CN112489018A - Intelligent power line inspection method and inspection line - Google Patents
Intelligent power line inspection method and inspection line Download PDFInfo
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- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/0008—Industrial image inspection checking presence/absence
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
The invention discloses an intelligent power line inspection method and system, wherein the method comprises the following steps: formulating a line patrol path of the unmanned aerial vehicle photographic device, and acquiring a power line channel image by using the unmanned aerial vehicle photographic device; preprocessing the acquired power line channel image and obtaining an image to be detected; acquiring the position of a power line in an image to be detected; detecting an abnormal region in the power line position of an image to be detected, and marking the abnormal region in the image to be detected to generate an intermediate result image; and marking an abnormal area at a corresponding position in the power line channel image, and outputting the marked power line channel image. According to the embodiment of the invention, the speed of acquiring the power line channel image is improved by utilizing the unmanned aerial vehicle photographic device. According to the embodiment of the invention, the abnormal situation of the power line can be rapidly identified through preprocessing, power line edge extraction and abnormal area identification, so that the aim of reducing manual participation is fulfilled.
Description
Technical Field
The invention belongs to the field of power transmission, and particularly relates to an intelligent power line inspection method and system.
Background
With the rapid development of economy, the demand for electric energy is more and more vigorous, the electric power transmission system is more and more huge, and the coverage is more and more broad. The transmission line is an important component of the power transmission system, and is easy to have disconnection accidents and foreign matter adhesion accidents due to human damage, natural disasters or natural aging and the like.
Traditional transmission line patrols and examines mainly by artifical the completion, and artifical the patrolling and examining adopts the mode of climbing power line shaft tower, has very big potential safety hazard. The manual inspection is limited by geographical environment and physical ability of human body, so that the inspection efficiency is low, the real-time performance is poor, and the requirement of the conventional electric power inspection is difficult to meet. In addition, the manual power line inspection mode is usually observed by naked eyes, and whether a line has a fault or not is judged by experience, so that the fault is easily caused, and the accuracy is not high. In addition, also beginning now to look over with the help of unmanned aerial vehicle equipment assistance, but still through video monitoring, the mode of manual check is gone on, though personnel's security improves, because still be the manual work directly to image judgement, fault detection's efficiency still is low.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide an intelligent power line patrol method and system based on image processing. The intelligent line patrol method comprises the following steps:
step S1, formulating a line patrol path of the unmanned aerial vehicle photographic device according to the trend of the power line, and acquiring a power line channel image by using the unmanned aerial vehicle photographic device;
step S2, preprocessing the acquired power line channel image and obtaining an image to be detected;
step S3, carrying out power line edge extraction on the image to be detected so as to obtain the power line position of a power line in the image to be detected;
step S4, detecting a high-brightness area or a low-brightness area in the power line position of the image to be detected, marking the high-brightness area or the low-brightness area as an abnormal area, and marking the abnormal area in the image to be detected to generate an intermediate result image;
step S5, according to the intermediate result image, marking the abnormal region at the corresponding position in the power line channel image, and outputting the marked power line channel image.
Further, in step S2, the preprocessing the acquired powerline channel image includes: graying, optical correction and image denoising.
Wherein the step S3 includes:
step S31, detecting the edge of the power line in the image to be detected by using a Ratio operator;
and step S32, processing the power line channel image with the detected power line edge by using a random Hough transformation method of the gradient direction information.
Further, the step S4 includes:
step S41, performing region segmentation on the position of the power line in the image to be detected, and obtaining N segmented regions to be detected;
step S42, counting the number of pixel points of each gray level in each segmented region to be detected, and generating N statistical result data according to a one-to-one correspondence relationship;
step S43, calculating the average value of the total gray scale of N segmented regions to be detected by utilizing N statistical result data;
and step S44, comparing the N statistical results with the average value of the overall gray level one by one, and marking the segmented to-be-detected area with the difference value larger than a preset abnormal threshold as an abnormal area.
Further, the step of marking the abnormal region at the corresponding position in the power line channel image specifically includes the following steps: and filling the pixel points marked as the abnormal areas in the power line channel image into red, green or blue.
Further, in step S1, the routing path of the unmanned aerial vehicle photographing device is established according to the trend of the power line and implemented by a GPS navigation system or a beidou navigation system.
