CN114779031A - Digital power equipment ultraviolet imaging discharge abnormity detection method and system - Google Patents
Digital power equipment ultraviolet imaging discharge abnormity detection method and system Download PDFInfo
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Abstract
The invention belongs to the field of electric power equipment discharge abnormity detection, and provides a digital electric power equipment ultraviolet imaging discharge abnormity detection method and system, wherein the method comprises the steps of detecting a plurality of electric power equipment detection points according to detection tasks, and associating the detection tasks with corresponding electric power equipment detection point information to obtain an ultraviolet imaging detection file; carrying out integrity and compliance verification on the ultraviolet imaging detection file to form an ultraviolet imaging detection file library; positioning a discharge position based on the ultraviolet imaging detection file after verification in the ultraviolet imaging detection file library, and giving a detection result according to the positioning discharge position; according to the invention, the original photon number is directly converted into the relative discharge intensity representation, the strongest discharge position can be obviously found on an output image, the diagnosis characteristic quantity in a detection file is automatically extracted and displayed, the field personnel is assisted in real time to deal with the abnormal condition in a targeted manner, and a processing strategy is rapidly formulated.
Description
Technical Field
The invention belongs to the technical field of discharge abnormity detection of power equipment, and particularly relates to an ultraviolet imaging discharge abnormity detection method and system for digital power equipment.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
As a common detection means of power equipment, the ultraviolet imaging can find the hidden danger or damage of the external insulation as soon as possible, and has great significance for reducing the failure rate of the equipment and ensuring the safe operation of a power system.
The traditional ultraviolet image shows a discharge area in a form of a binary light spot, when an instrument outputs detection data, binary processing is directly carried out on detected strong and weak information, and a binary threshold value is unknown, so that the difference of the strong and weak information cannot be seen from all discharge points in the light spot area in the detection image, the abnormal discharge can be judged only through the size and the outline of the discharge area, the statistical photon number is generally utilized, and the photon number statistical modes of different instrument manufacturers are different.
In addition, for detection means such as infrared and ultraviolet, when a large number of devices are subjected to popularization, the maximum workload is to correspond detection data to the tested devices and record basic information of detection, and the whole process is time-consuming and labor-consuming.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a system for detecting the ultraviolet imaging discharge abnormality of the digital power equipment.
According to some embodiments, a first aspect of the present invention provides a method for detecting an abnormal ultraviolet imaging discharge of a digital power device, which adopts the following technical solutions:
a digital power equipment ultraviolet imaging discharge abnormity detection method comprises the following steps:
detecting a plurality of power equipment detection points according to the detection tasks, and associating the detection tasks with corresponding power equipment detection point information to obtain an ultraviolet imaging detection file;
carrying out integrity and compliance verification on the ultraviolet imaging detection file to form an ultraviolet imaging detection file library;
positioning a discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library, and giving a detection result according to the positioning discharge position;
the ultraviolet imaging detection file positioning discharge position after verification in the ultraviolet imaging detection file library specifically comprises the following steps:
extracting an ultraviolet intensity matrix and a visible light image based on the verified ultraviolet imaging detection file;
performing light spot segmentation based on the ultraviolet intensity matrix to obtain a discharge central area;
and mapping the edge information of the divided discharge central area into a visible light image to obtain an abnormal discharge position.
Further, the detection task includes a plurality of pieces of detection information, and each piece of detection information includes the following fields:
the system comprises a measuring point serial number, a station name, a station code, a tested device name, a tested device code, a measuring point name and a measuring point code.
Further, the ultraviolet imaging detection file comprises a file length, a specification version number, file generation time, a site name, a site code, weather, temperature, humidity, an instrument manufacturer, an instrument model, an instrument version number, system frequency, atlas number, longitude, latitude, altitude, an atlas and a reserved field;
the map comprises map type codes, map data length, map generation time, names of devices to be tested, codes of the devices to be tested, names of measuring points, codes of measuring points, detection channel marks, types of stored data, detection distances, accumulated time, frame acquisition frequency, output frame rate, frame number, gain, spot color, binarization threshold, photon number, discharge state, visible light zooming, visible light exposure value, visible light image data length, image width, image height, ultraviolet intensity matrix, visible light image data and reserved fields.
