CN204405556U - A kind of glue into concrete beam cracks pick-up unit based on Digital Image Processing - Google Patents
A kind of glue into concrete beam cracks pick-up unit based on Digital Image Processing Download PDFInfo
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- CN204405556U CN204405556U CN201420822397.8U CN201420822397U CN204405556U CN 204405556 U CN204405556 U CN 204405556U CN 201420822397 U CN201420822397 U CN 201420822397U CN 204405556 U CN204405556 U CN 204405556U
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Abstract
The utility model discloses a kind of glue into concrete beam cracks pick-up unit based on Digital Image Processing, it is characterized in that: comprise supply module, range finder module, image collection module, image processing module, FRACTURE CHARACTERISTICS extraction module and crack information storage module, image collection module is connected with image processing module respectively with range finder module, and image processing module, FRACTURE CHARACTERISTICS extraction module, crack information storage module are connected with supply module order.This equipment safety is reliable, reduces testing cost, effectively can get rid of the subjective disturbing factor of people, and efficiently solve image discontinuous, leak the existence of clapping or repeating to take phenomenon and detect the problem that accuracy is not high, detection efficiency is low.
Description
Technical field
The utility model relates to bridge machinery field, is specifically related to a kind of glue into concrete beam cracks pick-up unit based on Digital Image Processing.
Background technology
Bridge is the important component part in traffic system.There is aging phenomenon in a lot of bridge of China, in recent years by the impact of overload and oversize situation, some problems have also appearred in the bridge much built up soon, and these bridges also exist some potential safety hazards, therefore need the detection of being correlated with to bridge.In testing result, the crack situation at bridge bottom surface and bridge pier place is one of important indicator showing bridge quality condition.
For the crack of concrete bridge soffit, main detection method is manual detection both at home and abroad at present.The implementation of manual detection method is mainly by the crack at the bottom of telescope distant surveillance bridge, or by building platform at the bottom of bridge, closely detect by an unaided eye the crack of bridge bottom surface, the numerical value such as length, width in record crack, and judged the growing state in crack by repeated detection.At the bottom of common bridge, platform has framing scaffold and bridge inspection vehicle.When being difficult to scaffold erecting, what mainly adopt is bridge inspection vehicle.Testing staff walks on the truss arm of bridge inspection vehicle, detects bridge bottom crack.
For the detection of crack data, the mainly hand-held New Instrument for Crack Width existed in the market.Hand-held New Instrument for Crack Width is popped one's head in by liquid crystal display main frame, micro-amplification and is formed, first after needing human eye to lock crack target during measurement, instrument could be utilized will to pop one's head near tested crack, exaggerated crack pattern picture is seen thus in LCDs, fine setting probe makes crack substantially vertical with electronics graduated scale, and shared by crack, how many interpretations of scale mark go out fracture width.
Research shows, existing Bridge Crack detection mode mainly exists following defect or deficiency:
(1) data reliability is low: manual observation, with a lot of subjectivities, detects data not accurate enough.
(2) efficiency is low: manual detection speed is slow, and elapsed time is long.
(3) huge labour is spent: because observed pattern is inconvenient, artificial observation needs to spend a large amount of labour, and sometimes also needs restricting traffic, makes troubles to other haulage vehicles.
(4) work is dangerous: be generally river or other low lying areas below bridge, uses support to belong to work high above the ground, has certain danger.
For the defect of manual detection method, propose several solution both at home and abroad.Such as patent CN201126427Y proposes to use aeromodelling airplane to carry camera and detects crack at the bottom of bridge.This method is difficult to the quality ensureing to collect image, and the crack precision that can detect is not high yet.The bridge that patent CN103253314A adopts negative-pressure adsorption climb type robot to be adsorbed on different operating mode on the surface fracture detects.It is wide that above method also exists the scope of application, and cost is high, and image is discontinuous, leakage is clapped or repeat the shortcomings such as shooting phenomenon existence.