An intelligent power line patrol system, comprising:
the unmanned aerial vehicle photographing device is used for acquiring power line channel images according to a preset line patrol path, wherein the line patrol path is formulated according to the trend of a power line;
the image preprocessing unit is used for preprocessing the acquired power line channel image and acquiring an image to be detected;
the power line position acquisition unit is used for carrying out power line edge extraction on the image to be detected so as to acquire the power line position of a power line in the image to be detected;
the intermediate result image generating unit is used for detecting a high-brightness area or a low-brightness area in the power line position of the image to be detected, marking the high-brightness area or the low-brightness area as an abnormal area, and marking the abnormal area in the image to be detected to generate an intermediate result image;
and the marked image output unit is used for marking the abnormal area at the corresponding position in the power line channel image according to the intermediate result image and outputting the marked power line channel image.
Further, the image preprocessing unit preprocesses the acquired power line channel image, and specifically includes: graying, optical correction and image denoising.
Further, the power line position acquisition unit includes:
the power line edge detection subunit detects the power line edge in the image to be detected by using a Ratio operator;
and the power line position acquisition subunit processes the power line channel image with the edge of the detected power line by using a random Hough transformation method of the gradient direction information so as to acquire the power line position of the power line in the image to be detected.
Further, the intermediate result image generating unit includes:
the to-be-detected region generating subunit is used for performing region segmentation on the position of the power line in the to-be-detected image and obtaining N segmented to-be-detected regions;
a gray level pixel point counting subunit, configured to count the number of pixel points of each gray level in each segmented to-be-detected region, and generate N pieces of statistical result data according to a one-to-one correspondence relationship;
the gray level average value calculating operator unit is used for calculating the total gray level average value of the N segmented to-be-detected areas by utilizing the N statistical result data;
and the abnormal area marking subunit is used for comparing the N statistical results with the overall gray average value one by one, and marking the segmented to-be-detected area with the difference value larger than a preset abnormal threshold as an abnormal area.
The embodiment of the invention has the following beneficial effects: according to the embodiment of the invention, through the steps of preprocessing, power line edge extraction, abnormal area identification and the like, the situations of damage, foreign matter adhesion and the like in the power line can be quickly and accurately identified, the detection result can be visually output, an unmanned aerial vehicle photographing device is utilized in the whole process, and an automatic navigation cruise mode is combined, so that the operation accuracy can be effectively improved, the error caused by manual acquisition is avoided, the purpose of reducing the manual participation degree is achieved, and the indicative function can be provided for manual reinspection.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent power line inspection method according to a first embodiment of the present invention;
Detailed Description
The following description of the embodiments refers to the accompanying drawings, which are included to illustrate specific embodiments in which the invention may be practiced.
Referring to fig. 1, an embodiment of the invention provides an intelligent power line patrol method, which includes steps S1-S5.
And step S1, formulating a line patrol path of the unmanned aerial vehicle photographic device according to the trend of the power line, and acquiring the power line channel image by using the unmanned aerial vehicle photographic device.
Specifically, utilize unmanned aerial vehicle camera device to gather the image, the mode that uses most often just is that manual operation unmanned aerial vehicle camera device carries out the video shooting, but when shooing the power line, if adopt manual operation to shoot, though compare in the artifical mode of directly looking over at the scene, can save the manpower to a certain extent, but manual operation is difficult to keep the stable operation to unmanned aerial vehicle camera device, the shake appears easily, circumstances such as height or direction sudden change, and then can cause the power line passageway image of gathering to be fuzzy or undersize, lead to follow-up being difficult to directly be used for the power line profile to draw. Adopt navigation, can go on strict formulation to unmanned aerial vehicle photographic arrangement's the route of cruising according to the actual trend of power line, finally can let unmanned aerial vehicle photographic arrangement carry out the collection of power line channel image with a fixed speed, suitable relative highly delay the route of cruising as far as possible, and then guaranteed power line channel image quality.
Specifically, the line patrol path for formulating the unmanned aerial vehicle photographing device according to the trend of the power line is realized through a GPS navigation system or a Beidou navigation system, so that the cruise path can be effectively guaranteed not to deviate, or the deviation probability is reduced.
And step S2, preprocessing the acquired power line channel image and obtaining an image to be detected.
Specifically, the power line channel image is usually a color image after being acquired, and if the color image is directly utilized for processing, the data amount of the operation is too large due to too many features, so that the power line channel image needs to be subjected to operations such as graying processing, the converted image is the image to be detected, and the image to be detected is used for operation during actual operation, so that the algorithm is simplified. In some embodiments, in order to further reduce the data processing amount, the frame extraction processing is performed on the acquired power line channel image to reduce the number of pictures to be processed, and the frame extraction number is not too large to avoid missing the power line channel image.
