CN114429447A - Transmission line defect detection method and device - Google Patents
Transmission line defect detection method and device Download PDFInfo
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- CN114429447A CN114429447A CN202111528303.7A CN202111528303A CN114429447A CN 114429447 A CN114429447 A CN 114429447A CN 202111528303 A CN202111528303 A CN 202111528303A CN 114429447 A CN114429447 A CN 114429447A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
Abstract
The invention relates to the technical field of power transmission line monitoring and operation and maintenance protection, and particularly provides a power transmission line defect detection method and device, which comprise the following steps: acquiring an image of a power transmission line, and preprocessing the image of the power transmission line; performing state recognition on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model; the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state. The technical scheme provided by the invention can realize automatic classification and identification of the line defects, can monitor the line state in real time for 24 hours, and improves the intelligent operation and maintenance level of the line.
Description
Technical Field
The invention relates to the technical field of power transmission line monitoring and operation and maintenance protection, in particular to a power transmission line defect detection method and device.
Background
The transmission line has large reserve and wide distribution range, is usually in the sparse areas such as hills, mountains, unfavorable geological areas and the like, and has extremely bad operation conditions. The transmission line is influenced by external environmental factors such as wind power, ice coating, temperature and the like for a long time and is likely to generate defects or damage, although the hidden danger can not influence the equipment in a short time, if the hidden danger can not be found and processed in time, the loss of the equipment is increased, the efficiency is lowered, serious accidents such as wire breakage, substation equipment damage, power distribution network outage and the like can be caused in serious conditions, and the life and property safety of the public is directly threatened. Therefore, the method is important for carrying out regular inspection and even uninterrupted monitoring on the power transmission line, finding hidden dangers and faults and timely processing, and is important for social life and production safety.
The traditional power transmission line inspection method finds equipment abnormality by means of human vision, takes pictures and videos of a lead by using a camera or an unmanned aerial vehicle arranged on a tower, and then carries out manual identification by background personnel. The mode seriously depends on the operation experience of background personnel, and has huge manpower consumption and low efficiency. And present image access is all by tour personnel manual operation to unmanned aerial vehicle is the example, and the image of shooing is deposited in unmanned aerial vehicle local earlier, returns the manual work again after the office and leads to the server on, and the ageing is lower, lacks defect automatic checkout technique.
Disclosure of Invention
In order to overcome the defects, the invention provides a method and a device for detecting the defects of the power transmission line.
In a first aspect, a method for detecting defects of a power transmission line is provided, where the method includes:
acquiring an image of a power transmission line, and preprocessing the image of the power transmission line;
performing state recognition on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model;
the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state.
Preferably, the acquiring the image of the power transmission line includes: the power transmission line is aerial-photographed by an unmanned aerial vehicle or a helicopter, or the power transmission line is image-collected by a monitoring camera arranged on the power transmission line, so that the image of the power transmission line is obtained.
Preferably, the wire state includes at least one of: no wire, normal wire, broken strand, scattered strand and foreign matter adhesion.
Preferably, the pretreatment comprises at least one of: gaussian filtering and histogram equalization.
Preferably, the performing state identification on the power transmission line based on the preprocessed image of the power transmission line and the pre-constructed defect detection model of the power transmission line includes:
slicing the preprocessed image of the power transmission line into preset sizes;
and inputting the image of the power transmission line with the preset size into a pre-constructed power transmission line defect detection model, and acquiring the wire state of the power transmission line output by the pre-constructed power transmission line defect detection model.
Preferably, the process of obtaining the pre-constructed defect detection model of the power transmission line includes:
slicing a pre-acquired image of the power transmission line into preset sizes;
marking the lead state of the image of the power transmission line with a preset size by artificial semantics;
carrying out image enhancement on an image of a power transmission line with a preset size;
dividing the enhanced image of the power transmission line with the preset size into training data, verification data and test data;
and training an initial neural network model by using the training data, the verification data and the test data, and taking the trained initial neural network model as the pre-constructed power transmission line defect detection model.
Further, the preset size is 224 × 224.
Further, the image enhancement comprises at least one of: translation, rotation, scale scaling, Gaussian blur, brightness correction and clipping.
Further, in the training process of the initial neural network model, the learning rate is 0.000001, the momentum coefficient is 0.9, the batch size is 32, the iteration number is 100000, and the Epoch number is 200.
In a second aspect, a power transmission line defect detection apparatus is provided, which includes:
the acquisition module is used for acquiring an image of the power transmission line and preprocessing the image of the power transmission line;
the identification module is used for carrying out state identification on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model;
the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state.