Utility model content
The defect existed for above-mentioned prior art or deficiency, the utility model provides a kind of glue into concrete beam cracks pick-up unit based on Digital Image Processing, this equipment safety is reliable, reduce testing cost, effectively can get rid of the subjective disturbing factor of people, and efficiently solve image discontinuous, leak the existence of clapping or repeating to take phenomenon and detect that accuracy is not high, problem that detection efficiency is low.
The technical scheme realizing the utility model object is:
A kind of glue into concrete beam cracks pick-up unit based on Digital Image Processing, comprise supply module, range finder module, image collection module, image processing module, FRACTURE CHARACTERISTICS extraction module and crack information storage module, image collection module is connected with image processing module respectively with range finder module, and image processing module, FRACTURE CHARACTERISTICS extraction module, crack information storage module are connected with supply module order.Wherein:
Supply module, for modules stable output power supply in device;
Range finder module is stadimeter, for obtaining measurement point to the distance containing crannied bridge surface;
The built-in projection module of image collection module, camera module, amplification look in the distance module, indicating module and light strengthen module;
Image processing module, the process that this module carries out crack image procossing comprises filtering---weaken the impact of crack picture noise; Iamge Segmentation---crack information is separated from crack pattern picture; Morphological image operates---and further image is processed, get rid of non-crack information;
FRACTURE CHARACTERISTICS extraction module, for obtaining the geometric properties in crack from segmentation image, as the length in crack, width and area;
Crack information storage module, stores the crack information after gathering and analyzing, facilitates subsequent analysis and stay shelves.
Wherein, the critical piece of projector module is a projector be connected with computing machine, is controlled, projected the grid image of a checkerboard, carry out Region dividing with this to bottom bridge by projector to bridge bottom surface by computing machine.
Camera module forms primarily of slr camera and CCD digital camera, and slr camera is mainly used in the high-definition picture obtaining Bridge Crack position, thus is next step image procossing preparation material; The region that CCD digital camera calibrates for catching indicating module, then passes to computing machine by image, for next step control is prepared.
Amplify module of looking in the distance to form primarily of the astronomical telescope camera lens that can control to rotate automatically, after being connected with camera by adapter ring, higher enlargement factor can be obtained, thus realize the demand of wide-long shot.
Indicating module is a high-light laser being arranged on astronomical telescope, it and pick-up lens synchronous axial system, thus marks the region that is taken of bridge bottom surface projection grid.
Light strengthens the flashlamp that module is and camera shutter synchro control, can strengthen the luminosity of subject surface when insufficient light, improves shooting effect, meets request for utilization in particular cases.
Preferably, laser range finder selects LEICA DISTO D2, and measurement range is 0.05m-100m, can obtain measurement point easily to the distance containing crannied bridge surface.
Preferably, slr camera selects Nikon slr camera.
Preferably, the Meade astronomical telescope camera lens selecting can automatically control to rotate is amplified in module of looking in the distance, the nearly 2m of focal length.
Preferably, described light strengthens module and adopts powerful light fixture, and meanwhile, light source also will have the characteristic of high-frequency stabilization and low-power consumption, and the utility model selects LED light source as light fixture.
Described image processing module and FRACTURE CHARACTERISTICS extraction module are provided with many algorithms, and realizing the extraction of pre-service to gained image and eigenwert, is the calculating maincenter of whole device.
Described crack information storage module is on the basis analyzing gained information, forms preliminary conclusion, analyzes and store degree of impairment.
Therefore, the utility model is used to be embodied in the effect that concrete bridge bottom crack detects:
(1) easy to detect.Only need manual control detection system to the position of required detection, then determined the crack that will detect by computing machine, just can obtain crack data, without the need to manually closely detecting near crack.
(2) testing result is directly perceived, reliable, the error produced when avoiding manual detection.The utility model utilizes a set of detection system that can carry out clear observation to pontic surface appearance and accurately measure, and by Computer real-time processing, can obtain the accurate results being observed fracture length, width and area.
(3) after utilizing projector to carry out Region dividing to bridge bottom surface, by computing machine to the brightness of guiding the identification of laser to reduce collecting image region, collecting image region and image-region to be collected is distinguished with this, discontinuous, the leakage that avoid shooting image are clapped or are repeated to take phenomenon, improve the accuracy of detection.
