CN100469138C - Power transformer draught fan state recognizing method based on video monitoring and image recognition - Google Patents
Power transformer draught fan state recognizing method based on video monitoring and image recognition Download PDFInfo
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- CN100469138C CN100469138C CNB2006100807317A CN200610080731A CN100469138C CN 100469138 C CN100469138 C CN 100469138C CN B2006100807317 A CNB2006100807317 A CN B2006100807317A CN 200610080731 A CN200610080731 A CN 200610080731A CN 100469138 C CN100469138 C CN 100469138C
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Abstract
The disclosed state recognition method for a fan of power transformer comprises: with camera, decoder and video server, sending acquired signal to monitor center for remote video monitor; extracting target picture; then, analyzing, processing and recognizing the digital picture. This invention can auto recognize and alarm fault for fast fault diagnosis on power enterprise.
Description
Technical field
The invention belongs to remote digital video monitoring and image recognition technology and power transformer Fan Equipment monitoring running state technical field.Specifically, relate to application image gray processing, binaryzation, expansion, normalized image preconditioning technique to power transformer Fan Equipment treatment of picture and identification, power transformer Fan Equipment running status is carried out a kind of power transformer fan condition recognition methods of automated graphics identification and fault warning based on video monitoring and image recognition.
Background technology
At present to the power transformer Fan Equipment running status technological means that adopted of monitoring automatically, be in the blower fan power supply circuits, detect electric current have or not determine whether blower fan rotates.When fan electromotor broke down, this moment, blower fan stopped operating, and existing monitoring means is if detect, and the temperature that will cause power transformer is too high and finally burn, and makes electric power enterprise production suffer great loss.Therefore, this monitoring means is insecure.Adopt remote digital video monitoring and image recognition technology that the Fan Equipment running status is monitored, more directly perceived more, effective than existing monitoring means, and do not need contact arrangement, avoided interference to the normal operation of equipment.
Power transformer is very crucial equipment in transformer station, utilization remote digital video monitoring and image recognition technology, power transformer fan operation state is monitored in real time, by automatic identification and the fault warning of image processing techniques realization, very important realistic meaning is arranged to the power transformer fan condition.
Remote digital video monitoring and image identification system combine remote digital video monitoring and image recognition technology exactly, at first by equipment such as camera, decoder and video servers, the digital video signal that collects is sent back Surveillance center by transmission channel in real time in the mode of video flowing, in Surveillance center remote video monitoring is carried out at the scene, intercepting monitored object picture is analyzed, is handled and discern digital video image by corresponding image preconditioning technique from video flowing.Therefore use monitoring remote video and image recognition technology, can realize automatic identification and fault warning power transformer fan operation state.This technology provides a kind of new accurate means directly perceived for guaranteeing electric power enterprise production safety and quick diagnosis fault.
Summary of the invention
The objective of the invention is provides a kind of power transformer fan condition recognition methods based on video monitoring and image recognition at the deficiencies in the prior art.Described power transformer Fan Equipment is responsible for the transformer heat radiation, is made up of 3 blades.According to the architectural feature of blower fan, realize that the technical scheme that the object of the invention adopted is at first power transformer blower fan picture to be carried out gray processing, binary conversion treatment extraction recognition objective flabellum; And then image carried out expansion process, to eliminate of the interference of flabellum catch net to image.Through after the preliminary treatment, when blower fan was in running status, image was a black annulus; When blower fan is in halted state,, make that image is a circle ring area that has white breach owing to have the slit between the flabellum.Experimental results demonstrate that black pixel point accounts for about 98% of whole circle ring area during fan operation; And blower fan is when stopping, and this value is about 75%.Among the present invention, by the residing circle ring area of fan in the scan image, black picture element is counted out and is accounted for total pixel number purpose ratio value in the calculating flabellum circle ring area of living in, passes through the cube computing again, after enlarging the difference under two kinds of situations, with parameter 0.68 ([(0.98)
3+ (0.75)
3]/2 ≈ 0.68) compares, can draw the fan condition of once differentiating; By after repeatedly getting image, preliminary treatment, differentiation, get the majority of repeatedly differentiating and differentiate the operating state that the result is current blower fan simultaneously.
