noise;
s4-2, on the basis of a Roberts operator, detecting the gray scale edge of the suspected noisy cable line image by using a 4 x 4-order matrix operator template selected by a method of the difference between two pixels adjacent in the diagonal direction to obtain a suspected noisy edge faulty cable line image;
and S4-3, denoising the suspected fault cable line image with the noisy edge, and inversely transforming to obtain a gradient value image of the suspected fault cable line.
Further, the step S6 is implemented based on Matlab software, and includes the steps of:
s6-1, opening the gradient value image of the fault cable line in Matlab software;
s6-2, drawing a FRFT spectrum display function by using a function in an MATLAB toolbox;
s6-3, multiplying the FRFT spectrum display function and the filter function;
and S6-4, performing inverse transformation on the result of the S6-3, wherein the image information after inverse transformation has a light section with obviously high brightness, so that an accurate cable fault position point image is obtained.
Further, the filter function in the step S6-3 is a multi-stage filter function or a multi-channel filter function.
Compared with the prior art, the invention has the beneficial effects that: the cable line fault detection method has the advantages that the red ultraviolet composite flame detector is adopted to collect images of the cable line, the image collection is prevented from being influenced by field factors such as solar radiation, the Roberts operator edge detection method and the fractional Fourier transform method are used for processing collected cable line pictures, the position of a fault point is determined more accurately, and fault identification and detection of the cable line in various underground environments and environments where personnel cannot reach easily are met.
Drawings
The accompanying drawings, which are described herein to provide a further understanding of the application, are included in the following description:
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is an image of a suspected faulty cable run according to an embodiment of the present invention;
FIG. 3 is a gradient value image of a suspected faulty cable line according to an embodiment of the present invention;
fig. 4 is an image of a cable fault location point according to an embodiment of the present invention.
Detailed Description
Referring to fig. 1, in an embodiment, a cable fault detection method based on red-ultraviolet composite imaging includes the following steps:
s1: the method comprises the following steps that a plurality of red and ultraviolet composite flame detectors which are uniformly distributed on a cable line section to be detected acquire images of the cable line to obtain a plurality of cable line images, and the cable line images are decomposed into red and ultraviolet images and visible light shadow images;
s2: screening the red-purple image to select a red-purple image of the cable line with obvious red-purple brightness;
s3, synthesizing the cable line red-purple image and the corresponding visible light image by using an image feature point matching method, and further screening the cable line image with obvious red-purple brightness to obtain a suspected fault cable line image;
s4: processing the suspected fault cable line image through an improved Roberts operator edge detection method to obtain a suspected fault cable line gradient value image;
s5: comparing the gradient threshold values of the suspected fault cable line gradient value image and the normal cable line gradient value image point by point and judging whether the cable line is in fault or not;
s6: and performing inverse transformation on the image of the cable line with the fault by using a fractional Fourier transform method to obtain an accurate image of the cable fault position point.
Referring to fig. 2, further, in the step S3, a cable line image with obvious magenta and bright colors is further screened, the position of each 2 pixels is recorded as a coordinate, the difference is made between the position of each 2 pixels and the next 2 pixels, the obtained temperature difference value is recorded as 1K1, all the pixels are searched, 3 pixels are used as a group of data, a pixel S larger than 1K1 is searched, when consecutive groups of data are larger than 1K1, the region is determined as a position with high temperature, and a suspected fault cable line image is obtained.
Referring to fig. 3, further, the step S4 includes:
s4-1, adding noise on the basis of the suspected fault cable line image to obtain a suspected fault cable line image containing the noise;
s4-2, on the basis of a Roberts operator, detecting the gray scale edge of the suspected noisy cable line image by using a 4 x 4-order matrix operator template selected by a method of the difference between two pixels adjacent in the diagonal direction to obtain a suspected noisy edge faulty cable line image;
and S4-3, denoising the suspected fault cable line image with the noisy edge, and inversely transforming to obtain a gradient value image of the suspected fault cable line.