(4) impact of crack on bridge safty and permanance can be assessed by following the tracks of quantitative observation, can also measure the amount of deflection of bridge and strain etc. when bridge carries out loading test.
(5) with low cost.The price of the bridge inspection vehicle that present stage uses is about 4,000,000, and maintenance cost is high, and using inspection vehicle to carry out detection to a bridge block needs nearly 100,000 yuan of cost.Comparatively speaking, the utility model cost is low, and same Detection results is good, is convenient to promote the use of.
Accompanying drawing explanation
Fig. 1 is structural representation of the present utility model.
Fig. 2 is the block diagram of the utility model crack detection system.
Fig. 3 is the process flow diagram of the utility model Crack Detection algorithm.
Fig. 4 is the checkerboard grid image that projector projects to bridge bottom surface.
Fig. 5 is different windows medium filtering effect contrast figure.
Fig. 6 is skeletonization method principle schematic.
In figure: the grid image of the checkerboard that 1.LED light source 2. slr camera 3. laser instrument 4. projector 5.CCD digital camera 6. laser range finder 7. computing machine 8. supply module 9. projector projects goes out.
Embodiment
Below in conjunction with accompanying drawing, the utility model is described in detail.
As shown in Figure 1, the utility model glue into concrete beam cracks pick-up unit is made up of supply module 8, the computing machine 7 be connected with supply module 8 and the range finder module 6 be connected with computing machine 7, image collection module, the connected image processing module FRACTURE CHARACTERISTICS extraction module of order and crack information storage module is built-in with in computing machine 7
In this device course of work, the equipment that supply module 8 uses to each module of system is powered, the normal work of other modules in guarantee system.
Range finder module 6 is LEICA DISTO D2 laser range finder, and measurement range is 0.05m-100m, can obtain measurement point easily to the distance u containing crannied bridge surface.
Image collection module, comprises LED light source 1, slr camera 2, laser instrument 3, projector 4, CCD digital camera 5, and the concrete steps that this module carries out image acquisition are as follows:
1) as shown in Figure 4, controlled by computing machine 7, projected the grid image 9 of a checkerboard by projector 4 to bridge bottom surface, carry out Region dividing with this to bottom bridge.
Region after dividing is numbered, so that image record and management, is designated as successively from left to right [1,1], [1,2] ..., be designated as successively from top to bottom [1,1], [2,1] ..., the like.
2) by Nikon slr camera 2, take successively to grid spaces, bridge bottom surface, shooting order is from top to bottom, from left to right.
The luminosity of subject surface can be strengthened when insufficient light by LED light source 1, improve shooting effect, meet request for utilization in particular cases.LED light source 1 has the characteristic of high-frequency stabilization and low-power consumption, and controls with slr camera 2 shutter synchronization, and when shutter is pressed, slr camera 2 sends signal to computing machine 7, opens LED light source and takes bridge floor, closes LED light source 1 after postponing 1s.
Meanwhile, indicating module is a high-light laser 3 being arranged on slr camera 2 astronomical telescope, it and pick-up lens synchronous axial system, thus marks the region that is taken of bridge bottom surface projection grid.
3) while taking pictures in use slr camera 2 pairs of net regions, the laser instrument 3 be arranged on astronomical telescope just can mark the net region that slr camera 2 is being taken, such as, in Fig. 4 [5, 2], CCD digital camera 5 also can be taken bridge bottom surface simultaneously, and image is passed in computing machine 7, through the identification of computing machine 7 pairs of laser instrument 3 laser labellings, judge the grid spaces taking image, then grid of being correlated with by slide pictures marks, by projector 4, picture is projected bridge bottom surface again, shooting area and region to be captured can be told thus intuitively, avoid the discontinuous of shooting image, leak and clap or repeat to take phenomenon, improve the accuracy of detection.
Because the width of Bridge Crack is general all smaller, the width in most of crack is likely only within 1mm, and this just makes the number of pixels of occupying of every crack in certain width collected to lack.And only having when the resolution of digital camera is higher, the width represented by each unit picture element will be slightly smaller.Therefore, only have the accuracy adopting the digital camera of high multiple pixel can promote fracture identification well, in conjunction with existing digital technology, the utility model adopts Nikon slr camera, and installs the Meade astronomical telescope camera lens that can automatically control to rotate.
Image processing module, comprises filtering---weaken the impact of crack picture noise; Iamge Segmentation---crack information is separated from crack pattern picture; Morphological image operates---and further image is processed, get rid of non-crack information.
Filtering process, bridge imaging surface can be subject to a lot of noise under normal circumstances, and its reason has: the noise of the gradual change that (1) imaging system causes or illumination condition uneven; (2) irregularly shaped object, as the impact of greasy dirt or other non-concrete materials; (3) random noise that causes of the own particle interval of concrete.The interference of noise reduces the quality of image to a great extent, brings a lot of difficulty to the detection and Identification of image, so before to Image Segmentation Using, needs to do smoothing processing to weaken the impact of noise.
In the present embodiment, adopt median filter method fracture image to carry out filtering process, medium filtering can retain image border preferably, and image outline is more clear, can obtain reasonable smooth effect.
The principle of medium filtering is that window size is 3x3,5x5,7x7 with a window ..., image slides, the gray-scale value of pixel in window by the order arrangement risen or fall, gets the gray-scale value that the is arranged in middle gray-scale value as window center place pixel.Medium filtering is a kind of typical nonlinear filter, and the window usually selected has linear, square, cruciform and circle etc.
As shown in Figure 5, find through the contrast of different size window, window is less, and image detail protection is better, and noise removal capability is poorer.On the contrary, window is larger, and noise removal capability is stronger, but details protective capability is poorer, and through comparing, the cruciform window choosing 5x5 in the present embodiment carries out medium filtering process to image.
Iamge Segmentation, general pattern is made up of background and target object, and because they are different to the reflection potential of light, under normal circumstances, crack comparatively background is dark, therefore can select a gray threshold that object area is separated.In the present embodiment, Global thresholding Kittler binarization method is selected to carry out binary conversion treatment to image.
If f (x, y) is original-gray image, the process formula of Kittler binaryzation is:
T=
In formula, e (x, y)=max{|e
x|, | e
y| be the maximal value of gradient, and in e (x, y), e
x=f (x-1, y)-f (x+1, y), e
y=f (x, y-1)-f (x, y+1) represents the gradient in horizontal direction and the gradient in vertical direction respectively.
Because crack pattern picture is subject to the impact of noise, image is after Kittler binaryzation, and binary image often has following two kinds of situations:
(1) beyond crack area, there will be a lot of isolated point, isolated small size region;
(2) on crack area border, often there is burr, tiny projection, in the middle of crack area, often have tiny disconnection in the middle of crack area, often have cavity to exist.
For the existence of above two kinds of situations, propose in the present embodiment to utilize morphological operation fracture image to process, reach stress release treatment point, the object of noise region, reparation crack area.
Morphological image operates, and need to choose suitable structural element, structural element can not be too little, the too little object not reaching morphological operation, can not be too large, and too conference causes the crack after operating to occur disconnecting or changing fracture morphology largely.The selection principle of structural element is as follows:
(1) geometrically, structural element must be simpler than former figure, and bounded.
(2) structural element finally has convexity, as circular, cruciform and square etc.
In fact, after mathematical morphology operation, the isolated area larger for those still exists, and removes these isolated areas iff by morphological operation, above can change the actual form of crack area so largely.Therefore, the threshold value T rule of thumb setting isolated area size (area pixel number) after morphological operation is proposed in the present embodiment
1.According to crack area, generally there is the long feature setting regions length breadth ratio threshold value T larger with wide ratio (length breadth ratio) again
2.If region area is less than T in the crack pattern picture after binaryzation
1or length breadth ratio is less than T
2, then think that these regions are noise region, then remove such region.