Further, the spot segmentation is performed based on the ultraviolet intensity matrix to obtain a discharge center region, specifically:
graying the ultraviolet intensity matrix to form a gray discharge image;
performing histogram statistics on the gray light spot area based on the gray discharge image;
determining a segmentation threshold of the gray level discharge image according to the histogram statistical result;
and (4) segmenting the gray level discharge image based on the segmentation threshold value to obtain a binarization result, namely a discharge center area.
Further, the determining a segmentation threshold of the gray discharge image according to the histogram statistic result includes:
according to the data in the 7 th interval to the 10 th interval in the histogram;
determining a gray level intermediate value of an interval with the maximum number of pixel points of the histogram;
the gradation center value is used as a division threshold of the gradation discharge image.
Further, the segmentation threshold of the gray discharge image is specifically defined as follows:
wherein the content of the first and second substances,
，
Further, the discharge position includes the following information:
a discharge center coordinate;
the central discharge range is the number of pixels in the discharge central area;
the width and height of the smallest circumscribed rectangle of the discharge center region.
Further, the step of giving a diagnosis result according to the positioning discharge position specifically comprises:
obtaining an identification area to be classified by amplifying the minimum circumscribed rectangular area of the discharge center area by two times;
mapping the edge information of the to-be-classified identification area to a visible light image to obtain to-be-classified identification image;
carrying out automatic classification and identification on the equipment components on the image to be classified and identified to obtain a discharge component;
based on the discharge part, a detection result is obtained.
Further, the detection result includes:
a discharge center coordinate, a center discharge range, and a discharge center component.
According to some embodiments, a second aspect of the present invention provides a system for detecting abnormal ultraviolet imaging discharge of a digital power device, which adopts the following technical solutions:
a digital power equipment ultraviolet imaging discharge abnormity detection system comprises:
the data acquisition module is configured to detect a plurality of power equipment detection points according to the detection tasks, and associate the detection tasks with corresponding power equipment detection point information to obtain an ultraviolet imaging detection file;
the file library construction module is configured to carry out integrity and compliance verification on the ultraviolet imaging detection file to form an ultraviolet imaging detection file library;
the discharge detection module is configured to position a discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library and give a detection result according to the positioned discharge position;
the ultraviolet imaging detection file positioning discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library specifically comprises the following steps:
extracting an ultraviolet intensity matrix and a visible light image based on the verified ultraviolet imaging detection file;
performing light spot segmentation based on the ultraviolet intensity matrix to obtain a discharge central area;
and mapping the edge information of the divided discharge central area into a visible light image to obtain an abnormal discharge position.
Compared with the prior art, the invention has the beneficial effects that:
the invention changes the mode that the original ultraviolet imager directly utilizes the photon number to represent the discharge intensity, can retain the relative discharge intensity through a new file storage format, automatically extracts and displays the diagnosis characteristic quantity in the detection file, assists field personnel to pertinently treat abnormal conditions in real time, and rapidly formulates a treatment strategy. Meanwhile, the detection files are automatically uploaded to a background management system, so that transverse comparison and longitudinal comparison can be performed on mass detection data of the equipment, and data lookup and overall equipment condition mastering are facilitated.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a flowchart of a method for detecting an abnormal ultraviolet imaging discharge of a digital power device according to an embodiment of the present invention;
fig. 2 is a statistical result of a gray scale light spot area histogram according to an embodiment of the present invention;
FIG. 3 is a visible light image of an ultraviolet imaging apparatus according to an embodiment of the invention;
FIG. 4 is a test image of a conventional UV imaging apparatus according to an embodiment of the present invention;
fig. 5 is a detection image generated by a method for detecting abnormal ultraviolet imaging discharge of a digital power device according to an embodiment of the present invention;
FIG. 6 is a gray scale discharge image according to an embodiment of the present invention;
FIG. 7 is an image of a discharge center region after segmentation based on a segmentation threshold according to an embodiment of the present invention;
fig. 8 is a result image of mapping the discharge center region edge information into the visible light channel image according to the embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
Example one
As shown in fig. 1, the present embodiment provides a method for detecting an ultraviolet imaging discharge abnormality of a digital power device, and the present embodiment is exemplified by applying the method to a server, it is to be understood that the method may also be applied to a terminal, and may also be applied to a system including the terminal and the server, and is implemented through interaction between the terminal and the server. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a network server, cloud communication, middleware service, a domain name service, a security service CDN, a big data and artificial intelligence platform, and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and the like. The terminal and the server may be directly or indirectly connected through wired or wireless communication, and the application is not limited herein. In this embodiment, the method includes the steps of:
detecting a plurality of power equipment detection points according to the detection tasks, and associating the detection tasks with corresponding power equipment detection point information to obtain an ultraviolet imaging detection file;
carrying out integrity and compliance verification on the ultraviolet imaging detection file to form an ultraviolet imaging detection file library;
positioning a discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library, and giving a diagnosis result according to the positioning discharge position;
the ultraviolet imaging detection file positioning discharge position after verification in the ultraviolet imaging detection file library specifically comprises the following steps:
extracting an ultraviolet intensity matrix and a visible light image based on the verified ultraviolet imaging detection file;
performing spot segmentation based on the ultraviolet intensity matrix to obtain a discharge spot area;
and mapping the edge information of the divided discharge spot area into a visible light image to obtain an abnormal discharge position, as shown in fig. 8.
