CN114779031B - 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
- Publication number
- CN114779031B CN114779031B CN202210701169.4A CN202210701169A CN114779031B CN 114779031 B CN114779031 B CN 114779031B CN 202210701169 A CN202210701169 A CN 202210701169A CN 114779031 B CN114779031 B CN 114779031B
- Authority
- CN
- China
- Prior art keywords
- discharge
- detection
- ultraviolet imaging
- ultraviolet
- file
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 171
- 238000003384 imaging method Methods 0.000 title claims abstract description 105
- 238000000034 method Methods 0.000 claims abstract description 23
- 230000002159 abnormal effect Effects 0.000 claims abstract description 18
- 238000012795 verification Methods 0.000 claims abstract description 6
- 239000011159 matrix material Substances 0.000 claims description 26
- 230000011218 segmentation Effects 0.000 claims description 26
- 238000013507 mapping Methods 0.000 claims description 11
- 238000013500 data storage Methods 0.000 claims description 9
- 230000005856 abnormality Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- 230000015572 biosynthetic process Effects 0.000 claims 1
- 238000012545 processing Methods 0.000 abstract description 9
- 238000003745 diagnosis Methods 0.000 abstract description 8
- 238000007726 management method Methods 0.000 description 9
- 238000004891 communication Methods 0.000 description 7
- 230000003993 interaction Effects 0.000 description 3
- 238000007635 classification algorithm Methods 0.000 description 2
- 238000000105 evaporative light scattering detection Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009422 external insulation Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000011269 treatment regimen Methods 0.000 description 1
- 238000000825 ultraviolet detection Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1218—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using optical methods; using charged particle, e.g. electron, beams or X-rays
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
-
- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Photometry And Measurement Of Optical Pulse Characteristics (AREA)
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 verified ultraviolet imaging detection file 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 constitute prior art.
As a common detection means of power equipment, ultraviolet imaging can discover potential external insulation hazards or damages as soon as possible, and has great significance for reducing equipment failure rate and ensuring safe operation of a power system.
The traditional ultraviolet image reflects a discharge area in a form of binary light spots, when an instrument outputs detection data, the instrument directly carries out binary processing on detected strong and weak information, and a binary threshold value is unknown, so that the strong and weak difference of all discharge points in the light spot area in the detection image cannot be seen, 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 have differences.
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 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.
Further, 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.
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 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.
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 grayscale 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.
Further, the determining a segmentation threshold of the gray-scale discharge image according to the histogram statistic result 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;
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 the following formula:
,is as followsiThe number of the pixel points in each interval,Hthe histogram is a sequence of the number of pixels.
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 a region to be classified and identified by amplifying the minimum circumscribed rectangular region of the discharge center region 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.
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 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 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 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 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 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.
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 abnormal discharge in ultraviolet imaging 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 device according to an embodiment of the present invention;
FIG. 4 is a test image of a conventional UV imaging device according to an embodiment of the present invention;
fig. 5 is a detection image generated by a method for detecting abnormal discharge in ultraviolet imaging 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 abnormal ultraviolet imaging discharge 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 a terminal and a server, and is implemented by 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 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 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 discharging 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 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;
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,,,is as followsiThe number of the pixel points in each interval,Ha sequence of the number of pixels of the histogram;
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 pixels 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 images to be classified and identified to obtain discharge components;
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 part.
At present, ultraviolet channels of the existing imaging devices on the market are all displayed in a binarization mode, the whole discharge light spot area is white, and the actual strongest discharge area 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 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 detection file can be intelligently processed and analyzed, the discharge position can be quickly positioned, and a diagnosis result can be given.
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 entire discharge area, except for the areas of weaker intensity.
As shown in FIG. 2, byHRefers to the sequence of the number of pixels of the histogram,,is as followsiThe 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 of the whole light spot area.
Segmentation thresholdt =((idx-1)*gap+1+idx*gap)/2
In an example of the present invention,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 area,
3) discharge center region width w, height h.
The above information is obtained by automatically processing the ultraviolet image, and an intelligent classification module of the discharge component is mounted on the intelligent terminal, so as to automatically identify and label the name of the component in which the discharge occurs, such as a typical component of equipment such as a joint, a sleeve, a lead, a fitting, and the like.
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 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.
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, and 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 File Overall 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 a background management system, and generally comprises hundreds of detection points by taking a transformer substation as an example; after the detection task is obtained, the detection task is issued to an imaging device, the imaging device side performs overall checking through a task management module, and the detection task is transmitted back to the intelligent terminal after the 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 diagnosis characteristic quantity in the detection file is automatically extracted and displayed, field personnel are assisted in real time to deal with abnormal conditions in a targeted manner, and a processing strategy is rapidly 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 area generated by each manufacturer are different, and the statistical modes are 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 using three characteristic quantities, namely the discharge center coordinate, the center discharge range and the discharge center part, and a new digital operation process is relied on, so that 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 division, and in actual implementation, there may be other divisions, for example, multiple modules may be combined or 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 (9)
1. A method for detecting abnormal discharge of digital power equipment by ultraviolet imaging 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; the ultraviolet imaging detection file comprises a file length, a standard 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, map number, longitude, latitude, altitude, a map 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, data storage types, 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;
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 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 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.