The invention has the beneficial effects as follows when identification power transformer fan operation state, utilization remote digital video monitoring and image recognition technology, power transformer fan operation state is monitored in real time, adopt repeatedly result of experiment calculated threshold quantitative criteria, reduce the uncertainty in the identifying, recognition accuracy is reached more than 98%, reduce the error rate of recognition result; Therefore by automatic identification and the fault warning of image processing techniques realization, very important realistic meaning is arranged to the power transformer fan condition.
Description of drawings
Fig. 1 is the original image of identifying object one power transformer blower fan rotation of the present invention and halted state.
Fig. 2 is the gray-scale map of power transformer blower fan image preprocessing process.
Fig. 3 is the binaryzation figure as a result of power transformer blower fan image preprocessing process.
Fig. 4 is the expansion results figure of power transformer blower fan image preprocessing process.
Fig. 5 is the bianry image normalization result of power transformer blower fan image preprocessing process.
Fig. 6 is the flow chart of power transformer blower fan image recognition.
Embodiment
The present invention be directed to the deficiencies in the prior art and a kind of power transformer fan condition recognition methods based on video monitoring and image recognition is provided.Below in conjunction with accompanying drawing the present invention is further specified.
Fig. 1 is the original image of rotation of power transformer blower fan and halted state.Because the data volume of coloured image is big, convenient and swift for other features extraction of later stage, need carry out gray processing to image and handle.Gray-scale map (Grayscale) is only to contain monochrome information, does not contain the image of color information, just as we see at ordinary times brightness by dark to bright black-and-white photograph, variation is continuous.Therefore, represent gray-scale map, just need quantize brightness value.Usually be divided into 0 to 255 totally 256 ranks, 0 the darkest (complete black), 255 the brightest (complete white).From coloured image to obtaining by following formula for the transformation of gray-scale map:
Y＝0.299R+0.587G+0.114B
Wherein R represents red color component value; G represents green component values; B represents the blue component value.
Fig. 1 is carried out the gray processing operation, abandon the colouring information of image, obtain gray-scale map result such as Fig. 2.For recognition objective is separated from background, Fig. 2 is proceeded binary conversion treatment, make picture be converted to the bianry image that only has two kinds of gray values of black and white, result such as Fig. 3.The binaryzation of image will further be simplified step and the process that gray level image is handled.If the gray value scope of image f in [a, b], binary-state threshold be made as T (a≤T≤b), the general expression of binary conversion treatment can be expressed as follows:
f
TBe bianry image, come indicated object object area (black region) with 1 usually, represent background area (white portion) with 0.
The dilation operation of image also claims to expand computing, uses symbol
Expression, X expands with S and is designated as
It is defined as
X is the set of the point of target image in the formula, and S is the set of structural elements vegetarian refreshments.Because there is separation net Fan Equipment flabellum front portion; play the purpose of protection flabellum; but separation net can produce the netted interference of white at identified region after image binaryzation is handled, disturb in order to remove these, and the image of the method that this paper has adopted image expansion after to binaryzation handled.Fig. 3 is carried out expansion process, result such as Fig. 4.
In order to extract the blower fan feature normally, easily, need the image after the binaryzation is carried out the normalized of size, result such as Fig. 5.
When blower fan is in starting state, be the circular ring type zone of a black through the image after the expansion process; And when blower fan was in halted state, owing to have the space between three flabellums, image expansion was a breach circle ring area that has three whites after handling, and carried out the identification of blower fan work at present state according to this feature.Experimental results demonstrate that during fan starting, the black picture element in the image after the expansion in the flabellum circular ring type of living in zone is counted out and accounted for whole circular ring type area pixel about 98% of the summation of counting out; When blower fan stops, then be about 75%.The present invention counts by the black picture element in the calculating flabellum circular ring type of living in zone and accounts for the whole circular ring type zone size of the ratio of pixel number always, judges the residing state of current blower fan, and specific algorithm is as follows.
(1) scanning each pixel of circular ring type zone to be identified, " pixel counter " add one operation.If the pixel value of this pixel is 255 (whites), " white pixel point counter " does add one operation.Behind the end of scan, the value of " white pixel point counter " and " pixel counter " is number and this area pixel point sum of the white pixel point in zone to be identified.
