CN102519974B - Method for detecting cracking of composite insulator based on intelligent image identification - Google Patents
Method for detecting cracking of composite insulator based on intelligent image identification Download PDFInfo
- Publication number
- CN102519974B CN102519974B CN201110419583.8A CN201110419583A CN102519974B CN 102519974 B CN102519974 B CN 102519974B CN 201110419583 A CN201110419583 A CN 201110419583A CN 102519974 B CN102519974 B CN 102519974B
- Authority
- CN
- China
- Prior art keywords
- composite insulator
- image
- cluster parachute
- full
- slight crack
- 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
Images
Landscapes
- Insulators (AREA)
Abstract
The invention provides a method for detecting the cracking of a composite insulator based on the intelligent image identification. A high spatial resolution camera is adopted to image the composite insulator, the obtained image is pretreated and undergoes edge detection, and cracking characteristics are extracted from the image to determine the cracking degree of the composite insulator. According to the method based on the image identification in the invention, the online detection of the cracking case of the composite insulator can be realized without the tower climbing of a worker, the onsite detection difficulty is small, and the early discovery and the replacement of the cracked composite insulator can avoid generations of power grid safety accidents.
Description
Technical field
The present invention relates to a kind of composite insulator be full of cracks detection method, belong to power transmission and transforming equipment running status maintenance field, relate in particular to a kind of composite insulator be full of cracks detection method based on image intelligent identification, can be used for the be full of cracks state of scene with electro-detection composite insulator.
Background technology
Composite insulator has good anti-fouling flashover performance, is not easy breakdownly, and there will not be the problems such as the cluster parachute self-destruction of null value, low value and the glass insulator of porcelain insulator.The eighties in 20th century, China experts and scholars have launched the research and development to composite insulator on the basis of drawing external experience, and mid-term, sample dropped into trial run the latter stage eighties.At the beginning of the nineties, there is pollution flashover accident in various places in succession, and because anti-pollution characteristic is good, composite insulator is put into linked network and uses.To the end of the year 1994, the composite insulator of hanging net operation reaches 50,000.Since then, composite insulator networking quantity rapidly increases: nineteen ninety-five is 100,000, within 1998, is 460,000, and calendar year 2001 is 1,600,000, and within 2005, hanging net operation has reached 3,000,000.End in Dec, 2010, the 66kV of State Grid Corporation of China's administration and above circuit account for electric pressure circuit all types of the same race at 37.02% of fortune insulator number at fortune composite insulator number.
From current ruuning situation, the operational reliability of composite insulator is better than porcelain insulator and glass insulator.But, along with the increase of the operation time limit, umbrella cover material embrittlement, sclerosis, efflorescence, cracking, core exposure, there is partial discharge phenomenon in insulating surface, hydrophobicity performance the problem such as weakens and highlights gradually.Insulator not only will play insulating effect to electrical equipment or conductor, also will play fixing suspension effect, and deteriorated insulator will threaten the safe operation of electrical network.
Experts and scholars have launched large quantity research to the detection method of insulator both at home and abroad, existing composite insulator detection method has contact, contactless, wherein contact measurement method comprises voltage distribution, short-circuit fork method, sparking distance method, photo-electric test rod method, sound pulse detection method, Leakage Current mensuration, and non-contact detection method comprises ultrasonic Detection Method, laser-Doppler vibratory drilling method, infrared measurement of temperature method, corona video camera method, sonic detection and radiowave detection method.Contact measurement method need to manually be stepped on tower operation, is not suitable for Site Detection.In non-contact detection method, most methods, only to fault detect successfuls a certain or that certain is several, are still difficult to detect to the fault of other types, and equipment needed thereby costliness, and it is not very desirable detecting effect.