Preprocessing the acquired power line channel image may include the steps of: graying, optical correction and image denoising. Because there may be problems such as jitter during the shooting process, it is necessary to perform preliminary processing on the image through steps such as optical correction and image denoising to ensure the overall display effect of the power line channel image. The graying processing can reduce the information amount in the picture, thereby reducing the difficulty of subsequent data processing.
And step S3, performing power line edge extraction on the image to be detected to acquire the power line position of the power line in the image to be detected.
Specifically, the power line edge information needs to be extracted from the image to be detected, and there are many ways to extract the image edge information from the grayscale image. After the extraction of the power line edge information is completed, the power line position is marked in the image to be detected, so that the subsequent abnormal area identification can be used.
Further, step S3 may include steps S31-S32.
Step S31, detecting the edge of the power line in the image to be detected by using a Ratio operator;
and step S32, processing the power line channel image with the detected power line edge by using a random Hough transformation method of the gradient direction information.
The power line edge can be detected in the image to be detected using the Ratio operator. However, the detected edge information may be affected by many factors, such as: the influence of the variation in the imaging height, the influence of the bending of the power line, and the influence of the position of the power line and the power tower. At this time, the random Hough transformation method using the gradient direction information is required to be further processed to obtain the final power line position
Step S4, detecting a high luminance region or a low luminance region in the power line position of the image to be detected, marking the high luminance region or the low luminance region as an abnormal region, and marking the abnormal region in the image to be detected to generate an intermediate result image.
Specifically, first, a simple introduction is made to the principle of abnormal region identification, and the power line is usually a fixed color (e.g., black) and is usually smooth in surface if a white object is attached thereto, such as: the gray scale of the bird excrement is different from that of the power line of other areas, and the gray scale of the bird excrement is lower, so that whether foreign matters or damage are attached to the power line can be judged. In a specific area, it is a common technology to identify a high-brightness area and a low-brightness area, both the high-brightness area and the low-brightness area can be understood as having an abnormality, and after the abnormality occurs, the abnormal area needs to be marked in the image to be detected to generate an intermediate result image. The high-brightness region and the low-brightness region are divided into different standards, and adjustment is usually realized by setting different thresholds. In actual engineering, before formal fault detection, engineers will adjust the threshold to achieve the best discrimination effect.
In some embodiments, step S4 includes steps S41-S44.
Step S41, performing region segmentation on the power line position in the image to be detected, and obtaining N segmented regions to be detected;
step S42, counting the number of pixel points of each gray level in each subsection to-be-detected area, and generating N statistical result data according to a one-to-one correspondence relationship;
step S43, calculating the average value of the total gray scale of N segmented regions to be detected by using N statistical result data;
and step S44, comparing the N statistical results with the average value of the overall gray level one by one, and marking the segmented to-be-detected area with the difference value larger than a preset abnormal threshold as an abnormal area.
There are many methods for extracting high-luminance points and low-luminance points from a picture. A simpler method is used here on the basis of the image to be detected. After the power line position is acquired, this region can be subjected to a separate data processing in the image to be detected, without any further consideration of the information of other regions in the image to be detected. The power line position in the image to be detected is firstly segmented to obtain N segmented regions to be detected, wherein the segmented regions can be directly partitioned along the power line, and the quantity of pixel points in each segmented region to be detected is ensured to be consistent as much as possible. Because the image to be detected is a gray image, the number of pixel points of each gray level in each segmented to-be-detected region can be counted, then the region average gray value of each segmented to-be-detected region can be calculated, the region average gray value is small for the segmented to-be-detected region with higher brightness, and the region average gray value is large for the segmented to-be-detected region with lower brightness. The average gray value of the areas of all the subsection to-be-detected areas is calculated, the average gray value of the overall gray value of all the subsection to-be-detected areas (namely the whole power line) is further calculated, the average gray value of the areas of all the subsection to-be-detected areas is compared with the average value of the overall gray value, and once the average gray value of the areas of all the subsection to-be-detected areas exceeds an abnormal threshold value, the areas can be judged to be abnormal. In some embodiments, two anomaly thresholds are set to identify high and low luminance regions, respectively.
