CN113052104A - Insulator positioning and identifying method and system based on image identification - Google Patents
Insulator positioning and identifying method and system based on image identification Download PDFInfo
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Abstract
The invention discloses an insulator positioning and identifying method and system based on image identification, which comprises the following steps: the unmanned aerial vehicle is provided with a camera, a flight control module, a communication module and a navigation module, the camera is used for acquiring image data of the power transmission line, and the navigation module is connected with the flight control module; the image recognition unit is in communication connection with the camera through the communication module and is used for receiving image data and recognizing the insulator through a neural network image recognition algorithm; and the big data analysis unit is connected with the image recognition unit and is used for analyzing the recognized insulator characteristics and judging whether a fault occurs or not. The invention does not need to manually inspect the line and take a picture of the insulator, and does not need to manually browse the picture to identify the fault of the insulator, thereby saving worry and labor, greatly liberating the manpower and obviously reducing the operation and maintenance cost of the power transmission line.
Description
Technical Field
The invention relates to the field of power transmission line inspection, in particular to an insulator positioning and identifying method and system based on image identification.
Background
The stable supply of electric power is a key factor for ensuring the stable development of life and production of people, and a large-scale power failure event caused by line faults can cause serious economic loss. The insulator is a special insulating control and can play an important role in an overhead transmission line. Early-year insulators are mostly used for telegraph poles, and a plurality of disc-shaped insulators are hung at one end of a high-voltage wire connecting tower which is gradually developed, are used for increasing creepage distance and are usually made of glass or ceramics, namely insulators.
The insulator is an important line facility which needs to be paid attention to in daily line patrol, and defects often occur, so that the safe operation of a power distribution network is seriously influenced. Therefore, in the inspection process of the power equipment, the insulator needs to be inspected frequently.
The existing inspection is performed in a manual inspection mode, and generally, operation and maintenance inspection personnel hold shooting equipment to shoot photos or identify insulators by naked eyes. After the inspection is finished, identifying the fault of the insulator by manually browsing the photos; this approach is not only time consuming and labor intensive, but also prone to omissions.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides the insulator positioning and identifying method and the insulator positioning and identifying system based on image identification, the image of the insulator can be obtained without manual line patrol, and the fault insulator can be automatically identified.
According to the embodiment of the first aspect of the invention, the insulator positioning and identifying system based on image identification comprises: the unmanned aerial vehicle is provided with a camera, a flight control module, a communication module and a navigation module, wherein the flight control module is used for controlling the flight state of the unmanned aerial vehicle, the camera is used for acquiring the image data of the power transmission line, and the navigation module is connected with the flight control module and used for providing position and route information; the image recognition unit is in communication connection with the camera through a communication module and is used for receiving image data and recognizing the insulator through a neural network image recognition algorithm; and the big data analysis unit is connected with the image recognition unit and is used for analyzing the recognized insulator characteristics and judging whether a fault occurs or not.
The insulator positioning and identifying system based on image identification according to the embodiment of the first aspect of the invention has at least the following technical effects: according to the embodiment of the invention, the unmanned aerial vehicle flies along the power transmission line, the camera arranged on the unmanned aerial vehicle shoots the image data of the power transmission line and remotely transmits the image data to the image recognition unit through the communication module, the image recognition unit recognizes the image with the insulator through a neural network image recognition algorithm and transmits the image to the big data analysis unit, and the big data analysis unit analyzes the characteristics of the insulator and judges whether the fault occurs. According to the invention, through the automatic line patrol and shooting and image recognition technology of the unmanned aerial vehicle, the full-automatic line patrol of the power transmission line is realized, manual line patrol and insulator shooting are not needed, and insulator faults are not needed to be recognized by manually browsing photos, so that the worry and labor are saved, the manpower is greatly liberated, and the operation and maintenance cost of the power transmission line is obviously reduced.
According to some embodiments of the invention, the camera is a dual light source camera.
According to some embodiments of the invention, the unmanned aerial vehicle further comprises a human-computer interaction module, and the human-computer interaction module is connected with the unmanned aerial vehicle through a communication module and is used for manually controlling the operation of the unmanned aerial vehicle and observing images shot by the camera in real time.
According to some embodiments of the invention, the human-computer interaction module comprises a display screen and a console.
According to some embodiments of the invention, the drone is powered by a graphene battery.
According to some embodiments of the invention, the communication module is a 5G module.
According to some embodiments of the invention, the navigation module is a GPS module or a beidou navigation module.
According to the second aspect of the invention, the insulator positioning and identifying method based on image identification comprises the following steps:
the unmanned aerial vehicle takes off and cruises along the power transmission line and takes a picture of the power transmission line in the way through the camera to obtain image data;
preprocessing image data, firstly down-sampling the image data to be a pixel point image suitable for the input parameter size of a neural network, and then carrying out gray processing;
sampling the preprocessed image data on features of different dimensions, and then generating a multi-scale feature map;
carrying out positioning detection on the multi-size characteristic diagram, clustering the characteristic tensors of each scale to obtain detection frames of different sizes, predicting the relative position of the insulator to obtain a Bounding Box center point;
dividing the obtained identification result into two types of insulator and insulator-free, and sending the image data with the insulator to a big data analysis unit;
and after receiving the image data of the insulator, the big data analysis unit stores the image data and compares the image data of the current insulator with the historical image data to judge whether a fault occurs.