The be full of cracks of composite insulator material can cause core exposure, is exposed to airborne plug and is easily corroded, and brittle failure even occurs in physical strength reduction.Because composite insulator is excellent type structure, once lose efficacy, will be greater than by the molecular insulator chain of multiple insulation the impact of transmission line of electricity.Existing composite insulator be full of cracks detection method is only suitable for carrying out in laboratory mostly, and cost is high, and workload is large, is not suitable for on-the-spot band electro-detection, and composite insulator lacks suitable in-situ check and test method and device.
About for example application number of bibliographical information of this respect liquid crystal picture by name that is 200520006400.X shows the utility model patent of the charged detector of high voltage composite insulators, a kind of device with electro-detection high voltage composite insulators defect is disclosed, conductive defect, the inside that can identify charged composite insulator come to nothing and composite insulator string in low null value insulation.But above-mentioned patent does not relate to the detection method of the be full of cracks situation of scene with electro-detection composite insulator.
In view of this, be necessary to provide a kind of composite insulator based on image recognition be full of cracks detection method, can the on-the-spot running status with electro-detection composite insulator, and the be full of cracks situation of composite insulator is detected to analysis.
Summary of the invention
Technical matters to be solved by this invention is: the deficiency existing for prior art, the detection method that provides a kind of composite insulator to chap, needn't step on tower, need not dismantle composite insulator, can detect at the scene the be full of cracks situation of composite insulator.
The technical solution adopted in the present invention is: a kind of composite insulator be full of cracks detection method based on image intelligent identification, it is characterized in that, and comprise the following steps:
1) use high spatial resolution camera to composite insulator imaging, obtain the high spatial resolution image of composite insulator;
2) image pre-service: the image of composite insulator is carried out to pre-service, comprise geometry correction, radiant correction, denoising, to obtain comparatively accurate spectral information;
3) rim detection: adopt the level and smooth image of Gaussian filter, by single order local derviation finite difference compute gradient amplitude and direction, gradient magnitude is carried out to non-maximum value inhibition, use dual threshold algorithm detect and be connected edge;
4) extract slight crack: first, determine the scope of composite insulator according to the result of rim detection, the result of rim detection is followed to the raw video fit of composite insulator, determine the pixel coverage of composite insulator cluster parachute, and by different gray-scale value mark for cluster parachutes different on image; Then, to each cluster parachute, the edge in its pixel coverage of mark, and judge whether edge is slight crack, wherein, judge that the method for slight crack is: if the threshold value that outnumbers of marginal point continuous pixels is judged to be slight crack by this edge, if do not have, be not slight crack; Finally, can obtain the slight crack of all cluster parachutes;
5) judge the be full of cracks situation of composite insulator: according to the cluster parachute scope of composite insulator, calculate a pixel count N that cluster parachute comprises
1, to this cluster parachute, according to the slight crack judged before, calculate pixel and the N of the slight crack comprising in this cluster parachute
2; Order
, judge by the scope of threshold value the degree that composite insulator chaps, if t is more than or equal to threshold value, this cluster parachute chaps; If t is less than threshold value, this cluster parachute does not chap; Judge one by one the be full of cracks degree of each cluster parachute on composite insulator, if there is a cluster parachute be full of cracks, judge whole string composite insulator be full of cracks; If cluster parachute all occurs without be full of cracks situation, judge that whole string composite insulator does not chap.
The invention has the beneficial effects as follows: the method that the present invention is based on image recognition can detect the be full of cracks situation of composite insulator online, do not need workman Deng Ta, Site Detection difficulty is little, and the composite insulator of finding early and replace be full of cracks can be avoided the generation of power grid security accident.
Brief description of the drawings
Fig. 1 is the Technology Roadmap of the composite insulator be full of cracks detection method based on image intelligent identification of the embodiment of the present invention.
Fig. 2 is the enforcement block diagram that obtains high spatial resolution image in Fig. 1.
Fig. 3 is the pretreated process flow diagram of image in Fig. 1.
Fig. 4 is the enforcement block diagram that extracts slight crack in Fig. 1.