Specifically, the detection task includes a plurality of pieces of detection information, and each piece of detection information includes the following fields:
the device comprises a measuring point serial number, a station name, a station code, a tested device name, a tested device code, a measuring point name and a measuring point code.
Specifically, the ultraviolet imaging detection file comprises a file length, a specification version number, file generation time, a site name, a site code, weather, temperature, humidity, an instrument manufacturer, an instrument model, an instrument version number, system frequency, atlas number, longitude, latitude, altitude, an atlas and a reserved field;
the map comprises map type codes, map data length, map generation time, names of devices to be tested, codes of the devices to be tested, names of measuring points, codes of measuring points, detection channel marks, types of stored data, detection distances, accumulated time, frame acquisition frequency, output frame rate, frame number, gain, spot color, binarization threshold, photon number, discharge state, visible light zooming, visible light exposure value, visible light image data length, image width, image height, ultraviolet intensity matrix, visible light image data and reserved fields.
In a specific embodiment, the performing spot segmentation based on the ultraviolet intensity matrix to obtain a discharge center region specifically includes:
graying the ultraviolet intensity matrix to form a grayscale discharge image, as shown in fig. 6;
performing histogram statistics on the gray light spot area based on the gray discharge image;
wherein, the gray light spot area is the non-0 area of the ultraviolet intensity matrix.
As shown in fig. 2, determining a segmentation threshold of the gray discharge image according to the histogram statistics includes:
according to data in 7 th to 10 th intervals in the histogram;
determining a gray level intermediate value of an interval with the maximum number of pixel points of the histogram;
taking the gray central value as a segmentation threshold value of a gray discharge image;
the segmentation threshold of the gray discharge image is specifically defined as follows:
wherein the content of the first and second substances,
，
，
is a firstiThe number of the pixel points in each interval,Hthe number sequence of the pixel points of the histogram is shown;
the gray discharge image is segmented based on the segmentation threshold to obtain a binarization result, i.e. a discharge center region, as shown in fig. 7.
The discharge position comprises the following information: a discharge center coordinate; the central discharge range is the number of the pixel points in the discharge central area; the width and height of the smallest circumscribed rectangle of the discharge center region.
The method for giving the diagnosis result according to the positioning discharge position specifically comprises the following steps:
obtaining an identification area to be classified by amplifying the minimum circumscribed rectangular area of the discharge center area by two times;
mapping the edge information of the identification area to be classified into a visible light image to obtain the identification image to be classified;
carrying out automatic classification and identification on the equipment components on the image to be classified and identified to obtain a discharge component;
based on the discharge part, a detection result is obtained.
The detection result comprises:
a discharge center coordinate, a center discharge range, and a discharge center component.
At present, ultraviolet channels of existing imaging devices on the market are displayed in a binarization mode, and discharge light spot areas are all white, so that actual areas with the strongest discharge and area outlines with different discharge intensities cannot be effectively displayed. Therefore, the storage structure of the digital ultraviolet imaging device is changed, and the strongest discharge position can be obviously found on an output image through the representation of the relative discharge intensity.