In step S5, according to the intermediate result image, an abnormal region is marked at a corresponding position in the power line channel image, and the marked power line channel image is output.
Specifically, an abnormal area is just marked in the intermediate result image, in order to enable an engineer to visually see the abnormal area, the abnormal area marked by the intermediate result image is directly corresponding to the power line channel image and is marked in the same way, and finally the power line channel image marked with the abnormal area is output for the engineer to check.
The method specifically comprises the following steps of marking an abnormal area at a corresponding position in a power line channel image: and filling the pixel points marked as abnormal areas in the power line channel image into red, green or blue. In order to visually check the abnormal area, the abnormal area may be marked, and the mark may be marked with a wire frame or other special marks. The mode of directly filling the pixel points with larger identification degree is adopted, and the abnormal area can be known more vividly through the mode.
According to the intelligent power line patrol method provided by the embodiment of the invention, through the steps of preprocessing, power line edge extraction, abnormal area identification and the like, the situations of damage, foreign matter adhesion and the like in the power line can be rapidly and accurately identified, the detection result can also be visually output, an unmanned aerial vehicle photographing device is utilized in the whole process, and an automatic navigation cruise mode is combined, so that the operation accuracy can be effectively improved, the error caused by manual acquisition is avoided, the purpose of reducing the manual participation degree is achieved, and the indicative function can be provided for manual review.
Corresponding to the intelligent power line patrol method provided by the first embodiment of the present invention, a second embodiment of the present invention further provides an intelligent power line patrol system, which is characterized by comprising:
the unmanned aerial vehicle photographing device is used for acquiring power line channel images according to a preset line patrol path, wherein the line patrol path is formulated according to the trend of a power line;
the image preprocessing unit is used for preprocessing the acquired power line channel image and acquiring an image to be detected;
the power line position acquisition unit is used for carrying out power line edge extraction on the image to be detected so as to acquire the power line position of a power line in the image to be detected;
the intermediate result image generating unit is used for detecting a high-brightness area or a low-brightness area in the power line position of the image to be detected, marking the high-brightness area or the low-brightness area as an abnormal area, and marking the abnormal area in the image to be detected to generate an intermediate result image;
and the marked image output unit is used for marking the abnormal area at the corresponding position in the power line channel image according to the intermediate result image and outputting the marked power line channel image.
Further, the image preprocessing unit preprocesses the acquired power line channel image, and specifically includes: graying, optical correction and image denoising.
Further, the power line position acquisition unit includes:
the power line edge detection subunit detects the power line edge in the image to be detected by using a Ratio operator;
and the power line position acquisition subunit processes the power line channel image with the edge of the detected power line by using a random Hough transformation method of the gradient direction information so as to acquire the power line position of the power line in the image to be detected.
Further, the intermediate result image generating unit includes:
the to-be-detected region generating subunit is used for performing region segmentation on the position of the power line in the to-be-detected image and obtaining N segmented to-be-detected regions;
a gray level pixel point counting subunit, configured to count the number of pixel points of each gray level in each segmented to-be-detected region, and generate N pieces of statistical result data according to a one-to-one correspondence relationship;
the gray level average value calculating operator unit is used for calculating the total gray level average value of the N segmented to-be-detected areas by utilizing the N statistical result data;
and the abnormal area marking subunit is used for comparing the N statistical results with the overall gray average value one by one, and marking the segmented to-be-detected area with the difference value larger than a preset abnormal threshold as an abnormal area.
For the working principle and process of the intelligent power line patrol system of this embodiment, reference is made to the description of the first embodiment of the present invention, and details are not described here.
As can be seen from the above description, compared with the prior art, the beneficial effects of the present invention are: according to the embodiment of the invention, through the steps of preprocessing, power line edge extraction, abnormal area identification and the like, the situations of damage, foreign matter adhesion and the like in the power line can be quickly and accurately identified, the detection result can be visually output, an unmanned aerial vehicle photographing device is utilized in the whole process, and an automatic navigation cruise mode is combined, so that the operation accuracy can be effectively improved, the error caused by manual acquisition is avoided, the purpose of reducing the manual participation degree is achieved, and the indicative function can be provided for manual reinspection.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (10)
1. An intelligent power line inspection method is characterized by comprising the following steps:
step S1, formulating a line patrol path of the unmanned aerial vehicle photographic device according to the trend of the power line, and acquiring a power line channel image by using the unmanned aerial vehicle photographic device;
step S2, preprocessing the acquired power line channel image and obtaining an image to be detected;
step S3, carrying out power line edge extraction on the image to be detected so as to obtain the power line position of a power line in the image to be detected;
step S4, detecting a high-brightness area or a low-brightness area in the power line position of the image to be detected, marking the high-brightness area or the low-brightness area as an abnormal area, and marking the abnormal area in the image to be detected to generate an intermediate result image;
step S5, according to the intermediate result image, marking the abnormal region at the corresponding position in the power line channel image, and outputting the marked power line channel image.
