CN102609696A - Image recognition-based method for detecting faults of lighting equipment - Google Patents
Image recognition-based method for detecting faults of lighting equipment Download PDFInfo
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- CN102609696A CN102609696A CN2012100754917A CN201210075491A CN102609696A CN 102609696 A CN102609696 A CN 102609696A CN 2012100754917 A CN2012100754917 A CN 2012100754917A CN 201210075491 A CN201210075491 A CN 201210075491A CN 102609696 A CN102609696 A CN 102609696A
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- 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
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- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
- Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection
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Abstract
The invention discloses an image recognition-based method for detecting faults of lighting equipment, which mainly comprises the steps of mounting a camera, calibrating the position of the lighting equipment, real-timely imaging by the camera, decoloring, binarization processing and comparing an image to be inspected with a standard image. The method uses the camera which is assorted by computer software to monitor the faults of the lighting equipment, so the expenses of the manpower resource are effectively reduced, the fault detection and discovery efficiencies are improved, and the method can be used for the lighting of large exhibition halls, public occasions and places which are not suitable for practical observation.
Description
Technical field
The present invention relates to a kind of light fixture fault detection method, specifically is a kind of light fixture fault detection method based on image recognition.
Background technology
At large-scale public places such as all kinds of exhibition centers, museums, the fault detect of light fixture is all judged for visual inspection through the people.The keeper is through making an inspection tour the way in whole place in the shop; Observe the working condition of light fixture one by one; Whether light fixture exists fault, is judged, is discerned by naked eyes fully, if museum reaches certain scale; Because on-the-spot place is excessive, then the keeper makes an inspection tour the also increase thereupon of time of club of whole museum cost.
Traditional light fixture fault detect is based on the fault detect of electric signal.The fault test set that for example detects, the equipment that carries out fault detect based on the magnitude of voltage situation of change based on the electrorheological law.The equipment price that carries out fault detect based on electric signal is higher, and this kind equipment itself also is electrified equipment, is difficult to when fault test set self goes wrong find, changes the checkout equipment relative complex.
Summary of the invention
The present invention seeks to: for overcoming the above problems; A kind of light fixture fault detection method based on image recognition is proposed; The present invention uses camera coupled computer software to accomplish the fault monitoring of illumination equipment; Effectively reduced the spending of human resources, and improved the efficient of fault detect and discovery, can use in the place of large-scale museum, public arena illumination and not suitable actual observation.
Technical scheme of the present invention is: a kind of light fixture fault detection method based on image recognition may further comprise the steps: step 1, to the field of illumination that will keep watch on camera equipment is installed;
Step 2, all light fixture all just often, all light fixture are opened and are in illumination condition are taken a reference base picture with camera in guaranteeing monitor area, and calibrate that there is the some zone of light fixture in all on this reference base picture;
Step 3, its monitor area is carried out the timing capture, and all light fixture in the monitor area are opened all when guaranteeing capture through the software control camera;
Step 4, utilize software, be translated into the gray scale picture the processing of discoloring of step 3 picture shot;
Step 5, the gray scale picture after discoloring is carried out binary conversion treatment, obtaining one, only to have color value be that RGB (0,0,0) and color value are the picture to be checked of RGB (255,255,255);
Step 6, utilize software that picture to be checked and the reference base picture that step 4 obtains compared; If some zone is demarcated to there being light fixture on reference base picture, and picture to be checked in the regional color value of respective point be RGB (0,0; 0); There is fault in the light fixture of then judging this some zone, and software sends warning message, notifies managerial personnel to check whether this area illumination device is normal.
In said step 2, the regional scaling method of point that has light fixture to exist on the reference base picture is:
1) utilizes software to the reference base picture processing of discoloring, be translated into the gray scale picture;
2) the gray scale picture after discoloring is carried out binary conversion treatment, obtaining one, only to have color value be that RGB (0,0,0) and color value are the reference base picture of RGB (255,255,255);
3) be that the some region labeling of RGB (255,255,255) is the some zone that has light fixture to exist with color value on the reference base picture.