Fig. 5 is the method block diagram that judges composite insulator be full of cracks situation in Fig. 1.
Embodiment
In order to understand better the present invention, further illustrate content of the present invention below in conjunction with embodiment, but content of the present invention is not only confined to the following examples.Those skilled in the art can make various changes or modifications the present invention, and these equivalent form of values are equally within the listed claims limited range of the application.
Description of symbols in accompanying drawing: 1-obtains high spatial resolution image, the pre-service of 2-image, 3-rim detection, 4-slight crack extracts, and 5-judges the be full of cracks situation of composite insulator, 1.1-composite insulator, 1.2-high spatial resolution camera, 1.3-high spatial resolution image, 2.1-geometry correction, 2.2-radiant correction, 2.3-denoising, 2.4-image after treatment, the pixel coverage of 4.1-composite insulator cluster parachute, 4.2-slight crack, the be full of cracks situation of 5.1-cluster parachute, the be full of cracks situation of 5.2-composite insulator.
Principle of work of the present invention: high spatial resolution image can reflect the detailed information that subject is abundant, if composite insulator has slight crack, on high spatial resolution image, can be resolved out, therefore, only need scene to carry out imaging to composite insulator, can analyze the be full of cracks situation of composite insulator by image.On image, slight crack has certain shape facility, can be by the slight crack situation of its corresponding composite insulator of analysis of texture of extraction image.
Fig. 1 is Technology Roadmap of the present invention.First composite insulator based on image recognition be full of cracks detection method provided by the invention will obtain the high spatial resolution image of composite insulator, image pre-service 2, and then rim detection 3, extracts slight crack 4, judges the be full of cracks situation 5 of composite insulator.
Fig. 2 is the enforcement block diagram that obtains high spatial resolution image in Fig. 1, directly uses high spatial resolution camera to composite insulator imaging, then image is carried out to pre-service.Pretreated flow process as shown in Figure 3, is carried out geometry correction 2.1, radiant correction 2.2 to high spatial resolution image 1.3, and then denoising 2.3 obtains compound inslation sub-image after treatment.
To compound inslation sub-image after treatment, compound inslation sub-image is carried out to rim detection with canny operator, step is as follows: with the level and smooth image of Gaussian filter, by single order local derviation finite difference compute gradient amplitude and direction, gradient magnitude is carried out to non-maximum value inhibition, use dual threshold algorithm detect and be connected edge.
Fig. 4 is the enforcement block diagram that extracts slight crack in Fig. 1.First, determine the scope of composite insulator according to the result of rim detection, the result of rim detection is followed to the raw video fit of composite insulator, determine the pixel coverage of composite insulator cluster parachute, and by different gray-scale value mark for cluster parachutes different on image.Then, to each cluster parachute, the edge in its pixel coverage of mark, and judge whether edge is slight crack.Wherein, judge that the method for slight crack is: if the threshold value that outnumbers of marginal point continuous pixels is judged to be slight crack by this edge, if do not have, be not slight crack.Finally, can obtain the slight crack of all cluster parachutes.
Obtain after the cluster parachute scope and slight crack of composite insulator, judged the method for composite insulator be full of cracks degree as shown in Figure 5.According to the cluster parachute scope of composite insulator, calculate a pixel count N that cluster parachute comprises
1, to this cluster parachute, according to the slight crack judged before, calculate pixel and the N of the slight crack comprising in this cluster parachute
2.Order
, judge by the scope of threshold value the degree that composite insulator chaps, if t is more than or equal to threshold value, this cluster parachute chaps; If t is less than threshold value, this cluster parachute does not chap.Judge one by one the be full of cracks degree of each cluster parachute on composite insulator, if there is a cluster parachute be full of cracks, judge whole string composite insulator be full of cracks; If cluster parachute all occurs without be full of cracks situation, judge that whole string composite insulator does not chap.
The content not being described in detail in this instructions belongs to the known prior art of professional and technical personnel in the field.