In a third aspect, a storage medium is provided, where the storage medium includes a stored program, and when the program runs, a device on which the storage medium is located is controlled to execute the power transmission line defect detection method.
In a fourth aspect, a processor is provided, where the processor is configured to execute a program, where the program executes the method for detecting the defect of the power transmission line when running.
One or more technical schemes of the invention at least have one or more of the following beneficial effects:
the invention provides a method and a device for detecting defects of a power transmission line, which comprise the following steps: acquiring an image of a power transmission line, and preprocessing the image of the power transmission line; performing state recognition on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model; the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state. The technical scheme provided by the invention can realize automatic classification and identification of line defects, can monitor the line state in real time for 24 hours, and improves the intelligent level of operation and maintenance of the line.
Drawings
Fig. 1 is a schematic flow chart of main steps of a method for detecting defects of a power transmission line according to an embodiment of the present invention;
FIG. 2 is a graph of the loss function of the model during initial neural network model training according to an embodiment of the present invention;
fig. 3 is a main structural block diagram of the power transmission line defect detection apparatus according to the embodiment of the present invention.
Detailed Description
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic flow chart of main steps of a power transmission line defect detection method according to an embodiment of the present invention. As shown in fig. 1, the method for detecting defects of a power transmission line in the embodiment of the present invention mainly includes the following steps:
step S101: acquiring an image of a power transmission line, and preprocessing the image of the power transmission line;
step S102: performing state recognition on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model;
the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state.
In this embodiment, the power transmission line may be aerial-photographed by an unmanned aerial vehicle or a helicopter, or the power transmission line may be image-captured by a surveillance camera arranged on the power transmission line, so as to obtain an image of the power transmission line.
Wherein the wire state comprises at least one of: no wire, normal wire, broken strand, scattered strand and foreign matter adhesion. The pre-treatment comprises at least one of the following: gaussian filtering and histogram equalization.
Specifically, the state recognition of the power transmission line based on the preprocessed image of the power transmission line and the pre-constructed defect detection model of the power transmission line includes:
slicing the preprocessed image of the power transmission line into preset sizes;
and inputting the image of the power transmission line with the preset size into a pre-constructed power transmission line defect detection model, and acquiring the wire state of the power transmission line output by the pre-constructed power transmission line defect detection model.
Preferably, the process of obtaining the pre-constructed defect detection model of the power transmission line includes:
slicing a pre-acquired image of the power transmission line into preset sizes;
marking the lead state of the image of the power transmission line with a preset size by manual semantics;
carrying out image enhancement on the image of the power transmission line with a preset size;
dividing the enhanced image of the power transmission line with the preset size into training data, verification data and test data;
and training an initial neural network model by using the training data, the verification data and the test data, and taking the trained initial neural network model as the pre-constructed power transmission line defect detection model.
Wherein the preset size is 224 × 224.
In one embodiment, to scale up the data set, operations such as translation, rotation, scaling, gaussian blur, luminance correction, cropping, etc. are used to perform sample augmentation, such as flipping left and right and flipping up and down for each picture, followed by random cropping of the image to allow objects to appear at different positions in the image at different scales, which can reduce the sensitivity of the model to the target position. Brightness processing can also be carried out, the original image brightness is corrected to be between 50% and 150% of the original brightness, and the quantity of fault samples is increased;
in one embodiment, during the training process of the initial neural network model, the learning rate is 0.000001, the momentum coefficient is 0.9, the batch size is 32, the number of iterations is 100000, the Epoch number is 200, and the loss function curve of the model during the training process is shown in fig. 2, and it can be seen that the model loss value is below 0.1.
Based on the same inventive concept, the present invention provides a power transmission line defect detection apparatus, as shown in fig. 3, the power transmission line defect detection apparatus includes:
the acquisition module is used for acquiring an image of the power transmission line and preprocessing the image of the power transmission line;
the identification module is used for carrying out state identification on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model;
the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state.
Preferably, the acquiring an image of the power transmission line includes: the power transmission line is aerial-photographed by an unmanned aerial vehicle or a helicopter, or the power transmission line is image-collected by a monitoring camera arranged on the power transmission line, so that the image of the power transmission line is obtained.
Preferably, the wire state includes at least one of: no wire, normal wire, broken strand, scattered strand and foreign matter adhesion.
Preferably, the pretreatment comprises at least one of: gaussian filtering and histogram equalization.
Preferably, the performing state identification on the power transmission line based on the preprocessed image of the power transmission line and the pre-constructed defect detection model of the power transmission line includes:
slicing the preprocessed image of the power transmission line into preset sizes;
and inputting the image of the power transmission line with the preset size into a pre-constructed power transmission line defect detection model, and acquiring the wire state of the power transmission line output by the pre-constructed power transmission line defect detection model.