According to some embodiments of the invention, the pre-processing step comprises: determining whether the encoding is correct; determining whether the naming format of the inspection image is correct or not; and determining the coding format according to the suffix name of the polling image, and checking whether the polling image is damaged.
According to some embodiments of the invention, the pre-processing step comprises: and performing denoising processing on the image by a spatial domain filtering method and a frequency domain filtering method.
According to the insulator positioning and identifying method based on image identification in the embodiment of the second aspect of the invention, at least the following technical effects are achieved: according to the embodiment of the invention, the unmanned aerial vehicle flies along the power transmission line, the camera arranged on the unmanned aerial vehicle shoots the image data of the power transmission line and remotely transmits the image data to the image recognition unit through the communication module, the image recognition unit recognizes the image with the insulator through a neural network image recognition algorithm and transmits the image to the big data analysis unit, and the big data analysis unit analyzes the characteristics of the insulator and judges whether the fault occurs. According to the invention, through the automatic line patrol and shooting and image recognition technology of the unmanned aerial vehicle, the full-automatic line patrol of the power transmission line is realized, manual line patrol is needed and the insulator is shot, and manual photo browsing is not needed to recognize the insulator fault, so that the worry and labor are saved, the manpower is greatly liberated, and the operation and maintenance cost of the power transmission line is obviously reduced.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of an insulator positioning and identifying system based on image identification according to an embodiment of the present invention;
fig. 2 is a flowchart of an insulator location identification method based on image identification in the embodiment of the present invention.
Reference numerals
The unmanned aerial vehicle comprises an unmanned aerial vehicle 100, a camera 110, a flight control module 120, a communication module 130, a navigation module 140, an image recognition unit 200, a big data analysis unit 300 and a human-computer interaction module 400.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
Referring to fig. 1, an insulator positioning and identifying system based on image recognition includes:
unmanned aerial vehicle 100, image recognition unit 200 and big data analysis unit 300, unmanned aerial vehicle 100 is last to be configured with camera 110, flight control module 120, communication module 130 and navigation module 140, flight control module 120's effect is the flight state of control unmanned aerial vehicle 100, including CPU, inertia measurement module, the barometer, electron compass and driving motor etc., unmanned aerial vehicle 100 and flight control module 120 in this embodiment adopt the existing equipment of big jiang, camera 110's effect is the image data who acquires transmission line, camera 110 is two light source cameras in this embodiment, both can acquire conventional image, also can acquire hot infrared image, also can acquire clear image when light is relatively poor. The navigation module 140 is connected to the flight control module 120, and the navigation module 140 may adopt a GPS module or a beidou navigation module, preferably, in the embodiment, the beidou navigation module is adopted to realize positioning and navigation. The communication module 130 may adopt a 4G, 5G, 433M wireless or other communication module, and in this embodiment, a 5G module is adopted.
The image recognition unit 200 and the big data analysis unit 300 are arranged in a server of a main control center, the image recognition unit 200 is in communication connection with the camera 110 through the communication module 130, the big data analysis unit 300 is connected with the image recognition unit 200, the image recognition unit 200 recognizes the insulator through a neural network image recognition algorithm, the big data analysis unit 300 stores the insulator image in a classified mode during each cruising, and when a new insulator image is received, the new insulator image is compared with historical data, so that whether a fault occurs is analyzed and judged.
In order to realize manual control under special conditions, the unmanned aerial vehicle further comprises a human-computer interaction module 400, wherein the human-computer interaction module 400 comprises a display screen and a console, the display screen and the console are connected with the unmanned aerial vehicle 100 through the communication module 130, a user can manually control the operation of the unmanned aerial vehicle 100 through the console, and images shot by the camera 110 are observed in real time through the display screen.
Unmanned aerial vehicle 100 provides power through graphite alkene battery, and graphite alkene group battery has good frost resistance, also enables unmanned aerial vehicle 100 to have good flight mileage like this in chilly season.
Referring to fig. 2, the present invention further relates to an insulator positioning and identifying method based on image identification, comprising the following steps:
s1: the unmanned aerial vehicle 100 takes off and cruises along the power transmission line and takes a picture of the power transmission line in the approach through the camera 110 to acquire image data.
S2: preprocessing image data, wherein the preprocessing step comprises the steps of firstly confirming the image data and determining whether the codes are correct; determining whether the naming format of the inspection image is correct or not; and determining the coding format according to the suffix name of the polling image, and checking whether the polling image is damaged. And then denoising the image by a spatial domain filtering method and a frequency domain filtering method.