Claims (1)
1. the composite insulator be full of cracks detection method based on image intelligent identification, is characterized in that, comprises the following steps:
1) use high spatial resolution camera to composite insulator imaging, obtain the high spatial resolution image of composite insulator;
2) image pre-service: the image of composite insulator is carried out to pre-service, comprise geometry correction, radiant correction, denoising, to obtain comparatively accurate spectral information;
3) rim detection: adopt the level and smooth image of Gaussian filter, by single order local derviation finite difference compute gradient amplitude and direction, gradient magnitude is carried out to non-maximum value inhibition, use dual threshold algorithm detect and be connected edge;
4) extract slight crack: first, determine the scope of composite insulator according to the result of rim detection, the result of rim detection is followed to the raw video fit of composite insulator, determine the pixel coverage of composite insulator cluster parachute, and by different gray-scale value mark for cluster parachutes different on image; Then, to each cluster parachute, the edge in its pixel coverage of mark, and judge whether edge is slight crack, wherein, judge that the method for slight crack is: if the threshold value that outnumbers of marginal point continuous pixels is judged to be slight crack by this edge, if do not have, be not slight crack; Finally, can obtain the slight crack of all cluster parachutes;
5) judge the be full of cracks situation of composite insulator: according to the cluster parachute scope of composite insulator, calculate a pixel count N that cluster parachute comprises
1, to this cluster parachute, according to the slight crack judged before, calculate pixel and the N of the slight crack comprising in this cluster parachute
2; Order
, judge by the scope of threshold value the degree that composite insulator chaps, if t is more than or equal to threshold value, this cluster parachute chaps; If t is less than threshold value, this cluster parachute does not chap; Judge one by one the be full of cracks degree of each cluster parachute on composite insulator, if there is a cluster parachute be full of cracks, judge whole string composite insulator be full of cracks; If cluster parachute all occurs without be full of cracks situation, judge that whole string composite insulator does not chap.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110419583.8A CN102519974B (en) | 2011-12-15 | 2011-12-15 | Method for detecting cracking of composite insulator based on intelligent image identification |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110419583.8A CN102519974B (en) | 2011-12-15 | 2011-12-15 | Method for detecting cracking of composite insulator based on intelligent image identification |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102519974A CN102519974A (en) | 2012-06-27 |
| CN102519974B true CN102519974B (en) | 2014-07-02 |
Family
ID=46290964
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110419583.8A Active CN102519974B (en) | 2011-12-15 | 2011-12-15 | Method for detecting cracking of composite insulator based on intelligent image identification |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102519974B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103886610B (en) * | 2014-04-05 | 2016-08-17 | 东北电力大学 | A kind of insulator image defect detection method |
| CN108737686A (en) * | 2018-06-11 | 2018-11-02 | 昆明理工大学 | Edge enhancing error based on image coefficient change spreads digital halftoning method |
| CN109615656A (en) * | 2018-11-20 | 2019-04-12 | 哈尔滨理工大学 | A kind of backbone localization method based on pattern search |
| CN109884468B (en) * | 2019-03-05 | 2020-06-02 | 河海大学 | Insulator self-explosion defect detection method based on image pixel accumulation analysis |
| CN111260637B (en) * | 2020-01-19 | 2022-12-13 | 石家庄铁道大学 | Asphalt road transverse fracture detection method based on regional difference |
| CN112379225A (en) * | 2020-10-31 | 2021-02-19 | 国网天津市电力公司 | Power equipment corona identification and evaluation alarm system and use method thereof |