2. The intelligent power line patrol method according to claim 1, wherein in step S2, the preprocessing of the acquired power line channel image includes the following steps: graying, optical correction and image denoising.
3. The intelligent power line patrol method according to claim 1, wherein the step S3 includes:
step S31, detecting the edge of the power line in the image to be detected by using a Ratio operator;
and step S32, processing the power line channel image with the detected power line edge by using a random Hough transformation method of gradient direction information to obtain the power line position of the power line in the image to be detected.
4. The intelligent power line patrol method according to claim 1, wherein the step S4 includes:
step S41, performing region segmentation on the position of the power line in the image to be detected, and obtaining N segmented regions to be detected;
step S42, counting the number of pixel points of each gray level in each segmented region to be detected, and generating N statistical result data according to a one-to-one correspondence relationship;
step S43, calculating the average value of the total gray scale of N segmented regions to be detected by utilizing N statistical result data;
and step S44, comparing the N statistical results with the average value of the overall gray level one by one, and marking the segmented to-be-detected area with the difference value larger than a preset abnormal threshold as an abnormal area.
5. The intelligent power line patrol method according to claim 1, wherein the step of marking the abnormal region at the corresponding position in the power line channel image specifically comprises the following steps: and filling the pixel points marked as the abnormal areas in the power line channel image into red, green or blue.
6. The intelligent power line patrol method according to claim 1, wherein in step S1, the routing of the unmanned aerial vehicle camera device according to the trend of the power line is implemented by a GPS navigation system or a beidou navigation system.
7. The utility model provides a power line intelligence patrols linear system which characterized in that includes:
the unmanned aerial vehicle photographing device is used for acquiring power line channel images according to a preset line patrol path, wherein the line patrol path is formulated according to the trend of a power line;
the image preprocessing unit is used for preprocessing the acquired power line channel image and acquiring an image to be detected;
the power line position acquisition unit is used for carrying out power line edge extraction on the image to be detected so as to acquire the power line position of a power line in the image to be detected;
the intermediate result image generating unit is used for detecting a high-brightness area or a low-brightness area in the power line position of the image to be detected, marking the high-brightness area or the low-brightness area as an abnormal area, and marking the abnormal area in the image to be detected to generate an intermediate result image;
and the marked image output unit is used for marking the abnormal area at the corresponding position in the power line channel image according to the intermediate result image and outputting the marked power line channel image.
8. The intelligent power line patrol system according to claim 7, wherein the image preprocessing unit preprocesses the acquired power line channel image, and specifically comprises: graying, optical correction and image denoising.
9. The intelligent power line patrol system according to claim 7, wherein the power line position acquisition unit comprises:
the power line edge detection subunit detects the power line edge in the image to be detected by using a Ratio operator;
and the power line position acquisition subunit processes the power line channel image with the edge of the detected power line by using a random Hough transformation method of the gradient direction information so as to acquire the power line position of the power line in the image to be detected.
10. The intelligent power line patrol system according to claim 7, wherein the intermediate result image generation unit includes:
the to-be-detected region generating subunit is used for performing region segmentation on the position of the power line in the to-be-detected image and obtaining N segmented to-be-detected regions;
a gray level pixel point counting subunit, configured to count the number of pixel points of each gray level in each segmented to-be-detected region, and generate N pieces of statistical result data according to a one-to-one correspondence relationship;
the gray level average value calculating operator unit is used for calculating the total gray level average value of the N segmented to-be-detected areas by utilizing the N statistical result data;
and the abnormal area marking subunit is used for comparing the N statistical results with the overall gray average value one by one, and marking the segmented to-be-detected area with the difference value larger than a preset abnormal threshold as an abnormal area.
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|---|---|---|---|---|
| CN113343841A (en) * | 2021-06-03 | 2021-09-03 | 国网北京市电力公司 | Method and device for determining abnormal condition of power tunnel |
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