The comparative figures are shown in fig. 3, 4 and 5. As shown in fig. 3, this is a visible light image of the ultraviolet imaging device, as shown in fig. 4, this is a detection image of the conventional ultraviolet imaging device, and the white area is a discharge light spot area detected by the ultraviolet channel, and is a binarized area, which can only represent the outline and position of the whole discharge. As shown in fig. 5, this is a detection image generated according to the storage structure of this patent, and it can be seen that, because the relative discharge information is retained, the binarized light spot area is converted into a gray scale area, and the larger the gray scale value, the higher the discharge intensity, and it can be seen that the strongest point of discharge is located at about the joint position of the current transformer.
After the intelligent terminal receives the detection file, the intelligent terminal can perform intelligent processing and analysis on the detection file, quickly locate the discharge position and give a diagnosis result.
The specific spot segmentation process is as follows:
processing the ultraviolet light spot matrix to form a gray image:
carrying out histogram statistics on a non-0 area of the light spot matrix;
the gray scale value 0-255 is divided into 10 intervals, and the step length of each intervalgapIs 26.
It can be seen that the intensity distribution is more uniform over the discharge area, except for the weaker areas.
As shown in FIG. 2, usingHRefers to the sequence of the number of pixels of the histogram,
，
is a firstiThe number of pixel points in each interval.
And searching data in the 7 th interval to the 10 th interval (namely, the gray value is more than 157), and taking the gray value middle value of the interval with the maximum H value as the segmentation threshold value of the whole facula area.
Namely, it is
Segmentation thresholdt =（（idx-1）*gap+1+idx*gap）/2
In an example of the present invention, it is,idxis 9, thus calculated to obtaintIs 221.5.
Therefore, the spot image is segmented according to the threshold value, and a binarization result is obtained.
This region can be considered to be the discharge center region.
And mapping the edge information of the divided discharge central area into a visible light channel image.
After the automatic data processing finds the discharge center area, the following information of the discharge can be automatically obtained:
1) the discharge center coordinates (xc, yc),
2) the central discharge range A, namely the number of pixel points in the discharge central region,
3) the width w and the height h of the discharge central region.
The above information is obtained after the ultraviolet image is automatically processed, and meanwhile, an intelligent classification module of the discharging component is loaded on the intelligent terminal, so that the name of the component which is discharged is automatically identified and labeled, for example, a connector, a sleeve, a lead, a fitting and other typical components of the equipment.
The region to be classified and identified is determined by a discharge center region centered at (xc, yc), having a width of 2w and a height of 2 h.
The intelligent identification module classifies the regions to be classified and identified by using a mode classification algorithm facing image processing in a mode of labeling a visible light image sample of an equipment component, and the region classification algorithm can adopt mature algorithms such as LeNet5 and the like.
Finally, the device ultraviolet detection image feature description quantity can be automatically obtained as follows:
by combining with DLT 345 and 2019 charged equipment ultraviolet diagnosis technology and applying the relevant rules of the guide rule, the abnormal state can be rapidly judged.
Through the mode, the automatic acquisition of ultraviolet imaging data, equipment correspondence, automatic side-end judgment and automatic data return management are completed, and the overall working quality and efficiency are effectively improved.
Example two
The embodiment provides a digital power equipment ultraviolet imaging discharge abnormity detection system, which comprises:
the data acquisition module is configured to detect a plurality of power equipment detection points according to the detection tasks, and associate the detection tasks with corresponding power equipment detection point information to obtain an ultraviolet imaging detection file;
the file library construction module is configured to verify the integrity and the compliance of the ultraviolet imaging detection file to form an ultraviolet imaging detection file library;
the discharge detection module is configured to position a discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library and give a detection result according to the positioned discharge position;
the ultraviolet imaging detection file positioning discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library specifically comprises the following steps:
extracting an ultraviolet intensity matrix and a visible light image based on the verified ultraviolet imaging detection file;
performing spot segmentation based on the ultraviolet intensity matrix to obtain a discharge center area;
and mapping the edge information of the divided discharge central area into a visible light image to obtain an abnormal discharge position.
Specifically, an ultraviolet imaging apparatus includes:
(1) the ultraviolet imaging module is used for forming imaging data of the visible light imaging channel and the ultraviolet imaging channel;
(2) the data storage module is used for storing the imaging data output by the ultraviolet imaging module to form a standardized detection file and simultaneously writing the detection information of the corresponding equipment acquired by the task management module into the detection file;
(3) and the data communication module is used for communicating and transmitting the file stored by the data storage module with the intelligent terminal.