Preferably, the process of obtaining the pre-constructed defect detection model of the power transmission line includes:
slicing a pre-acquired image of the power transmission line into preset sizes;
marking the lead state of the image of the power transmission line with a preset size by artificial semantics;
carrying out image enhancement on an image of a power transmission line with a preset size;
dividing the enhanced image of the power transmission line with the preset size into training data, verification data and test data;
and training an initial neural network model by using the training data, the verification data and the test data, and taking the trained initial neural network model as the pre-constructed power transmission line defect detection model.
Further, the preset size is 224 × 224.
Further, the image enhancement comprises at least one of: translation, rotation, scale scaling, Gaussian blur, brightness correction and clipping.
Further, in the training process of the initial neural network model, the learning rate is 0.000001, the momentum coefficient is 0.9, the batch size is 32, the iteration number is 100000, and the Epoch number is 200.
Further, the present invention provides a storage medium, where the storage medium includes a stored program, and when the program runs, the device on which the storage medium is located is controlled to execute the power transmission line defect detection method.
Further, the invention provides a processor, where the processor is configured to execute a program, where the program executes the method for detecting the defect of the power transmission line when running.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (12)
1. A method for detecting defects of a power transmission line is characterized by comprising the following steps:
acquiring an image of a power transmission line, and preprocessing the image of the power transmission line;
performing state recognition on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model;
the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state.
2. The method of claim 1, wherein the acquiring the image of the power transmission line comprises: the electric transmission line is aerial-photographed through an unmanned aerial vehicle or a helicopter, or the monitoring camera arranged on the electric transmission line acquires images of the electric transmission line to obtain the images of the electric transmission line.
3. The method of claim 1, wherein the wire status comprises at least one of: no wire, normal wire, broken strand, scattered strand and foreign matter adhesion.
4. The method of claim 1, wherein the pre-processing comprises at least one of: gaussian filtering and histogram equalization.
5. The method of claim 1, wherein the identifying the state of the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed defect detection model of the power transmission line comprises:
slicing the preprocessed image of the power transmission line into preset sizes;
and inputting the image of the power transmission line with the preset size into a pre-constructed power transmission line defect detection model, and acquiring the wire state of the power transmission line output by the pre-constructed power transmission line defect detection model.
6. The method of claim 1, wherein the pre-constructed transmission line defect detection model obtaining process comprises:
slicing a pre-acquired image of the power transmission line into a preset size;
marking the lead state of the image of the power transmission line with a preset size by manual semantics;
carrying out image enhancement on the image of the power transmission line with a preset size;
dividing the enhanced image of the power transmission line with the preset size into training data, verification data and test data;
and training an initial neural network model by using the training data, the verification data and the test data, and taking the trained initial neural network model as the pre-constructed power transmission line defect detection model.
7. The method of claim 5 or 6, wherein the predetermined size is 224 x 224.
8. The method of claim 6, wherein the image enhancement comprises at least one of: translation, rotation, scale scaling, Gaussian blur, brightness correction and clipping.
9. The method of claim 6, wherein during the training of the initial neural network model, the learning rate is 0.000001, the momentum coefficient is 0.9, the batch size is 32, the number of iterations is 100000, and the Epoch number is 200.
10. A transmission line defect detection device, characterized in that the device comprises:
the acquisition module is used for acquiring an image of the power transmission line and preprocessing the image of the power transmission line;
the identification module is used for carrying out state identification on the power transmission line based on the preprocessed image of the power transmission line and a pre-constructed power transmission line defect detection model;
the pre-constructed power transmission line defect detection model is obtained by image training of the power transmission line after preprocessing with an artificial annotation lead state.
11. A storage medium, characterized in that the storage medium comprises a stored program, and when the program runs, the storage medium is controlled to execute the method for detecting the defect of the power transmission line according to any one of claims 1 to 9.
12. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the method according to any one of claims 1 to 9 when running.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111528303.7A CN114429447A (en) | 2021-12-14 | 2021-12-14 | Transmission line defect detection method and device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111528303.7A CN114429447A (en) | 2021-12-14 | 2021-12-14 | Transmission line defect detection method and device |
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| CN114429447A true CN114429447A (en) | 2022-05-03 |
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| CN202111528303.7A Pending CN114429447A (en) | 2021-12-14 | 2021-12-14 | Transmission line defect detection method and device |
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- 2021-12-14 CN CN202111528303.7A patent/CN114429447A/en active Pending
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