And then, down-sampling the image data to form pixel point images suitable for the input parameter size of the neural network, and then carrying out gray processing.
S3: and sampling the preprocessed image data on the features of different dimensions, and then generating a multi-scale feature map.
S4: and positioning and detecting the multi-size characteristic diagram, clustering the characteristic tensors of each scale to obtain detection frames of different sizes, predicting the relative position of the insulator, and obtaining a Bounding Box center point.
S5: the obtained recognition results are classified into two types, insulator-present and insulator-absent, and the image data with the insulator is transmitted to the big data analysis unit 300.
S6: after receiving the image data of the insulator, the big data analysis unit 300 stores the image data and compares the image data of the current insulator with the historical image data to determine whether a fault occurs.
In summary, in the embodiment of the present invention, the unmanned aerial vehicle 100 flies along the power transmission line, the camera 110 disposed on the unmanned aerial vehicle 100 captures image data of the power transmission line and remotely sends the image data to the image recognition unit 200 through the communication module 130, the image recognition unit 200 recognizes an image with an insulator through a neural network image recognition algorithm and sends the image to the big data analysis unit 300, and the big data analysis unit 300 analyzes characteristics of the insulator to determine whether a fault occurs. According to the invention, through the automatic line patrol and shooting and image recognition technology of the unmanned aerial vehicle 100, the full-automatic line patrol of the power transmission line is realized, manual line patrol and insulator shooting are not needed, and insulator faults are not needed to be recognized by manually browsing photos, so that the worry and labor are saved, the manpower is greatly liberated, and the operation and maintenance cost of the power transmission line is obviously reduced.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. An insulator positioning and identifying system based on image identification is characterized by comprising:
the unmanned aerial vehicle (100) is provided with a camera (110), a flight control module (120), a communication module (130) and a navigation module (140), the flight control module (120) is used for controlling the flight state of the unmanned aerial vehicle (100), the camera (110) is used for acquiring image data of a power transmission line, and the navigation module (140) is connected with the flight control module (120) and used for providing position and route information;
the image recognition unit (200) is in communication connection with the camera (110) through a communication module (130) and is used for receiving image data and recognizing the insulator through a neural network image recognition algorithm;
the big data analysis unit (300) is connected with the image recognition unit (200) and used for analyzing the recognized insulator characteristics to judge whether a fault occurs or not.
2. The image recognition based insulator location recognition system of claim 1, wherein: the camera (110) is a double-light-source camera.
3. The image recognition based insulator location recognition system of claim 1, wherein: still include human-computer interaction module (400), human-computer interaction module (400) through communication module (130) with unmanned aerial vehicle (100) link to each other and be used for the operation of manual control unmanned aerial vehicle (100) and observe the image that camera (110) shot in real time.
4. The image recognition based insulator location recognition system of claim 3, wherein: the human-computer interaction module (400) comprises a display screen and a console.
5. The image recognition based insulator location recognition system of claim 1, wherein: the unmanned aerial vehicle (100) provides power through the graphene battery.
6. The image recognition based insulator location recognition system of claim 1, wherein: the communication module (130) is a 5G module.
7. The image recognition based insulator location recognition system of claim 1, wherein: the navigation module (140) is a GPS module or a Beidou navigation module.
8. An insulator positioning and identifying method based on image identification is characterized by comprising the following steps:
the unmanned aerial vehicle (100) takes off and cruises along the power transmission line and takes pictures of the power transmission line in the way through the camera (110) to obtain image data;
preprocessing image data, firstly down-sampling the image data to be a pixel point image suitable for the input parameter size of a neural network, and then carrying out gray processing;
sampling the preprocessed image data on features of different dimensions, and then generating a multi-scale feature map;
carrying out positioning detection on the multi-size characteristic diagram, clustering the characteristic tensors of each scale to obtain detection frames of different sizes, predicting the relative position of the insulator to obtain a Bounding Box center point;
dividing the obtained identification result into two types of insulator and insulator-free, and sending the image data with the insulator to a big data analysis unit (300);
after receiving the image data of the insulator, the big data analysis unit (300) stores the image data and compares the image data of the current insulator with historical image data to judge whether a fault occurs.
9. The image recognition-based insulator positioning recognition method according to claim 8, wherein: the pretreatment step comprises: determining whether the encoding is correct; determining whether the naming format of the inspection image is correct or not; and determining the coding format according to the suffix name of the polling image, and checking whether the polling image is damaged.
10. The image recognition-based insulator positioning recognition method according to claim 8, wherein: the pretreatment step comprises: and performing denoising processing on the image by a spatial domain filtering method and a frequency domain filtering method.
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| US20160117845A1 (en) * | 2014-10-27 | 2016-04-28 | King Fahd University Petroleum and Minerals | Contamination level estimation method for high voltage insulators |
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| CN206618697U (en) * | 2017-04-06 | 2017-11-07 | 侯思明 | A kind of high-voltage line image capturing system |
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Application publication date: 20210629 |