Advantage of the present invention is: the development of computer vision technique, the lighting fault detection method that makes this paper propose is accomplished.The present invention uses camera coupled computer software to accomplish the fault monitoring of illumination equipment; Replace naked eyes to come surveillance illumination equipment with camera; Can effectively alleviate the low and personnel of the light fixture fault detect efficient excessive problem of paying wages; But and can realize full-time supervision, warning through the characteristics of camera full-time employment.Characteristics such as traditional relatively light fixture detection method price is higher, construction complicacy; The present invention utilizes simple common device; Realization has effectively reduced the spending of human resources to the supervision of the light fixture in large-scale place, and has improved the efficient of fault detect and discovery.
Description of drawings
Below in conjunction with accompanying drawing and embodiment the present invention is further described:
Fig. 1 is the process flow diagram of the embodiment of the invention;
Fig. 2 is the matrix that discolors during the present invention implements.
Embodiment
Embodiment: with reference to shown in Figure 1, the light fixture fault detection method based on image recognition of present embodiment may further comprise the steps:
Step 1, to the field of illumination that will keep watch on camera equipment is installed.
Should note: after the installation of camera equipment, it is not rotated or the shift position, the situation that can not correctly discern the light fixture fault in the monitor area possibly caused in random rotation camera angle or shift position again.
Step 2, in guaranteeing monitor area all light fixture all just often (being non-fault), all light fixture are opened and are in illumination condition; Take a reference base picture with camera, and calibrate that there is the some zone of light fixture in all on this reference base picture;
The scaling method in illumination equipment point zone is following in the present embodiment:
1) utilizes software to the reference base picture processing of discoloring, be translated into the gray scale picture;
2) the gray scale picture after discoloring is carried out binary conversion treatment, obtaining one, only to have color value be that RGB (0,0,0) and color value are the reference base picture of RGB (255,255,255);
3) be that the some region labeling of RGB (255,255,255) is the some zone that has light fixture to exist with color value on the reference base picture.
Step 3, its monitor area is carried out the timing capture through the software control camera; And all light fixture in the monitor area are all opened (said " all light fixture are all opened " here when guaranteeing the camera capture; Only refer to switch open, do not guarantee that all light fixture all are in the normal illumination state) all light fixture.Need the interval time of adjacent twice capture to decide according to on-site actual situations.
Step 4, utilize software, be translated into the gray scale picture the processing of discoloring of camera picture shot in the step 3;
The operation of discoloring of image is according to the multiplication of matrices rule; Let view data can in very fast computing time, accomplish discoloring of picture; Here used the matrix that discolors (like Fig. 2) of a 5X5 to accomplish the operation of discoloring to picture; Through the image of being obtained being carried out and the matrix multiple that discolors, the result is exactly the gray-scale map after discoloring.
Step 5, utilize software that the gray scale picture after discoloring is carried out binary conversion treatment, obtaining one, only to have color value be that RGB (0,0,0) and color value are RGB (255; 255,255) picture to be checked, wherein: color value is RGB (255,255; 255) some zone is the zone that has light fixture to exist, and color value is that the some zone of RGB (0,0,0) generally is the zone (so-called " generally being " that does not have light fixture to exist; Be meant: because possibly there is fault in some regional light fixture, for the zone that these light fixture break down, the color value on photo to be checked also is RGB (0; 0,0), hereinafter has explanation more specifically to this).
Step 6, utilize software that picture to be checked and the reference base picture that step 4 obtains compared.
Because reference base picture all is in (non-fault) shooting under the normal condition at all light fixture, so all exist the some zone of light fixture to fix at this reference base picture subscript.Under normal circumstances (when promptly not having light fixture to break down), if certain some zone has light fixture to exist, the color value in this some zone of picture to be checked is RGB (255,255,255) so; But, if certain is a bit demarcated to there being light fixture in zone on reference base picture, and picture to be checked in the regional color value of respective point be RGB (0; 0,0),---promptly this some zone itself has light fixture to exist; And the color value in respective point zone is RGB (0,0,0) in the picture to be checked that step 4 obtains; There is fault in the light fixture of then judging this some zone, and software sends warning message, notifies managerial personnel to check whether this area illumination device is normal.