Referring to fig. 4, further, the step S6 is implemented based on Matlab software, and includes the steps of:
s6-1, opening the gradient value image of the fault cable line in Matlab software;
s6-2, drawing a FRFT spectrum display function by using a function in an MATLAB toolbox;
s6-3, multiplying the FRFT spectrum display function and the filter function;
and S6-4, performing inverse transformation on the result of the S6-3, wherein the image information after inverse transformation has a light section with obviously high brightness, so that an accurate cable fault position point image is obtained.
Further, the filter function in the step S6-3 is a multi-stage filter function or a multi-channel filter function.
The method has the working principle that the red-ultraviolet composite flame detector is adopted to collect images of the cable line, so that the image collection is prevented from being influenced by field factors such as solar radiation and the like, the images are decomposed into a red-purple image and a visible light shadow image, the red-purple image is screened, the red-purple image and the visible light shadow image are synthesized, and the suspected fault cable line image is obtained by screening again; noise reduction and graying are carried out through an improved Roberts operator, and gradient value images of suspected fault cable lines are processed through fractional order Fourier transform in Matlab, so that accurate cable fault position point images are obtained.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. A cable fault detection method based on red and ultraviolet composite imaging is characterized in that: which comprises the following steps:
s1: the method comprises the following steps that a plurality of red and ultraviolet composite flame detectors which are uniformly distributed on a cable line section to be detected acquire images of the cable line to obtain a plurality of cable line images, and the cable line images are decomposed into red and ultraviolet images and visible light shadow images;
s2: screening the red-purple image to select a red-purple image of the cable line with obvious red-purple brightness;
s3, synthesizing the cable line red-purple image and the corresponding visible light image by using an image feature point matching method, and further screening the cable line image with obvious red-purple brightness to obtain a suspected fault cable line image;
s4: processing the suspected fault cable line image through an improved Roberts operator edge detection method to obtain a suspected fault cable line gradient value image;
s5: comparing the gradient threshold values of the suspected fault cable line gradient value image and the normal cable line gradient value image point by point and judging whether the cable line is in fault or not;
s6: and performing inverse transformation on the image of the cable line with the fault by using a fractional Fourier transform method to obtain an accurate image of the cable fault position point.
2. The cable fault detection method based on red-ultraviolet composite imaging according to claim 1, characterized in that: and step S3, further screening out cable line images with obvious magenta brightness, recording the positions of every 2 pixels as coordinates, subtracting the positions of every 2 pixels from the next 2 pixels, recording the obtained temperature difference as 1K1, searching all the pixels, using 3 pixels as a group of data, searching for pixels S larger than 1K1, and when the continuous groups of data are larger than 1K1, determining that the area is a high-temperature position, and obtaining a suspected fault cable line image.
3. The cable fault detection method based on red-ultraviolet composite imaging according to claim 1, characterized in that: the step S4 includes:
s4-1, adding noise on the basis of the suspected fault cable line image to obtain a suspected fault cable line image containing the noise;
s4-2, on the basis of a Roberts operator, detecting the gray scale edge of the suspected noisy cable line image by using a 4 x 4-order matrix operator template selected by a method of the difference between two pixels adjacent in the diagonal direction to obtain a suspected noisy edge faulty cable line image;
and S4-3, denoising the suspected fault cable line image with the noisy edge, and inversely transforming to obtain a gradient value image of the suspected fault cable line.
4. The cable fault detection method based on red-ultraviolet composite imaging according to claim 1, characterized in that: the step S6 is implemented based on Matlab software, and includes the steps of:
s6-1, opening the gradient value image of the fault cable line in Matlab software;
s6-2, drawing a FRFT spectrum display function by using a function in an MATLAB toolbox;
s6-3, multiplying the FRFT spectrum display function and the filter function;
and S6-4, performing inverse transformation on the result of the S6-3, wherein the image information after inverse transformation has a light section with obviously high brightness, so that an accurate cable fault position point image is obtained.
5. The cable fault detection method based on red-ultraviolet composite imaging according to claim 4, wherein: the filter function in the step S6-3 is a multi-stage filter function or a multi-channel filter function.
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Cited By (1)
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| CN116823808A (en) * | 2023-08-23 | 2023-09-29 | 青岛豪迈电缆集团有限公司 | Intelligent detection method for cable stranded wire based on machine vision |
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