Crack breakpoint joint, crack pattern picture after filtering, after Iamge Segmentation and morphological operation, leave few connected region, we think that these are all the ingredients in crack or crack.Crack pattern picture inevitably makes the crack originally connected together disconnect when image segmentation operations, crack disconnects the calculating of fracture length, width and area after impact.
Method of attachment for crack has a lot, and algorithm selected in the present embodiment is as follows, for transverse crack:
(1) the initial pixel point in crack is first found, method is if this pixel in 5-10 pixel coverage or in vertical direction finds bright spot (bright spot is crack area) in 2-4 pixel coverage in the horizontal direction, then think that this point is the initial pixel point in horizontal direction crack, otherwise just think that this point is a part for noise region or noise region.
(2), after finding initial pixel point, define the right side, three directions of this point, be upper and lowerly respectively the one two three direction, and priority is followed successively by from big to small.According to depth-first search strategy, search rule is along first direction search until do not have bright spot in this direction from initial pixel point, then continuation second direction, the 3rd direction, by that analogy.
(3) accessed according to last point, looks for the crack area pixel nearest with this point in specific hunting zone, connects this two points.Then above step is repeated for entire image.
FRACTURE CHARACTERISTICS extraction module, this module is intended to extract the length in crack, width and area three kinds of geometric properties, the very large meaning of information in these three kinds of cracks describes the damaged condition in crack.
Skeletonizing asks fracture length, and skeletonizing refers to the process crack with one fixed width being become single pixel.Skeletonizing can reduce the redundant information in image, describes the direction in crack more compactly, form, the information such as length.The skeleton SK(M of target M) be made up of the center of circle of maximal inscribed disks all in M, as shown in Figure 6.
From the definition of skeletonizing, can see that the slit image prime number after skeletonizing is exactly the length in crack, directly ask for slit image prime number after skeleton, if length is
, can obtain the area in crack according to the pixel count in the front crack of skeletonizing, if area is s, then the mean breadth in crack is
Telemetry calculates fracture width, so-called telemetry be exactly directly utilize laser range finder to obtain object distance u(u for camera lens photocentre is to the distance of body surface) calculate the method for fracture width.
For selected camera, known camera imaging area is axb, and the resolution of captured image is s
1xs
2.If known focal distance f, be a certain position shooting of u in object distance, the pixel count recording the width in crack shared is in the picture m, then the developed width L that can obtain crack is:
If do not forehand during camera shooting, but there is pitching and skew relative to bridge surface, then need to revise conversion formula, obtaining revised fracture width L ' is:
=
Utilize chain code to ask for flaw area, chain code describes and adopts the coordinate of curve starting point and slope (direction) to represent curve.The basic thought of image object boundary chain code representation is: along border in turn for borderline each coordinate points find out represent this line segment with 4 directional chain-code or 8 directional chain-code time corresponding direction encoding value, marked out.Like this, the object boundary in image can be represented by string number.
Described by region chain code, the area in region is in fact the discretize of the curve surface integral to x-axis, and area S is
Wherein, y
i=y
i-1+ p
i2, y
0the ordinate of initial point, p
i0, p
i2that i-th chain code is in k=0(level respectively) vertical with k=2() component in direction (having positive and negative point according to the direction on border),
it is the vertical range of i-th chain code.
Claims (7)
1. the glue into concrete beam cracks pick-up unit based on Digital Image Processing, it is characterized in that: comprise supply module, range finder module, image collection module, image processing module, FRACTURE CHARACTERISTICS extraction module and crack information storage module, image collection module is connected with image processing module respectively with range finder module, and image processing module, FRACTURE CHARACTERISTICS extraction module, crack information storage module are connected with supply module order; Wherein:
Supply module, for modules stable output power supply in device;
Range finder module is stadimeter, for obtaining measurement point to the distance containing crannied bridge surface;
The built-in projection module of image collection module, camera module, amplification look in the distance module, indicating module and light strengthen module;
Image processing module, the process that this module carries out crack image procossing comprises filtering---weaken the impact of crack picture noise; Iamge Segmentation---crack information is separated from crack pattern picture; Morphological image operates---and further image is processed, get rid of non-crack information;
FRACTURE CHARACTERISTICS extraction module, for obtaining the geometric properties in crack from segmentation image, as the length in crack, width and area;
Crack information storage module, stores the crack information after gathering and analyzing, facilitates subsequent analysis and stay shelves.