3. The method for detecting the abnormal discharge in the ultraviolet imaging 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, and specifically comprises:
graying the ultraviolet intensity matrix to form a grayscale 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.
4. The method for detecting ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 3, wherein the determining the segmentation threshold of the gray scale discharge image according to the histogram statistics result comprises:
determining a gray level intermediate value of an interval with the maximum number of pixel points of the histogram according to data in a 7 th interval to a 10 th interval in the histogram;
the gray level intermediate value is used as a division threshold value of a gray level discharge image.
5. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 4, wherein the segmentation threshold of the gray-scale discharge image is defined by the following formula:
6. 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 pixels in the discharge central area;
the width and height of the smallest circumscribed rectangle of the discharge center region.
7. 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 detection result according to the positioning discharge position specifically comprises the steps of:
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 images to be classified and identified to obtain discharge components;
based on the discharge part, a detection result is obtained.
8. The method for detecting the ultraviolet imaging discharge abnormity of the digital power equipment as claimed in claim 7, wherein the detection result comprises:
a discharge center coordinate, a center discharge range, and a discharge center component.
9. 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 ultraviolet imaging detection file comprises a file length, a standard 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, map number, longitude, latitude, altitude, a map 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, data storage types, 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;
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 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 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.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210701169.4A CN114779031B (en) | 2022-06-21 | 2022-06-21 | Digital power equipment ultraviolet imaging discharge abnormity detection method and system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210701169.4A CN114779031B (en) | 2022-06-21 | 2022-06-21 | Digital power equipment ultraviolet imaging discharge abnormity detection method and system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114779031A CN114779031A (en) | 2022-07-22 |
CN114779031B true CN114779031B (en) | 2022-09-23 |
Family
ID=82421707
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210701169.4A Active CN114779031B (en) | 2022-06-21 | 2022-06-21 | Digital power equipment ultraviolet imaging discharge abnormity detection method and system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114779031B (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
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 |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101477631B (en) * | 2009-01-20 | 2011-01-19 | 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 |
CN110146791A (en) * | 2019-05-07 | 2019-08-20 | 国网山东省电力公司电力科学研究院 | A kind of corona detection method based on image procossing |
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 |
CN111833312B (en) * | 2020-06-22 | 2022-09-09 | 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 |
-
2022
- 2022-06-21 CN CN202210701169.4A patent/CN114779031B/en active Active
Also Published As
Publication number | Publication date |
---|---|
CN114779031A (en) | 2022-07-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111461068B (en) | Chromosome metaphase map identification and segmentation method | |
CN113095438B (en) | Wafer defect classification method, device and system thereof, electronic equipment and storage medium | |
CN110706206A (en) | Fluorescent cell counting method, fluorescent cell counting device, terminal equipment and storage medium | |
CN111784692A (en) | Method and device for detecting insulator defects in power system and electronic equipment | |
CN114779031B (en) | Digital power equipment ultraviolet imaging discharge abnormity detection method and system | |
US20220222799A1 (en) | Method for detecting defect in products and electronic device using method | |
CN113255590A (en) | Defect detection model training method, defect detection method, device and system | |
CN110674834A (en) | Geo-fence identification method, device, equipment and computer-readable storage medium | |
CN113762229B (en) | Intelligent identification method and system for building equipment in building site | |
CN103913150B (en) | Intelligent electric energy meter electronic devices and components consistency detecting method | |
CN116343255B (en) | Automatic check system for optical character plate in picture | |
CN110310341B (en) | Method, device, equipment and storage medium for generating default parameters in color algorithm | |
CN112818165A (en) | Data processing method, device, equipment and storage medium | |
CN117129527A (en) | Urban road paving quality detection method and system | |
CN111931721A (en) | Method and device for detecting color and number of annual inspection label and electronic equipment | |
CN116563841A (en) | Detection method and detection device for power distribution network equipment identification plate and electronic equipment | |
CN115760854A (en) | Deep learning-based power equipment defect detection method and device and electronic equipment | |
CN116091481A (en) | Spike counting method, device, equipment and storage medium | |
CN113079052B (en) | Model training method, device, equipment and storage medium, and method and device for identifying data of Internet of things | |
CN111292374B (en) | Method and equipment for automatically plugging and unplugging USB interface | |
CN110503685B (en) | Data processing method and equipment | |
CN114782955A (en) | Buried point processing method, electronic device, and storage medium | |
CN117912003B (en) | License plate recognition method and system based on deep learning | |
CN116665138B (en) | Visual detection method and system for stamping processing of automobile parts | |
CN116071369B (en) | Infrared image processing method and device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |