CN109358065A - A kind of subway tunnel appearance detecting method - Google Patents
A kind of subway tunnel appearance detecting method Download PDFInfo
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- CN109358065A CN109358065A CN201811228215.3A CN201811228215A CN109358065A CN 109358065 A CN109358065 A CN 109358065A CN 201811228215 A CN201811228215 A CN 201811228215A CN 109358065 A CN109358065 A CN 109358065A
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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- G01N21/88—Investigating the presence of flaws or contamination
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
- G01N2021/8893—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques providing a video image and a processed signal for helping visual decision
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Abstract
The invention discloses a kind of subway tunnel appearance detecting methods, carry out high-definition image acquisition to structure of the subway tunneling boring surface along the travel path of subway by certain speed using underground railway track image data acquiring platform；It is laterally disposed to the high-definition image of each section acquisition, image by certain speed walking, the acquisition of certain amount website is placed longitudinally, image array is thus formed, image array is subjected to vertical, horizontal splicing, forms a complete, full face subway high definition figure；Then subway segment CAD polar plot corrects image after splicing, obtains the Roaming figure with position coordinates；Then last to calculate defect size and position, automatic classification and statistics automatically the defects of marking crack and infiltration in Roaming figure.The present invention can obtain all visual defects information on subway tunnel surface, the defects of observing the infiltration of submillimeter level, crackle, erosion, leakage, peeling, faulting of slab ends on surface information, the electronization pipe for subway tunnel is supported and maintenance provides science, comprehensive data.
Description
Technical field
The present invention relates to subway tunnel appearance detecting methods.
Background technique
Urban subway tunnel structure local environment is sensitive, complicated, vulnerable to subway train operational shock influence and lining cutting knot
Unavoidably there is percolating water, crack, faulting of slab ends, breakage, big in the junction of structure and the constructional deficiency of its own, subway tunnel structure
The various diseases such as deformation, to influence the performance and safe condition of structure.For the comprehensive and timely safety for grasping tunnel structure
State, it is necessary to it is observed, detect and monitored.The detection of subway tunnel structure disease at present is all used substantially and is manually patrolled
There is the problems such as detection amount of labour is big, and subjectivity is larger in detecting method, detection efficiency is low, low precision, it is difficult to guarantee testing result
Integrality and accuracy can not record and analyze the evolution of disease, can not adapt to the subway tunnel being gradually expanded
The demand of structure health monitoring.
Therefore need a kind of automation, scan-type, digitization, image conversion automatic checkout equipment integrate completion subway tunnel
The full face appearance detecting device and method in road, it is efficient, comprehensive to solve tunnel safety detection problem.
Summary of the invention
The technical problem to be solved by the present invention is in view of the shortcomings of the prior art, provide a kind of subway tunnel appearance detection
Method obtains subway tunnel panoramic high-definition figure and image geometry information by image processing techniques, obtains subway tunnel surface
All visual defects information.
In order to solve the above technical problems, the technical scheme adopted by the invention is that: a kind of subway tunnel appearance detecting method,
The following steps are included:
1) according to subway Tunnel testing required precision γ, camera width direction resolution ratio dpi, central line of camera lens is reached
The distance d of tunnel arc surface, the length SS of camera sensor sensitive filmL, calculate camera minimum focus f；
It 2) is respectively SS by lens focus f, camera sensor length and widthLAnd SSH, tunnel radius r, camera to tunnel
The vertical range d in face calculates the angle beta and direction of travel width S of the tunnel arc surface of every camera covering；
3) according to image Duplication ol, the angle beta and direction of travel width S of single camera covering, the range for needing to detect
θ, shutter interval time t determine camera quantity n2With the travel speed v of Image-capturing platform；
4) by n2A camera once as a line image, clap the image of shooting according to different time intervals simultaneously by single camera
It takes the photograph to form a column image, forms matrix image, i.e. M (n1,n2)；
5) to the n of matrix image1×n2It opens image and carries out splicing；
6) by coordinate transform by each pixel transform in the image after splicing the corresponding seat into CAD coordinate system
Cursor position completes image registration so that the image after splicing becomes the image file for having geometric coordinate and dimension information；
7) defect of image tagged and measurement subway tunnel appearance after registration is utilized.
Camera quantity
The travel speed of Image-capturing platform
The specific implementation process of step 5) includes:
1) according to acquisition platform path dot sequency, stitching image I is treatedcBetween splicing sequence sorted in advance, wherein c
Indicate the quantity of image to be spliced；
2) SURF feature detection algorithm is used, image characteristic point to be spliced is searched；
3) adjacent image I to be spliced is choseni, Ij, the geological information between image to be spliced is combined using RANSAC algorithm
Characteristic point purification is carried out, initial matching pair is obtained；
4) k Feature Points Matching pair, k >=4 are randomly selected from initial matching centering by successive ignition；Treat stitching image
Rough registration is carried out, and utilizes formula v2=Hv1Estimate projective transformation matrix H, wherein v1=(x1,y1,z1), v2=(x2,y2,z2)
For corresponding characteristic point, z=1 is enabled, passes through v1, v2Between homogeneous lineare transformation relationship, acquire element H in Hi,jValue, H is one
A 3 × 3 homogeneous matrix；
5) deformation algorithm is kept using structure, the image after rough registration is deformed, I is obtainedi', Ij'；
6) Graphcut algorithm is used, I is searchedi', Ij' overlapping region best seam；
7) formula is utilizedCalculate pixel in the characteristic point to seam in overlapping region
Distance, as registration error, wherein vfIndicate the characteristic point randomly selected, m indicates vfQuantity, vsIndicate pixel in seam
Point, n indicate vsQuantity；
8) step 3)~step 7) is repeated, all possible image registration relationship is calculated, by registration error E (v) < δ's
Characteristic point, to all characteristic points remained to merging, final image registration relationship is calculated with this to remaining, as
Image is to Ii, IjOptimal registration relationship；
9) step 8) is repeated, the optimal registration relationship between all adjacent images pair is calculated；
10) light velocity method adjustment Algorithm is used, all image registration relationships are optimized；
11) Graphcut algorithm, finding step 10 are used) in final images after registration IcBetween overlapping region best seam
Joint close；
12) image I is realized using multi-spectrum fusion technologycSeamless anastomosing and splicing.
Step 6) the realization process includes:
1) gray processing, equalization and binary conversion treatment are carried out to spliced image, obtains the boundary of works in image
Location information；
2) works boundary coordinate in works boundary coordinate in image and CAD diagram is corresponded, is become by bilinearity
Change, determine correct coordinate position (x, y) for each pixel in image, two-wire mapping relations are as follows:
3) coefficient in above-mentioned two-wire mapping relations formula is found out, realizes the coordinate and practical CAD diagram paper coordinate of each pixel
It corresponds, completes image and be registrated with CAD diagram paper.
Compared with prior art, the advantageous effect of present invention is that: the present invention not only available subway tunnel table
All visual defects information in face observe that the infiltration of submillimeter level, crackle, erosion, leakage, peeling, faulting of slab ends etc. lack on surface
Information is fallen into, meets the needs of Practical Project；The evolving trend of the surface defect both macro and micro of subway tunnel can also be obtained, and
Establish subway tunnel health electronic archive system.
Detailed description of the invention
Fig. 1 is the flow chart of subway tunnel appearance detection system provided by the invention；
Fig. 2 and Fig. 3 is subway tunnel Image-capturing platform provided by the invention；
Fig. 4 is that camera is put and LED lamplight；
101 be acquisition platform, 102 single image acquisition ranges, 103 underground railway tracks；201 be high definition camera, 202 camera
Pallet, 203 be liftable bar, and 204 be the pulley for possessing step function, and 206 be LED ring illumination lamp
Fig. 5 is camera arrangement and shooting area figure；
207 be single camera shooting area, and 208 be lateral overlap region, and 209 be longitudinal overlap region；
Fig. 6 is subway tunnel image mosaic expanded view, that is, image block matrix.
Fig. 7 is stitching algorithm procedure chart；
Fig. 8 is registration process figure.
Specific embodiment
The present invention includes underground railway track data acquisition platform, image mosaic processing, image registration processing and defect database.
It specifically refers to complete to structure of the subway along the travel path of subway by certain speed using underground railway track image data acquiring platform
Cross-sectional face carries out high-definition image acquisition；It is laterally disposed to the high-definition image of each section acquisition, by certain speed walking, centainly
The image of quantity website acquisition is placed longitudinally, thus forms image array, and image array is carried out vertical, horizontal splicing, is formed
One complete, full face subway high definition figure；Then subway segment CAD polar plot corrects image after splicing, obtains
To the Roaming figure for having position coordinates；Then the defects of marking crack and infiltration in Roaming figure, it is big that defect is finally calculated automatically
Small and position, automatic classification and statistics.
(1) subway tunnel Image-capturing platform 101,
Subway tunnel acquisition platform includes Image-capturing platform 101, and more high definition cameras 201, camera pallet 202 can
Elevating lever 203, the pulley 204 of step function, battery bracket 205, LED ring illumination lamp 206.Implementation process is as follows:
To meet detection accuracy requirement, detection accuracy requires γ (0.1mm < γ < 0.2mm), and camera width direction is differentiated
Rate dpi, camera focus f, it is necessary to meet:
First according to subway Tunnel testing required precision γ, camera width direction resolution ratio dpi, central line of camera lens is arrived
Up to the distance d of tunnel arc surface, the length SS of camera sensor sensitive filmL, calculate camera minimum focus f.
Again by lens focus f, size sensor SSLAnd SSH, tunnel radius r, the vertical range d of camera to tunnel face, meter
Calculate the angle beta and direction of travel width S of the tunnel arc surface of every camera covering
The angle beta and direction of travel width S covered further according to image Duplication ol (>=20% ,≤30%), single camera,
Detection range θ, shutter interval time t is needed to determine camera quantity n2With the travel speed v of Image-capturing platform.
Above step has determined platform parameters and the speed of service.When platform acquires, n is placed first, in accordance with Fig. 3 and Fig. 42
Platform camera 201, LED illumination lamp 206, step counting wheel 204, the placing battery and to all cameras on disk 202 on battery stages 205
201, LED illumination lamp, note step wheel 204 etc. are powered；Adjusting elevating lever 203 makes disc centre identical as subway tunnel center, phase
Difference is less than within 100mm；
Can be electronic also in a manner of hand push, according to travel speed v, Image-capturing platform operation is pushed, each website is single
The shooting area of camera is shown in the 206 of Fig. 5, wherein 207 be lateral overlap region, more cameras will detect section covering.
Annular LED headlamp 206 is opened, and pushes Image-capturing platform operation, it is same according to same time interval to automatically control all cameras
When shoot, within a certain period of time it is all shooting shooting numbers be n1, by n2The image that a camera is once shot simultaneously is as one
Row image (Fig. 6 landscape images), single camera shoot to form a column image (longitudinal direction Fig. 6 image) according to different time intervals, by
This forms matrix image, i.e. M (n1,n2)。
(2) image mosaic is handled
Shown in Fig. 6, subway tunnel acquisition platform has taken n1×n2High-definition image is opened, these images are platforms in different positions
The a series of images for setting shooting at close range, different from the camera of fixed position, these images are there are motion parallax, therefore multistation
Point image splicing is the core work of technique.
It is arranged as matrix form image sequence, as shown in Figure 6 according to by these image files first.Specific stitching algorithm mistake
Journey as shown in fig. 7, algorithm the specific implementation process is as follows:
1) according to acquisition platform path dot sequency, stitching image I is treatedcBetween splicing sequence sorted in advance, wherein c
Indicate the quantity of image to be spliced；
2) SURF feature detection algorithm is used, image characteristic point is searched；
3) adjacent image I to be registered is choseni, Ij, carried out using the geological information between RANSAC algorithm combination image special
Sign point purification, obtains initial matching pair；
4) k Feature Points Matching pair, k >=4 are randomly selected from initial matching centering by successive ignition；Image is carried out thick
Registration, and utilize formulaEstimate projective transformation matrix H, wherein v1=
(x1,y1,z1), v2=(x2,y2,z2) it is corresponding characteristic point, z=1 is enabled, v is passed through1, v2Between homogeneous lineare transformation relationship,
Acquire element H in Hi,jValue, H is one 3 × 3 homogeneous matrix；
5) deformation algorithm is kept using structure, the image after rough registration is deformed, I is obtainedi', Ij'；
6) Graphcut algorithm is used, I is searchedi', Ij' overlapping region best seam；
7) formula is utilizedCalculate pixel in the characteristic point to seam in image overlapping region
The distance of point, as registration error, wherein vfIndicate the characteristic point randomly selected, m indicates vfQuantity, vsIt indicates in seam
Pixel, n indicate vsQuantity；
8) step 3)~step 7) is repeated, all possible image registration relationship is calculated, by the spy of registration error E (v) < δ
Sign point usually takes δ=100, to all characteristic points remained to merging, calculates final image with this and match to remaining
Quasi- relationship, as image to Ii, IjOptimal registration relationship；
9) step 8) is repeated, the optimal registration relationship between all adjacent images pair is calculated；
10) light velocity method adjustment Algorithm is used, all image registration relationships are optimized；
11) Graphcut algorithm, finding step 10 are used) in final images after registration IcBetween overlapping region best seam
Joint close；
12) image I is realized using multi-spectrum fusion technologycSeamless anastomosing and splicing.
(3) figure registration process
Previous step completes the splicing operation of the high definition picture in one section of tunnel, and the high definition panorama image in this section of tunnel is
It sets up.It next is exactly the registration work of high-definition image, the purpose is to: high definition panorama image is cut and is calibrated,
So that every piece of section of jurisdiction size on high definition figure is consistent with corresponding CAD polar plot coordinate, size, i.e., by works image registration
To among CAD diagram shape.
The method of registration be by changes in coordinates by each pixel transform in image the corresponding coordinate into CAD coordinate system
Position, so that image becomes the image file for having geometric coordinate and dimension information similar with map.The specific steps of which are as follows:
A) above-mentioned high definition figure figure is subjected to gray processing, equalization and binary conversion treatment, obtains the side of works in image
Boundary's location information.
B) works in panoramic picture and its practical shape and size have deviation, as shown in figure 8, the mesh of figure registration
Be exactly that image data is subjected to geometric transformation, realize and corresponded with CAD diagram shape.By works boundary coordinate in image with
Works boundary coordinate corresponds in CAD diagram, is changed by bilinearity, determines for pixel each in image and correctly sits
Cursor position (x, y), the two-wire mapping relations of two width figures are as follows in Fig. 8:
C) by A and A ', corresponding 4 points such as B and B ' bring formula (9) into respectively, 8 coefficients of above-mentioned a-h can be found out.
E) it after by above-mentioned transformation, realizes that the coordinate of each pixel and practical CAD diagram paper coordinate correspond, completes image
It is registrated with CAD diagram paper.
(4) Database Systems
After figure is registrated, the relationship of image pixel Yu structure actual size has been determined by vector cad file.And according to
Number of pixels determines length, width and the area of defect.Image after completing registration can be by the way of similar map to knot
The defect that structure beyond the region of objective existence is seen is marked and measures.And such as by these defective datas: number is recorded in position, length, width and area
Among library, defect information database is formed.
Among image file after registration, to different type defect classification annotation and number in tunnel, its position is measured
With the geometric dimensions such as size.History testing result can also be compared and analyzed, in conjunction with big data technology, research and judgement ground
Iron tunnel aging rule and trend.Electronization pipe for subway tunnel is supported and maintenance provides science, comprehensive data.
Claims (5)
1. a kind of subway tunnel appearance detecting method, which comprises the following steps:
1) according to subway Tunnel testing required precision γ, camera width direction resolution ratio dpi, central line of camera lens reaches tunnel
The distance d of arc surface, the length SS of camera sensor sensitive filmL, calculate camera minimum focus f；
It 2) is respectively SS by lens focus f, camera sensor length and widthLAnd SSH, tunnel radius r, camera arrives tunnel face
Vertical range d calculates the angle beta and direction of travel width S of the tunnel arc surface of every camera covering；
3) according to image Duplication ol, the angle beta and direction of travel width S of single camera covering, the range Theta for needing to detect, fastly
Door interval time t, determines camera quantity n2With the travel speed v of Image-capturing platform；
4) by n2Once the image of shooting is as a line image simultaneously for a camera, and single camera is according to different time intervals shooting shape
Cheng Yilie image forms matrix image, i.e. M (n1,n2)；
5) to the n of matrix image1×n2It opens image and carries out splicing；
6) by coordinate transform by each pixel transform in the image after splicing the corresponding coordinate bit into CAD coordinate system
It sets, so that the image after splicing becomes the image file for having geometric coordinate and dimension information, completes image registration；
7) defect of image tagged and measurement subway tunnel appearance after registration is utilized.
2. subway tunnel appearance detecting method according to claim 1, which is characterized in that camera quantity
3. subway tunnel appearance detecting method according to claim 1, which is characterized in that the traveling speed of Image-capturing platform
Degree
4. subway tunnel appearance detecting method according to claim 1, which is characterized in that the specific implementation process of step 5)
Include:
1) according to acquisition platform direction of travel and camera arrangement sequence, stitching image I is treatedcBetween splicing sequence carry out it is pre-
Sequence, wherein c indicates the quantity of image to be spliced；
2) SURF feature point detection algorithm is used, image characteristic point is searched；
3) adjacent image I to be registered is choseni, Ij, characteristic point is carried out using the geological information between RANSAC algorithm combination image
Purification, obtains initial matching pair；
4) k Feature Points Matching pair, k >=4 are randomly selected from initial matching centering by successive ignition；Image is slightly matched
Standard, and utilize formulaEstimate projective transformation matrix H, wherein v1=(x1,
y1,z1), v2=(x2,y2,z2) it is Ii, IjIn corresponding characteristic point, enable z=1, pass through v1, v2Between homogeneous lineare transformation close
System, acquires element H in Hi,jValue, H is one 3 × 3 homogeneous matrix；
5) deformation algorithm is kept using structure, the image after rough registration is deformed, I is obtainedi', Ij'；
6) Graphcut algorithm is used, I is searchedi', Ij' overlapping region best seam；
7) formula is utilizedCalculate pixel in the characteristic point to seam in image overlapping region
Distance, as registration error, wherein vfIndicate the characteristic point randomly selected, m indicates vfQuantity, vsIndicate pixel in seam
Point, n indicate vsQuantity；
8) step 3)~step 7) is repeated, all possible image registration relationship is calculated, by the characteristic point of registration error E (v) < δ
To remaining, δ=100 are usually taken, to all characteristic points remained to merging, final image registration is calculated with this and is closed
System, as image to Ii, IjOptimal registration relationship；
9) step 8) is repeated, the optimal registration relationship between all adjacent images pair is calculated；
10) bundle adjustment algorithm is used, all image registration relationships are optimized；
11) Graphcut algorithm, finding step 10 are used) in final images after registration IcBetween overlapping region best seam；
12) image I is realized using multi-spectrum fusion technologycSeamless anastomosing and splicing.
5. subway tunnel appearance detecting method according to claim 1, which is characterized in that the realization process packet of step 6)
It includes:
1) gray processing, equalization and binary conversion treatment are carried out to spliced image, obtains the boundary position of works in image
Information；
2) works boundary coordinate in works boundary coordinate in image and CAD diagram is corresponded, is changed by bilinearity, is
Each pixel determines correct coordinate position (x, y) in image, and two-wire mapping relations are as follows:
3) coefficient in above-mentioned two-wire mapping relations formula is found out, the coordinate and practical CAD diagram paper coordinate for realizing each pixel are one by one
It is corresponding, it completes image and is registrated with CAD diagram paper.
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| CN111665263B (en) * | 2020-06-11 | 2022-04-29 | 长江空间信息技术工程有限公司(武汉) | Shield diversion tunnel structure seam detection method |
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| CN113446953B (en) * | 2021-06-22 | 2023-03-07 | 深圳市市政设计研究院有限公司 | Subway tunnel deformation monitoring system based on digital photogrammetry technology |
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