2. device according to claim 1, it is characterized in that: the critical piece of described projection module is a projector be connected with computing machine, controlled by computing machine, projected the grid image of a checkerboard by projector to bridge bottom surface, carry out Region dividing with this to bottom bridge.
3. device according to claim 1, is characterized in that: described camera module forms primarily of slr camera and CCD digital camera, and slr camera is mainly used in the high-definition picture obtaining Bridge Crack position, thus is next step image procossing preparation material; The region that CCD digital camera calibrates for catching indicating module, then passes to computing machine by image, for next step control is prepared.
4. device according to claim 1, it is characterized in that: amplify module of looking in the distance and form primarily of the astronomical telescope camera lens that can control to rotate automatically, after being connected with camera by adapter ring, higher enlargement factor can be obtained, thus realize the demand of wide-long shot.
5. device according to claim 1, is characterized in that: indicating module is a high-light laser being arranged on astronomical telescope, it and pick-up lens synchronous axial system, thus marks the region that is taken of bridge bottom surface projection grid.
6. device according to claim 1, it is characterized in that: light strengthens the flashlamp that module is and camera shutter synchro control, the luminosity of subject surface can be strengthened when insufficient light, improve shooting effect, meet request for utilization in particular cases.
7. device according to claim 1, is characterized in that: described range finder module is laser range finder, and measurement range is 0.05m-100m.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105784710A (en) * | 2014-12-23 | 2016-07-20 | 桂林电子科技大学 | Concrete bridge crack detection device based on digital image processing |
| CN106225736A (en) * | 2016-07-05 | 2016-12-14 | 中铁第五勘察设计院集团有限公司 | A kind of interior formwork detection device |
| CN106249622A (en) * | 2016-07-13 | 2016-12-21 | 商丘师范学院 | A kind of civil engineering range finding control system |
| CN106872486A (en) * | 2017-03-29 | 2017-06-20 | 中国核工业华兴建设有限公司 | A kind of large volume dry concrete wall detection method of surface flaw |
| CN107289858A (en) * | 2017-07-06 | 2017-10-24 | 广州市九州旗建筑科技有限公司 | The measurement apparatus and method of virtual ruler built in a kind of digital picture |
| WO2019084975A1 (en) * | 2017-10-30 | 2019-05-09 | 江阴市恒润环锻有限公司 | Flange for monitoring cracks in zones using finite element mesh generation method |
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2014
- 2014-12-23 CN CN201420822397.8U patent/CN204405556U/en not_active Expired - Fee Related
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105784710A (en) * | 2014-12-23 | 2016-07-20 | 桂林电子科技大学 | Concrete bridge crack detection device based on digital image processing |
| CN105784710B (en) * | 2014-12-23 | 2018-08-28 | 桂林电子科技大学 | A kind of glue into concrete beam cracks detection device based on Digital Image Processing |
| CN106225736A (en) * | 2016-07-05 | 2016-12-14 | 中铁第五勘察设计院集团有限公司 | A kind of interior formwork detection device |
| CN106249622A (en) * | 2016-07-13 | 2016-12-21 | 商丘师范学院 | A kind of civil engineering range finding control system |
| CN106872486A (en) * | 2017-03-29 | 2017-06-20 | 中国核工业华兴建设有限公司 | A kind of large volume dry concrete wall detection method of surface flaw |
| CN107289858A (en) * | 2017-07-06 | 2017-10-24 | 广州市九州旗建筑科技有限公司 | The measurement apparatus and method of virtual ruler built in a kind of digital picture |
| WO2019084975A1 (en) * | 2017-10-30 | 2019-05-09 | 江阴市恒润环锻有限公司 | Flange for monitoring cracks in zones using finite element mesh generation method |
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