(4) And the task management module is used for receiving the detection tasks issued by the intelligent terminal and managing and checking the detection conditions.
The main part function of ultraviolet imaging module is unanimous with other ultraviolet image appearance, and the difference of this patent lies in: firstly, a data communication module is added, so that information interaction can be carried out with an intelligent terminal; secondly, a task management module is added, and the ultraviolet imaging device can receive detection information sent by the intelligent terminal, write corresponding information into a storage file and return the corresponding information; and thirdly, a data storage module is added, so that a new ultraviolet data storage format is invented and the imaging device is stored. The device can be deeply fused with the power equipment operation site, and data and detection equipment are correspondingly transmitted back by one key, so that the digital operation process is realized.
The data communication module adopts a Bluetooth mode of more than 3.0 for transmission, performs data interaction in a message mode, adopts a point-to-point communication mode, and has a Bluetooth service UUID (serial port service) of 00001101-.
The task management module can receive a detection task issued by the intelligent terminal through Bluetooth, the detection task comprises a plurality of pieces of detection information, and each piece of detection information comprises the following fields:
the method comprises the following steps of measuring point serial number, station name, station code, tested device name, tested device code, measuring point name and measuring point code;
and secondly, after the data storage module forms the detection file, the detection file is transmitted back to the intelligent terminal.
The data storage module mainly repackages the data detected by the ultraviolet imaging module and writes key information such as detection information into a detection file.
The data storage format requires the following:
TABLE 1 Overall File storage Format
TABLE 2 map storage Format
The ultraviolet imaging intelligent terminal is a mobile electronic device which has an external communication function and can perform data processing, and can be a tablet personal computer, a mobile phone and the like.
The intelligent terminal can synchronously detect tasks from the background management system, and generally comprises hundreds of detection points by taking one transformer substation as an example; the detection task is obtained and sent to the imaging device, the imaging device side integrally checks through the task management module, and the detection task is transmitted back to the intelligent terminal after detection is completed; after receiving the detection file obtained by the imaging device, the intelligent terminal can verify the integrity and the compliance of the detection file. By the data processing method, the diagnostic characteristic quantity in the detection file is automatically extracted and displayed, the field personnel are assisted to deal with the abnormal condition in a targeted manner in real time, and a processing strategy is quickly formulated. Meanwhile, the detection files are automatically uploaded to a background management system, so that transverse comparison and longitudinal comparison can be performed on mass detection data of the equipment, and data lookup and overall equipment condition mastering are facilitated.
The traditional ultraviolet imager does not output the information of the structures in tables 1 and 2 of the embodiment, and the discharge area presents a binary light spot area, that is, the non-0 gray level area in the ultraviolet intensity matrix defined in table 2 is a whole pure-color light spot, and most of the light spots are white, and red, green and the like can also be generated. The photon number is a statistical value of the ultraviolet imager to the binary light spot area, the threshold values of the binary light spot areas generated by various manufacturers are different, and the statistical mode is not uniform; in addition, the whole binarization light spot area is displayed in a pure color storage mode, and the position of the point with the strongest discharge and the real influence range cannot be seen, so that the concept of photon number is not objective to judge whether the abnormality exists. The processing mode of the embodiment does not depend on the concept of photon number, the detection result is described by the three characteristic quantities of the discharge center coordinate, the center discharge range and the discharge center part, and a new digital operation process is relied on, so that the subsequent rapid abnormity judgment and data management can be ensured.
The modules are the same as the corresponding steps in the implementation example and application scenarios, but are not limited to the disclosure of the first embodiment. It should be noted that the modules described above as part of a system may be implemented in a computer system such as a set of computer-executable instructions.