After managerial personnel's field review,, then need artificial maintenance if it is unusual to find that this area illumination device exists really.If should not have the light fixture existence unusually in the zone; The software wrong report is described; At this moment should find out the wrong report reason, most of wrong report situation is to be caused by camera rotation or shift position, and some wrong report is that the light intensity decline that light fixture sends causes.For first kind of wrong report situation, should reinforce camera position, it can not arbitrarily be moved; For second kind of wrong report situation, can solve through adjustment binaryzation operational threshold, to reduce the generation of wrong report situation.
In order to let people can understand content of the present invention more intuitively and to implement according to this, the applicant is existing open as follows with its once concrete experiment of using method of the present invention to do:
A) experimental situation
The VS2010 coding is used in this experiment, and whether the light fixture that cooperates the logical camera of a Daepori to keep watch in the appointed area exists fault.The light fixture of appointment is indoor daylight lamp.
B) experiment content
At first open the camera capture, demarcate the position of all light fixture, this experimental calibration goes out six daylight lamp equipment, and after demarcation was accomplished, program can be pointed out the number and the position in this calibration point zone.
After demarcating completion, the tentation data of archive needed has been accomplished archive operations.At this moment can begin monitoring.In the monitor procedure, if there have the not high or brightness of light to change to be excessive, program can be pointed out should zone bulb existing problems.
Calculation procedure is to discolor earlier to operate to be converted into gray-scale map in the program; And then carry out binaryzation operation and be converted into that only to have rgb value be that the point of (255,255,255) and (0,0,0) is regional.
After picture was converted into gray-scale map, there be not colouring information in all pixels in the picture, have only the half-tone information value., program carries out gradation conversion before being converted into binary image to image; Be in order to improve the accuracy of fault detect,, directly be converted into binary image to the original image of obtaining if without gradation conversion; On the picture after converting, can increase the probability of occurrence of noise data.In order to address this problem, we have proposed middle step of converting: be converted into gray level image earlier, be converted into binary image by gray level image again.
In the picture to be checked after the binaryzation operation transforms, all positions of light fixture very clearly are presented on the picture, and other zones that do not have light fixture all are black (saying accurately, is the zone that does not have lighting source).Real time picture (picture to be checked) after so just can using the predetermined file picture (reference base picture) of software contrast and handling contrasts; Comparing result according to the zone; Just can obtain the failure message of light fixture, thereby report to the police according to the failure message that obtains.
C) experimental result
If one of them lamp has not worked, system can point out corresponding location device to break down.So just can accomplish the supervision of the appointed area being specified light fixture, after equipment goes wrong, can in time feed back.
Claims (2)
1. light fixture fault detection method based on image recognition is characterized in that this method may further comprise the steps:
Step 1, to the field of illumination that will keep watch on camera equipment is installed;
Step 2, all light fixture all just often, all light fixture are opened and are in illumination condition are taken a reference base picture with camera in guaranteeing monitor area, and calibrate that there is the some zone of light fixture in all on this reference base picture;
Step 3, its monitor area is carried out the timing capture, and all light fixture in the monitor area are opened all when guaranteeing capture through the software control camera;
Step 4, utilize software, be translated into the gray scale picture the processing of discoloring of step 3 picture shot;
Step 5, the gray scale picture after discoloring is carried out binary conversion treatment, obtaining one, only to have color value be that RGB (0,0,0) and color value are the picture to be checked of RGB (255,255,255);
Step 6, utilize software that picture to be checked and the reference base picture that step 4 obtains compared; If some zone is demarcated to there being light fixture on reference base picture, and picture to be checked in the regional color value of respective point be RGB (0,0; 0); There is fault in the light fixture of then judging this some zone, and software sends warning message, notifies managerial personnel to check whether this area illumination device is normal.
