CN113034021A - Power transmission line defect analysis method and system based on machine patrol data - Google Patents
Power transmission line defect analysis method and system based on machine patrol data Download PDFInfo
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Abstract
The invention discloses a power transmission line defect analysis method and system based on machine patrol data. Unmanned aerial vehicle sends the image data who obtains to the master control center, and the master control center carries out the preliminary treatment back to image data, through the transmission line part characteristic of feature extraction unit discernment in the image data, then puts into the defect analysis unit with the part characteristic and combines early warning analysis algorithm to this part characteristic and carry out the analysis through the defect analysis database, can discern the transmission line that has the defect rapidly, need not artifical discernment and very big promotion identification efficiency. In addition, the image data is also attached with positioning information and identification information of the current circuit, when the main control center finds the defect, the position of the defect can be positioned at the first time, the hidden danger can be eliminated when the main control center goes to the site at the first time, and the operation and maintenance efficiency is improved.
Description
Technical Field
The invention relates to the field of operation and maintenance of power transmission lines, in particular to a power transmission line defect analysis method and system based on machine patrol data.
Background
One of the fundamental goals of power system operation is to provide consistent and high quality electrical power to people under reasonable planning. At the present stage, the electric power construction develops rapidly, but many drawbacks come after: the safety management system of the electric power construction site is incomplete; most of power transmission equipment is exposed in the environment under severe conditions for a long time, and the complex construction road section brings great hidden danger to safety production. In the traditional routing inspection of the power transmission line, the problems of great influence by natural factors such as terrain, weather and the like, low routing inspection efficiency, severe work safety problem and the like often occur. Although the unmanned aerial vehicle is adopted to replace the routing inspection at the present stage, the data analysis still adopts manual identification. The labor cost is high, and the recognition efficiency is low.
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 power transmission line defect analysis method and system based on the machine patrol data, which can automatically complete the defect analysis of the power transmission line, reduce the labor cost and improve the identification efficiency.
According to the embodiment of the first aspect of the invention, the method for analyzing the defects of the power transmission line based on the machine patrol data comprises the following steps:
a user inputs an inspection plan through a control center, and the control center sends navigation data to the unmanned aerial vehicle;
the unmanned aerial vehicle patrols the line according to the navigation data and takes a picture of the power transmission line in the process of patrolling the line to obtain a picture of the power transmission line, and the picture is recorded and simultaneously added with positioning information during shooting and identification information of the current line to obtain image data of the specified power transmission line;
the unmanned aerial vehicle sends the acquired image data to a control center;
the control center firstly preprocesses the image data through a preprocessing unit;
sending the preprocessed image data to a feature extraction unit, and identifying and extracting the power transmission line component features in the image data by the feature extraction unit;
the feature extraction unit sends the feature of the component to the defect analysis unit, the defect analysis unit analyzes the feature of the component through a defect analysis database in combination with an early warning analysis algorithm to judge whether the defect exists, and if the defect exists, a defect warning is sent out and the position and the identification information of the component are displayed.
According to the power transmission line defect analysis method based on the machine patrol data in the embodiment of the first aspect of the invention, at least the following technical effects are achieved: according to the embodiment of the invention, the unmanned aerial vehicle is used for line patrol, image data are shot in the line patrol process, manual line patrol is not needed, and the labor and the trouble are saved. Unmanned aerial vehicle sends the image data who obtains to the master control center, and the master control center carries out the preliminary treatment back to image data, through the transmission line part characteristic of feature extraction unit discernment in the image data, then puts into the defect analysis unit with the part characteristic and combines early warning analysis algorithm to this part characteristic and carry out the analysis through the defect analysis database, can discern the transmission line that has the defect rapidly, need not artifical discernment and very big promotion identification efficiency.
In addition, the image data is also attached with positioning information and identification information of the current circuit, when the main control center finds the defect, the position of the defect can be positioned at the first time, the hidden danger can be eliminated when the main control center goes to the site at the first time, and the operation and maintenance efficiency is improved.
According to some embodiments of the invention, the identification information of the current line includes information of a name of the transmission line, a station area where the transmission line is located, and a tower pole.
According to some embodiments of the invention, the detailed step of the pre-treatment is
Firstly, determining whether the naming format of the coding and inspection image is correct, then determining the coding format according to the suffix name of the inspection image, and checking whether the inspection image is damaged;
and finally, denoising the image by a spatial domain filtering method and a frequency domain filtering method.