In the foregoing embodiments, the descriptions of the embodiments have different emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The proposed system can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the above-described modules is merely a logical functional division, and in actual implementation, there may be another division, for example, a plurality of modules may be combined or may be integrated into another system, or some features may be omitted, or not executed.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. A method for detecting abnormal discharge of ultraviolet imaging of digital power equipment is characterized by comprising the following steps:
detecting a plurality of power equipment detection points according to the detection tasks, and associating the detection tasks with corresponding power equipment detection point information to obtain an ultraviolet imaging detection file;
carrying out integrity and compliance verification on the ultraviolet imaging detection file to form an ultraviolet imaging detection file library;
positioning a discharge position based on the ultraviolet imaging detection file after verification in the ultraviolet imaging detection file library, and giving a detection result according to the positioning discharge position;
the ultraviolet imaging detection file positioning discharge position after verification in the ultraviolet imaging detection file library specifically comprises the following steps:
extracting an ultraviolet intensity matrix and a visible light image based on the verified ultraviolet imaging detection file;
performing spot segmentation based on the ultraviolet intensity matrix to obtain a discharge center area;
and mapping the edge information of the divided discharge central area into a visible light image to obtain an abnormal discharge position.
2. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 1, wherein the detection task comprises a plurality of pieces of detection information, and each piece of detection information comprises the following fields:
the device comprises a measuring point serial number, a station name, a station code, a tested device name, a tested device code, a measuring point name and a measuring point code.
3. The method for detecting ultraviolet imaging discharge abnormity of digital power equipment as claimed in claim 1, wherein the ultraviolet imaging detection file comprises a file length, a specification version number, a file generation time, a site name, a site code, weather, temperature, humidity, an instrument manufacturer, an instrument model, an instrument version number, system frequency, a spectrum number, longitude, latitude, altitude, a spectrum and a reserved field;
the map comprises a map type code, a map data length, a map generation time, a tested device name, a tested device code, a measuring point name, a measuring point code, a detection channel mark, a storage data type, a detection distance, an accumulation duration, a frame acquisition frequency, an output frame rate, a frame number, a gain, a light spot color, a binarization threshold value, a photon number, a discharge state, a visible light zoom, a visible light exposure value, a visible light image data length, an image width, an image height, an ultraviolet intensity matrix, visible light image data and a reserved field.
4. The method for detecting the ultraviolet imaging discharge abnormality of the digital power equipment as claimed in claim 1, wherein the spot segmentation is performed based on the ultraviolet intensity matrix to obtain a discharge center region, specifically:
graying the ultraviolet intensity matrix to form a gray discharge image;
performing histogram statistics on the gray light spot area based on the gray discharge image;
determining a segmentation threshold of the gray level discharge image according to the histogram statistical result;
and segmenting the gray level discharge image based on the segmentation threshold value to obtain a binarization result, namely a discharge center area.
5. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment, as claimed in claim 4, wherein the determining the segmentation threshold value of the gray scale discharge image according to the histogram statistic result comprises:
according to data in 7 th to 10 th intervals in the histogram;
determining a gray level intermediate value of an interval with the maximum number of pixel points of the histogram;
the gradation center value is used as a division threshold of the gradation discharge image.
6. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 5, wherein the segmentation threshold of the gray-scale discharge image is defined by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
，
，
is a firstiThe number of the pixel points in each interval,Hthe histogram is a sequence of the number of pixels.
7. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 1, wherein the discharge position comprises the following information:
a discharge center coordinate;
the central discharge range is the number of the pixel points in the discharge central area;
the width and height of the smallest circumscribed rectangle of the discharge center region.
8. The method for detecting the ultraviolet imaging discharge abnormality of the digital power equipment as claimed in claim 1, wherein the step of giving a diagnosis result according to the positioning discharge position comprises the following steps:
obtaining an identification area to be classified by amplifying the minimum circumscribed rectangular area of the discharge center area by two times;
mapping the edge information of the identification area to be classified into a visible light image to obtain the identification image to be classified;
carrying out automatic classification and identification on the equipment components on the images to be classified and identified to obtain discharge components;
based on the discharge part, a detection result is obtained.
9. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 8, wherein the detection result comprises:
a discharge center coordinate, a center discharge range, and a discharge center part.