2. the light fixture fault detection method based on image recognition according to claim 1 is characterized in that in said step 2, and the regional scaling method of point that has light fixture to exist on the reference base picture is:
1) utilizes software to the reference base picture processing of discoloring, be translated into the gray scale picture;
2) the gray scale picture after discoloring is carried out binary conversion treatment, obtaining one, only to have color value be that RGB (0,0,0) and color value are the reference base picture of RGB (255,255,255);
3) be that the some region labeling of RGB (255,255,255) is the some zone that has light fixture to exist with color value on the reference base picture.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102797727A (en) * | 2012-08-17 | 2012-11-28 | 国电联合动力技术有限公司 | Method and device for detecting oil leakage of hydraulic system of wind turbine based on CCD (Charge Coupled Device) |
| CN105115973A (en) * | 2015-08-28 | 2015-12-02 | 武汉邮电科学研究院 | Equipment monitoring system and method based on visible light communication |
| CN106376163A (en) * | 2016-08-25 | 2017-02-01 | 福建福光股份有限公司 | Safety detection system and method for center-line light in airport |
| CN107688341A (en) * | 2016-08-05 | 2018-02-13 | 深圳市朗驰欣创科技股份有限公司 | The control method and control system of electric power tunnel lamp automatic detecting |
| CN108871001A (en) * | 2017-05-15 | 2018-11-23 | 广东科达洁能股份有限公司 | A kind of kiln of view-based access control model sensor breaks stick detection system and method |
| CN111913873A (en) * | 2020-06-17 | 2020-11-10 | 浙江数链科技有限公司 | Picture verification method, device and system and computer readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050162516A1 (en) * | 2003-09-25 | 2005-07-28 | Siemens Schwiez Ag | Method and analysis tool for checking the functional suitability of video monitoring devices, as well as a measurement device for carrying out the method |
| CN1674048A (en) * | 2004-03-22 | 2005-09-28 | 富士施乐株式会社 | Image processing apparatus, image processing method and program product therefor |
| CN102147859A (en) * | 2011-04-06 | 2011-08-10 | 浙江浙大华是科技有限公司 | Ship monitoring method |
-
2012
- 2012-03-21 CN CN2012100754917A patent/CN102609696A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050162516A1 (en) * | 2003-09-25 | 2005-07-28 | Siemens Schwiez Ag | Method and analysis tool for checking the functional suitability of video monitoring devices, as well as a measurement device for carrying out the method |
| CN1674048A (en) * | 2004-03-22 | 2005-09-28 | 富士施乐株式会社 | Image processing apparatus, image processing method and program product therefor |
| CN102147859A (en) * | 2011-04-06 | 2011-08-10 | 浙江浙大华是科技有限公司 | Ship monitoring method |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102797727A (en) * | 2012-08-17 | 2012-11-28 | 国电联合动力技术有限公司 | Method and device for detecting oil leakage of hydraulic system of wind turbine based on CCD (Charge Coupled Device) |
| 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 |
| CN105115973A (en) * | 2015-08-28 | 2015-12-02 | 武汉邮电科学研究院 | Equipment monitoring system and method based on visible light communication |
| CN107688341A (en) * | 2016-08-05 | 2018-02-13 | 深圳市朗驰欣创科技股份有限公司 | The control method and control system of electric power tunnel lamp automatic detecting |
| CN106376163A (en) * | 2016-08-25 | 2017-02-01 | 福建福光股份有限公司 | Safety detection system and method for center-line light in airport |
| CN106376163B (en) * | 2016-08-25 | 2018-08-21 | 福建福光股份有限公司 | The safety detecting system and method for airport center line lamps and lanterns |
| CN108871001A (en) * | 2017-05-15 | 2018-11-23 | 广东科达洁能股份有限公司 | A kind of kiln of view-based access control model sensor breaks stick detection system and method |
| CN108871001B (en) * | 2017-05-15 | 2024-04-19 | 广东科达洁能股份有限公司 | Kiln broken rod detection system and method based on visual sensor |
| CN111913873A (en) * | 2020-06-17 | 2020-11-10 | 浙江数链科技有限公司 | Picture verification method, device and system and computer readable storage medium |
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Application publication date: 20120725 |