According to some embodiments of the invention, the feature extraction unit extracts the feature of the component in the image data using a YOLO model extraction algorithm.
According to some embodiments of the present invention, the feature extraction unit extracts the feature of the component in the image data using an RCNN model extraction algorithm.
According to some embodiments of the invention, the feature extraction unit extracts the feature of the part in the image data using an SSD model extraction algorithm.
According to some embodiments of the invention, the pre-warning analysis algorithm is a multi-dimensional pre-warning analysis method of PCA-KMeans.
According to some embodiments of the invention, further comprising the step of manual review: and if the defect analysis unit judges that the current power transmission line has defects, sending the image data to the manual identification unit for manual secondary judgment.
According to a second aspect of the invention, the power transmission line defect analysis system based on the machine patrol data comprises an unmanned aerial vehicle and a control center, wherein the control center performs defect analysis on the power transmission line by the power transmission line defect analysis method based on the machine patrol data.
According to the power transmission line defect analysis system based on the machine patrol data 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 is used for line patrol, image data are shot in the line patrol process, manual line patrol is not needed, and the labor and the trouble are saved. Unmanned aerial vehicle sends the image data who obtains to the master control center, and the master control center carries out the preliminary treatment back to image data, through the transmission line part characteristic of feature extraction unit discernment in the image data, then puts into the defect analysis unit with the part characteristic and combines early warning analysis algorithm to this part characteristic and carry out the analysis through the defect analysis database, can discern the transmission line that has the defect rapidly, need not artifical discernment and very big promotion identification efficiency.
In addition, the image data is also attached with positioning information and identification information of the current circuit, when the main control center finds the defect, the position of the defect can be positioned at the first time, the hidden danger can be eliminated when the main control center goes to the site at the first time, and the operation and maintenance efficiency is improved.
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.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a transmission line defect analysis method based on machine patrol data in the embodiment of the present invention.
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, a method for analyzing defects of a power transmission line based on machine patrol data includes:
s1, inputting a line patrol plan by a user through a control center, and sending navigation data to the unmanned aerial vehicle by the control center;
s2, the unmanned aerial vehicle patrols the line according to the navigation data and shoots the power transmission line in the line patrolling process, the camera shoots the picture of the power transmission line, and the positioning information and the identification information of the current line during shooting are added while the picture is recorded, such as the name of the power transmission line, the station area where the power transmission line is located, the information of a tower pole and the like, so that the image data of the current power transmission line are obtained;
s3, the unmanned aerial vehicle sends the acquired image data to the control center, and the unmanned aerial vehicle carrying the 5G communication module is selected for inspection in the embodiment, so that the transmission rate is higher;
s4, after the server of the control center receives the image data, the pre-processing unit in the server first pre-processes the image data, the detailed steps of the pre-processing are
Firstly, determining whether the naming format of the coding and inspection image is correct, then determining the coding format according to the suffix name of the inspection image, and checking whether the inspection image is damaged, wherein the step is to read, store and analyze image data for subsequent units in the aspect;
because unmanned aerial vehicle patrols and examines and can receive the influence of illumination, noise often at the in-process of gathering the image to cause the image to have a large amount of noises, image light and shade imbalance and image quality decline scheduling problem, consequently still need carry out the denoising treatment to the image, the preprocessing unit carries out the noise step through space domain filtering method and frequency domain filtering method in this embodiment.
S5, sending the preprocessed image data to a feature extraction unit, identifying and extracting the component features of the power transmission line in the image data by the feature extraction unit, extracting the component features in the image data by one or more of a YOLO model extraction algorithm, an RCNN model extraction algorithm or an SSD model extraction algorithm by the feature extraction unit, for example, extracting the circular part of the shockproof hammer by the YOLO model extraction algorithm, identifying the insulator by extracting the texture features in the image by the RCNN model extraction algorithm, and extracting the edge line of the power transmission line by the SSD model extraction algorithm.
And S6, the feature extraction unit sends the part features to a defect analysis unit, the defect analysis unit analyzes the part features through a defect analysis database in combination with an early warning analysis algorithm, the early warning analysis algorithm in the embodiment is a multi-dimensional early warning analysis method of PCA-KMeans, whether defects exist is judged, and if the defects exist, such as broken insulators, broken power transmission lines, foreign bodies on towers, vibration-proof hammer breaks and the like, a defect warning is sent.