10. The utility model provides a digital power equipment ultraviolet formation of image discharge anomaly detection system which characterized in that includes:
the data acquisition module is configured to detect a plurality of power equipment detection points according to the detection tasks, and associate the detection tasks with corresponding power equipment detection point information to obtain an ultraviolet imaging detection file;
the file library construction module is configured to carry out integrity and compliance verification on the ultraviolet imaging detection file to form an ultraviolet imaging detection file library;
the discharge detection module is configured to locate a discharge position based on the verified ultraviolet imaging detection file in the ultraviolet imaging detection file library, and give a detection result according to the located discharge position;
the ultraviolet imaging detection file positioning discharge position after verification in the ultraviolet imaging detection file library specifically comprises the following steps:
extracting an ultraviolet intensity matrix and a visible light image based on the verified ultraviolet imaging detection file;
performing light spot segmentation based on the ultraviolet intensity matrix to obtain a discharge central area;
and mapping the edge information of the divided discharge central area into a visible light image to obtain an abnormal discharge position.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115527161A (en) * | 2022-09-13 | 2022-12-27 | 中国南方电网有限责任公司超高压输电公司广州局 | Abnormal discharge monitoring method and device, computer equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101477631A (en) * | 2009-01-20 | 2009-07-08 | 深圳先进技术研究院 | Method, equipment for extracting target from image and human-machine interaction system |
| KR101332715B1 (en) * | 2013-08-19 | 2013-11-26 | 한국 전기안전공사 | Method for diagnosising power facility using uv camera |
| CN107907803A (en) * | 2017-11-23 | 2018-04-13 | 南京杰迈视讯科技有限公司 | A kind of portable augmented reality ultraviolet imagery system |
| JP2020099016A (en) * | 2018-12-19 | 2020-06-25 | 株式会社オーケー社鹿児島 | Weak discharge imaging system |
| CN111443264A (en) * | 2020-04-30 | 2020-07-24 | 国网江苏省电力有限公司电力科学研究院 | Corona ultraviolet imaging equipment-based corona discharge intensity identification method and system and storage medium |
| CN111833312A (en) * | 2020-06-22 | 2020-10-27 | 国网江苏省电力有限公司电力科学研究院 | Ultraviolet image diagnosis method and system for detecting discharge of fault insulator |
| WO2020224458A1 (en) * | 2019-05-07 | 2020-11-12 | 国网山东省电力公司电力科学研究院 | Method for detecting corona discharge employing image processing |
| CN113506312A (en) * | 2021-06-24 | 2021-10-15 | 上海电力大学 | Ultraviolet discharge image segmentation method and computer readable medium |
-
2022
- 2022-06-21 CN CN202210701169.4A patent/CN114779031B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101477631A (en) * | 2009-01-20 | 2009-07-08 | 深圳先进技术研究院 | Method, equipment for extracting target from image and human-machine interaction system |
| KR101332715B1 (en) * | 2013-08-19 | 2013-11-26 | 한국 전기안전공사 | Method for diagnosising power facility using uv camera |
| CN107907803A (en) * | 2017-11-23 | 2018-04-13 | 南京杰迈视讯科技有限公司 | A kind of portable augmented reality ultraviolet imagery system |
| JP2020099016A (en) * | 2018-12-19 | 2020-06-25 | 株式会社オーケー社鹿児島 | Weak discharge imaging system |
| WO2020224458A1 (en) * | 2019-05-07 | 2020-11-12 | 国网山东省电力公司电力科学研究院 | Method for detecting corona discharge employing image processing |
| CN111443264A (en) * | 2020-04-30 | 2020-07-24 | 国网江苏省电力有限公司电力科学研究院 | Corona ultraviolet imaging equipment-based corona discharge intensity identification method and system and storage medium |
| CN111833312A (en) * | 2020-06-22 | 2020-10-27 | 国网江苏省电力有限公司电力科学研究院 | Ultraviolet image diagnosis method and system for detecting discharge of fault insulator |
| CN113506312A (en) * | 2021-06-24 | 2021-10-15 | 上海电力大学 | Ultraviolet discharge image segmentation method and computer readable medium |
Non-Patent Citations (2)
| Title |
|---|
| 李林发 等: "基于紫外成像的电晕放电参数变化特性及距离修正方法研究", 《水电能源科学》 * |
| 王胜辉 等: "基于改进SSD算法和紫外成像的悬式绝缘子放电严重程度评估", 《华北电力大学学报(自然科学版)》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115527161A (en) * | 2022-09-13 | 2022-12-27 | 中国南方电网有限责任公司超高压输电公司广州局 | Abnormal discharge monitoring method and device, computer equipment and storage medium |
| CN115527161B (en) * | 2022-09-13 | 2024-04-02 | 中国南方电网有限责任公司超高压输电公司广州局 | Abnormal discharge monitoring method, device, computer equipment and storage medium |
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