(2) calculating regional black picture element to be identified is counted and is accounted for the percentage of whole district to be identified pixel sum:
Black picture element proportion=(pixel sum-white pixel the is counted)/pixel sum of counting.
(3) " black picture element count proportion " done simple cube computing, the relative difference of this value when being in two different conditions to increase blower fan;
Black picture element proportion=(black picture element count proportion) of counting
3
(4) identification is judged.
Wherein the computational process of parameter 0.68 is as follows:
[(0.98)
3+(0.75)
3]/2≈0.68
Fig. 6 is the flow chart of power transformer blower fan image recognition.
Utilize remote digital video monitoring and image recognition technology, realize the automated graphics identification and the fault warning of power transformer Fan Equipment running status, comprise algorithm and application program.By methods such as image gray processing, binaryzation, filtering, expansions image is carried out preliminary treatment, utilize the threshold value quantizing standard to discern the state that blower fan rotates or stops as basis for estimation, and recognition result sent back Surveillance center, supply the usefulness of accident analysis afterwards, recognition accuracy reaches more than 98%.For the electric power system fault monitoring provides a kind of new means with accident analysis, to improve the level of IT application of electric power system.
Claims (1)
1. the image processing and the recognition methods of a power transformer fan operation status real time monitor is characterized in that: at first utilize digital video monitor system to obtain the original color image of power transformer fan operation state; Then this original image is carried out image gray processing and image binaryzation processing, to extract power transformer blower fan target image to be identified; Utilize the method for image expansion that the image after handling through image binaryzation is handled again, to eliminate of the interference of power transformer blower fan catch net to image; Then in the computed image in the flabellum circle ring area of living in black pixel point account for the ratio value of all pixels in the whole described circle ring area, this ratio value is carried out the cube computing, when operation values greater than 0.68 the time, determine that the power transformer blower fan is a starting state; When operation values less than 0.68 the time, determine that the power transformer blower fan is a halted state.
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| CNB2006100807317A CN100469138C (en) | 2006-05-15 | 2006-05-15 | Power transformer draught fan state recognizing method based on video monitoring and image recognition |
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| CN100469138C true CN100469138C (en) | 2009-03-11 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP5101465B2 (en) | 2008-11-25 | 2012-12-19 | 三菱重工業株式会社 | Equipment defect management method |
| CN102353355A (en) * | 2011-06-14 | 2012-02-15 | 西安工程大学 | Method for measuring power transmission line pole and tower inclination based on video differences |
| CN102797727B (en) * | 2012-08-17 | 2015-11-11 | 国电联合动力技术有限公司 | A kind of Wind turbines oil leakage of hydraulic system detecting method based on CCD and device |
| CN106156689B (en) * | 2015-03-23 | 2020-02-21 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN104902223A (en) * | 2015-04-17 | 2015-09-09 | 国家电网公司 | Fault monitoring system of power line |
| CN106514657B (en) * | 2016-12-30 | 2019-11-05 | 杭州电子科技大学 | A kind of sealing ring crawl and laying method based on robot motion planning |
| CN108038989A (en) * | 2017-12-04 | 2018-05-15 | 杭州纳戒科技有限公司 | Shared logistics box control method, apparatus and system |
| CN108734079B (en) * | 2018-02-07 | 2019-05-03 | 上海利莫网络科技有限公司 | Image big data instant analysis method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4837708A (en) * | 1987-07-01 | 1989-06-06 | Maraven, S.A. | Process and apparatus for determining flow rate of a flow medium in a flow line |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4837708A (en) * | 1987-07-01 | 1989-06-06 | Maraven, S.A. | Process and apparatus for determining flow rate of a flow medium in a flow line |
Non-Patent Citations (2)
| Title |
|---|
| 远程数字视频监控与图像识别技术在变电站中的应用. 王东方.华北电力大学工程硕士专业学位论文. |
| 远程数字视频监控与图像识别技术在变电站中的应用. 王东方.华北电力大学工程硕士专业学位论文. * |
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