In order to improve the accuracy of identification, the method also comprises the following steps of: and if the defect analysis unit judges that the current power transmission line has defects, sending the image data to the manual identification unit for manual secondary judgment. When the defect is judged to exist manually, a warning is given out, and the position and the identification information of the defect occurrence place are sent to the early warning platform of the control center, so that operation and maintenance personnel can go to the site for checking at the first time, and the hidden trouble is eliminated in time.
The invention also relates to a power transmission line defect analysis system based on the machine patrol data, which comprises an unmanned aerial vehicle and a control center, wherein the control center carries out defect analysis on the power transmission line by the power transmission line defect analysis method based on the machine patrol data.
In conclusion, the unmanned aerial vehicle line patrol is carried out, the image data are shot in the line patrol process, manual line patrol is not needed, and the labor and the worry are saved. Unmanned aerial vehicle sends the image data who obtains to the master control center, and the master control center carries out the preliminary treatment back to image data, through the transmission line part characteristic of feature extraction unit discernment in the image data, then puts into the defect analysis unit with the part characteristic and combines early warning analysis algorithm to this part characteristic and carry out the analysis through the defect analysis database, can discern the transmission line that has the defect rapidly, need not artifical discernment and very big promotion identification efficiency.
In addition, the image data is also attached with positioning information and identification information of the current circuit, when the main control center finds the defect, the position of the defect can be positioned at the first time, the hidden danger can be eliminated when the main control center goes to the site at the first time, and the operation and maintenance efficiency is improved.
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 (9)
1. A power transmission line defect analysis method based on machine patrol data is characterized by comprising the following steps:
a user inputs an inspection plan through a control center, and the control center sends navigation data to the unmanned aerial vehicle;
the unmanned aerial vehicle patrols the line according to the navigation data and takes a picture of the power transmission line in the process of patrolling the line to obtain a picture of the power transmission line, and the picture is recorded and simultaneously added with positioning information during shooting and identification information of the current line to obtain image data of the specified power transmission line;
the unmanned aerial vehicle sends the acquired image data to a control center;
the control center firstly preprocesses the image data through a preprocessing unit;
sending the preprocessed image data to a feature extraction unit, and identifying and extracting the power transmission line component features in the image data by the feature extraction unit;
the feature extraction unit sends the feature of the component to the defect analysis unit, the defect analysis unit analyzes the feature of the component through a defect analysis database in combination with an early warning analysis algorithm to judge whether the defect exists, and if the defect exists, a defect warning is sent out and the position and the identification information of the component are displayed.
2. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: the identification information of the current line comprises the name of the power transmission line, the station area where the power transmission line is located and the information of the tower pole.
3. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: the detailed steps of the pretreatment are
Firstly, determining whether the naming format of the coding and inspection image is correct, then determining the coding format according to the suffix name of the inspection image, and checking whether the inspection image is damaged;
and finally, denoising the image by a spatial domain filtering method and a frequency domain filtering method.
4. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: the feature extraction unit extracts the component features in the image data by adopting a YOLO model extraction algorithm.
5. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: the feature extraction unit extracts the component features in the image data by adopting an RCNN model extraction algorithm.
6. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: the feature extraction unit extracts the feature of the component in the image data by adopting an SSD model extraction algorithm.
7. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: the early warning analysis algorithm is a PCA-KMeans multi-dimensional early warning analysis method.
8. The power transmission line defect analysis method based on machine patrol data according to claim 1, characterized in that: further comprises the following steps of manual rechecking: and if the defect analysis unit judges that the current power transmission line has defects, sending the image data to the manual identification unit for manual secondary judgment.
9. A power transmission line defect analysis system based on machine patrol data comprises an unmanned aerial vehicle and a control center, wherein the control center carries out defect analysis on a power transmission line through the power transmission line defect analysis method based on machine patrol data according to any one of claims 1 to 8.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114442658A (en) * | 2021-12-23 | 2022-05-06 | 河南福多电力工程有限公司 | Automatic inspection system for unmanned aerial vehicle of power transmission and distribution line and operation method thereof |
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Application publication date: 20210625 |