| CN113622239A (en) * | 2021-09-28 | 2021-11-09 | 吴海涛 | Local strengthening method for road subgrade |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101609053A (en) * | 2009-07-24 | 2009-12-23 | 国网电力科学研究院武汉南瑞有限责任公司 | A kind of intelligent insulator on-line monitoring device and method thereof |
| CN102230893A (en) * | 2011-03-28 | 2011-11-02 | 广西电网公司电力科学研究院 | Quantitative identification method of composite insulator umbrella skirt aging |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3215646B2 (en) * | 1997-02-25 | 2001-10-09 | 日本碍子株式会社 | Inspection method for defective primer application and inspection apparatus used for the method |
-
2011
- 2011-12-15 CN CN201110419583.8A patent/CN102519974B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101609053A (en) * | 2009-07-24 | 2009-12-23 | 国网电力科学研究院武汉南瑞有限责任公司 | A kind of intelligent insulator on-line monitoring device and method thereof |
| CN102230893A (en) * | 2011-03-28 | 2011-11-02 | 广西电网公司电力科学研究院 | Quantitative identification method of composite insulator umbrella skirt aging |
Non-Patent Citations (5)
| Title |
|---|
| JP特开平10-235267A 1998.09.08 |
| 基于彩色图像的玻璃绝缘子缺陷诊断;林聚财 等;《电网技术》;20110131;第35卷(第1期);全文 * |
| 基于航拍图像的绝缘子表面状态检测;葛玉敏 等;《高压电器》;20100430;第46卷(第4期);全文 * |
| 林聚财 等.基于彩色图像的玻璃绝缘子缺陷诊断.《电网技术》.2011,第35卷(第1期),全文. |
| 葛玉敏 等.基于航拍图像的绝缘子表面状态检测.《高压电器》.2010,第46卷(第4期),全文. |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102519974A (en) | 2012-06-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102519974B (en) | Method for detecting cracking of composite insulator based on intelligent image identification | |
| CN102520286B (en) | Hyperspectrum-based composite insulator operation state classification method | |
| CN102520323B (en) | Hyperspectrum-based composite insulator aging operating state detection method | |
| CN102519846B (en) | Hyperspectrum-based composite insulator hydrophobicity detection method | |
| CN101487866B (en) | On-line detection method for AC power transmission line porcelain zero resistance insulator based on infrared thermal imaging | |
| CN103926510B (en) | A kind of cable sheath electric current and current-carrying capacity on-line monitoring and fault diagonosing localization method | |
| CN106680285B (en) | Method for recognizing insulator contamination state based on infrared image assisted visible light image | |
| CN111754465B (en) | Insulator positioning and string dropping detection method | |
| CN110349128B (en) | Method for detecting icicle bridging degree between glass insulator umbrellas | |
| CN104849287A (en) | Composite insulator contamination degree non-contact detection method | |
| CN104267063A (en) | Low-value insulator detection method based on infrared thermography | |
| CN103063166A (en) | Detection method and device for wind deflection angle of suspension type composite insulator chain | |
| CN102419408B (en) | System and method for determining single-phase disconnection fault sections based on load monitors | |
| CN101672885A (en) | Method for on-line detecting external insulation state of electric transmission and transformation equipment | |
| CN109827662A (en) | Determination method based on dead wind area low resistance insulator infrared detection temperature threshold | |
| CN204679591U (en) | A kind of leakage conductor state measuring device with electricity based on electric field method | |
| CN114283330B (en) | Online inspection identification method and system based on multi-source data | |
| Changfu et al. | Research of substation equipment abnormity identification based on image processing | |
| Zhong et al. | Mobile robot for inspection of porcelain insulator strings | |
| CN107544006A (en) | Experimental method for electric transmission line isolator type selecting under the big temperature difference of high wind sand and dust | |
| Pan | Intelligent image recognition research on status of power transmission lines | |
| Ni et al. | Research on Insulator Defect Detection Method Based on Image Processing and Watershed Algorithm | |
| CN108108682B (en) | Insulator flashover fault positioning method and system | |
| Li et al. | Research on the UAV Intelligent Inspection System to Monitor and Prevent Abnormal Heat of Composite Insulators for 500kV Transmission System | |
| CN104616020A (en) | Method and system for detecting icing of transmission line based on clustering analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |