CN108106801B - Bridge and tunnel disease non-contact detection system and detection method - Google Patents
Bridge and tunnel disease non-contact detection system and detection method Download PDFInfo
- Publication number
- CN108106801B CN108106801B CN201711130182.4A CN201711130182A CN108106801B CN 108106801 B CN108106801 B CN 108106801B CN 201711130182 A CN201711130182 A CN 201711130182A CN 108106801 B CN108106801 B CN 108106801B
- Authority
- CN
- China
- Prior art keywords
- image
- laser
- bridge
- digital camera
- camera
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
- G01M5/0008—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of bridges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/16—Measuring arrangements characterised by the use of optical techniques for measuring the deformation in a solid, e.g. optical strain gauge
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a bridge and tunnel defect non-contact detection system and a detection method, which solve the defects of low efficiency, no effective means for crack tracking measurement and the like of the traditional manual contact type deflection measurement and provide support for the intellectualization of a bridge structure detection technology.
Description
Technical Field
The invention relates to a photogrammetry technology used in civil engineering, which is applied to the technical field of detection of engineering entity maintenance, in particular to a bridge and tunnel defect non-contact detection system and a detection method.
Background
China is a mountainous country, and in order to improve the economic hourly speed of highway and railway transportation, roads are usually constructed in mountainous regions and other regions in the form of bridges and tunnels. By the end of 2013, bridge tunnels and the like in China exceed 73 thousands of seats, the total length is the first in the world, and China also becomes the country with the most complicated and fastest development of tunnels and underground engineering in the world. However, with the rapid development of the transportation industry, especially the rapid increase of over-limit (overweight, ultrahigh, ultra-wide and ultra-long) vehicles, the safety of bridges and tunnels is seriously threatened, and the following collapse accidents happen in recent years, which causes serious loss of property and life of people.
The current common bridge diseases respectively have the following aspects: cracks appear at different parts; the strength of the concrete is not uniform; water seepage of concrete; exposing the steel bars and corroding; the camber of the beam is too large and too small (the prestress is too large and too small); the prestressed duct grouting is not full, and the steel wire is corroded; frost cracking of the beam, etc. If the detection and the discovery are not timely carried out, serious consequences can be caused.
At present, most of domestic tunnel disease detection adopts manual detection, detection personnel are conveyed to the surface of a bridge structure by using platforms such as a bridge detection vehicle, cracks, cavities, corrosion and the like on the appearance of the bridge are observed and identified by artificial naked eyes, and the width, the length and the like of the cracks are measured by a portable instrument. Closing the tunnel by a manual visual observation method, then starting a vehicle with a lifter, lifting a person to the top of the tunnel with the height of 6-7 m, knocking the person little by a hammer, listening to sound or punching, and finishing the detection after 20 persons spend 4 hours when seeing that no hole exists in the tunnel and about 1 kilometer.
The traditional detection technology has the defects that: 1. the long-time high-altitude operation is carried out manually, the objectivity is poor, and the long-time high-altitude operation and the overhead operation are regarded as the fatigue of workers; 2. the detection platform occupies a driving channel and influences traffic; 3. the towering structure and the hidden part are difficult to reach and have poor adaptability.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a bridge and tunnel defect detection system and a detection method, which solve the defects of low efficiency, no effective means for crack tracking measurement and the like of the traditional manual contact type deflection measurement and provide support for the intellectualization of the bridge structure detection technology.
The technical purpose of the invention is realized by the following technical scheme: a bridge and tunnel disease non-contact detection system comprises a non-contact detector, a laser projection subsystem and a data processor for processing measurement data and presenting data processing results, wherein the non-contact detector comprises a high-definition digital camera, a long-focus digital camera, a prism-free laser range finder, a numerical control holder and a bracket;
the long-focus digital camera is connected with the high-definition digital camera and used for acquiring an apparent image of a long-distance structure;
the numerical control holder is arranged below the high-definition digital camera and is used for the high-definition digital camera to acquire images and space angle information of different parts of the bridge and tunnel;
the prism-free laser range finder is used for measuring the physical distance of the detected object;
the laser projection subsystem comprises a laser indicator array, a high-precision control holder and a high-stability bracket;
the laser indicator array is used for projecting a plurality of laser indicating points with fixed spatial positions on the surface of the bridge, the position of the laser point is dynamically adjusted through horizontal and vertical rotation of the high-precision control holder, and the high-stability support is used for supporting the laser indicator array.
Through the arrangement, in the bridge and tunnel load test, the multipoint deformation, the crack width and the length of the bridge are tracked and measured under the condition that a construction platform is not required to be built and the surface of the bridge is not required to be reached to install the prism and the strain sensor, and the working efficiency of the load test can be improved.
As specific embodiments of the present invention, the following may be preferred: the unmanned aerial vehicle system comprises a four-rotor remote control machine, a stability augmentation cradle head, a wireless image transmission communication module and a high-definition camera; high definition camera installs on four rotor telecoms through increasing steady cloud platform, and wireless picture transmission communication module is connected to high definition camera electricity, and wireless picture transmission communication module carries out image data transmission with data processor.
Through the setting, adopt the unmanned aerial vehicle system, can closely shoot bridge and tunnel image, can remote control, avoid shooing the dead angle for the acquirement of bridge and tunnel image is more comprehensive.
A bridge and tunnel disease non-contact detection method is operated by adopting the bridge and tunnel disease non-contact detection system, and comprises the following steps:
the detection of both the disturbance and the crack simultaneously or respectively comprises the following steps:
a perturbation degree detection step
Step A1: forming laser indication points through a laser projection subsystem, and determining a fixed 'reference point' in each preset area in a laser indication mode;
step A2: before loading, a long-focus digital camera and a high-definition digital camera are adopted to obtain an apparent image of a long-distance structure, a surface reference point is selected, and the physical distance of a detected object is obtained through a prism-free laser range finder; the camera detects a plurality of preset areas through the movement of the cradle head by adopting a numerical control cradle head to adjust images and space angles;
step A3: after loading, detecting different point positions by using the method of the step A2;
step A4: and the deflection change of the corresponding point is taken as the vertical distance displacement change of the reference point and the beam bottom before and after loading.
B crack measurement step
Step B1: acquiring an apparent image of a long-distance structure by adopting a long-focus digital camera and a high-definition digital camera, selecting surface characteristic points, and acquiring the physical distance of a detected object by a prism-free laser range finder;
the image and the space angle are adjusted by adopting a numerical control cradle head, and the camera detects the surface of the bridge tunnel through the motion of the cradle head;
step B2: and acquiring a crack image through the structural appearance image.
Through the setting, long focus digital camera and high definition digital camera mutually combine, acquire the structure apparent image of long-distance bridge tunnel, adopt numerical control cloud platform simultaneously, can increase the scope that the image was obtained, through the mode of laser fixed point to improve the precision that the image was obtained, then through image analysis, reachd cracked information.
As specific embodiments of the present invention, the following may be preferred: steps a2 or B1 may be replaced with: and acquiring the physical distance and the structure apparent image of the detected object by adopting an unmanned aerial vehicle system.
Through the setting, the acquisition of the image can be further assisted by an unmanned aerial vehicle system.
As specific embodiments of the present invention, the following may be preferred: in step A2 or B1, for a prism-free laser rangefinderProcessing the acquired data, comprising: obtaining a coordinate conversion formula between the pixel number occupied by the crack graph in the image and the actual physical width, wherein the area of the CCD is a multiplied by b, and the image resolution is s1×s2Substituting camera formation of image CCD's relevant parameter calculation crack actual width, horizontal length is: l = [ (u-f)/f)]·(am1/s1) (ii) a The longitudinal length is: l = [ (u-f)/f)]·(bm2/s2)；
Wherein, a is the long side size of the camera imaging CCD, b is the short side size of the camera imaging CCD, and s1Is a long-side pixel, s2Is the short edge pixel, u is the object distance, f is the focal length, m1M is the number of pixels occupied by the crack width in the image2The number of pixels occupied by the crack length in the image is taken as the number of pixels; l1=am1/s1，l2=bm2/s2。
With the above arrangement, the actual width of the crack can be obtained.
As specific embodiments of the present invention, the following may be preferred: obtaining relative deflection angles of three directions through a numerical control cradle head: alpha is alphaX、αY、αZTo l, to1，l2And (5) correcting: l1=cosαX、Y、Z·（am1/s1），l2=αX、Y、Z·（bm2/s2）。
Through the arrangement, the deviation of the actual width of the crack generated by the change of the deflection angle can be corrected, and the accuracy degree is improved.
As specific embodiments of the present invention, the following may be preferred: correcting the error of the focal length f, wherein f = (mbu)/(mb + s)2L), b and s2It is known that L is obtained by actual measurement.
Through the above arrangement, the accuracy can be further improved by correcting the error of the focal length f.
As specific embodiments of the present invention, the following may be preferred: measuring the distance I from the laser point to the lower edge in the two images by using a distance measuring technology in the imagesFront sideAnd = IRear endThen, the vertical deflection of the beam body at the measuring point is as follows: Δ u = IRear end-IFront side(ii) a Shooting two images containing corresponding laser points and outer contours before and after the application of load at different characteristic point positions of the bridge respectively, and measuring the vertical displacement delta u by using the distance measuring technologyiAnd then the final beam deflection calculation formula f = ∑ (Δ u)i/n）。
In conclusion, the invention has the following beneficial effects:
(1) with deformation measurement, outward appearance detection and the observation function collection in an organic whole of meeting an emergency, use a equipment can accomplish multinomial work, avoid detecting the scene and carry multiple professional equipment, promote work efficiency greatly.
(2) The structure deformation information is acquired by adopting an image measuring mode, external equipment such as a reflecting prism and the like does not need to be installed on the structure, the equipment is simple and convenient to use and convenient to carry, the workload of deformation measurement is greatly reduced, the structure can be measured at any time, and early preparation work is not needed.
(3) The long-focus lens is used for improving the capability of the equipment for obtaining images remotely, and compared with a non-contact detector, the long-focus lens can be automatically focused, and the volume of the long-focus lens is far smaller than that of a lens barrel of an astronomical telescope.
(4) Can measure the strain through structure apparent image, need not artifical at structure surface mounting sensor, avoided loaded down with trivial details cable work of arranging and expensive collection equipment, can observe structure arbitrary position.
Drawings
FIG. 1 is a schematic configuration diagram of the connection of the apparatus of embodiment 1;
FIG. 2 is a schematic view of the imaging relationship of embodiment 2;
FIG. 3 is a schematic view of the imaging principle of the CCD of embodiment 2;
FIG. 4 is a schematic view of the angle error correction in embodiment 2;
fig. 5 is a block diagram of the structure of the unmanned aerial vehicle system of embodiment 3;
FIG. 6 is a schematic diagram of non-contact measurement of bridge-tunnel deformation in example 2;
FIG. 7 is a graph showing the relationship between the laser spot and the beam profile before the bridge/tunnel deformation in example 2;
FIG. 8 is a graph showing the relationship between the laser spot and the beam profile after the bridge and tunnel deformation in example 2;
fig. 9 is a flow chart of deflection calculation of example 2.
In the figure: 1. a non-contact detector; 11. a high definition digital camera; 12. a tele digital camera; 13. a prism-free laser range finder; 14. a numerical control holder; 15. a support; 2. a laser projection subsystem; 21. an array of laser pointers; 22. the cradle head is controlled with high precision; 23. a high stability scaffold; 3. a data processor; 4. an unmanned aerial vehicle system; 41. a four-rotor remote control plane; 42. a stability augmentation holder; 43. a wireless image transmission communication module; 44. provided is a high-definition camera.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
Example 1:
a non-contact detection system for bridge and tunnel diseases is shown in figure 1 and comprises a non-contact detector 1, a laser projection subsystem 2 and a data processor 3 for processing measurement data and presenting data processing results, wherein the non-contact detector 1 comprises a high-definition digital camera 11, a long-focus digital camera 12, a prism-free laser range finder 13, a numerical control holder 14 and a support 15. Wherein, the long-focus digital camera 12 is connected with the high-definition digital camera 11 and is used for acquiring an apparent image of a long-distance structure; the numerical control holder 14 is installed below the high-definition digital camera 11 and is used for the high-definition digital camera 11 to acquire images and spatial angle information of different parts of the bridge and tunnel; the prism-free laser range finder 13 is used for measuring the physical distance of the detected object.
The laser projection subsystem 2 comprises a laser indicator array 21, a high-precision control holder 22 and a high-stability bracket 23; the laser indicator array 21 is used for projecting a plurality of laser indicating points with fixed spatial positions on the surface of the bridge, the position of the laser point is dynamically adjusted by controlling the horizontal and vertical rotation of the holder 22 with high precision, and the high-stability support 23 is used for supporting the laser indicator array 21.
In the bridge load test, the multipoint deformation, the crack width and the length of the bridge are tracked and measured without setting up a construction platform and reaching the surface of the bridge to install the prism and the strain sensor, so that the working efficiency of the load test can be improved.
Example 2:
a bridge and tunnel disease non-contact detection method is combined with the method shown in fig. 2, fig. 3 and fig. 4, the bridge and tunnel disease non-contact detection system is adopted to operate, and the detection of both the disturbance degree and the crack simultaneously or respectively comprises the following steps:
a perturbation degree detection step
Step A1: forming laser indication points through the laser projection subsystem 2, and determining a fixed 'reference point' in each preset area in a laser indication mode;
step A2: before loading, a long-focus digital camera 12 and a high-definition digital camera 11 are adopted to obtain an apparent image of a long-distance structure, a surface reference point is selected, and a physical distance of a detected object is obtained through a prism-free laser range finder 13; the camera detects a plurality of preset areas through the movement of the cradle head by adjusting images and space angles through the numerical control cradle head 14;
step A3: after loading, detecting different point positions by using the method of the step A2;
step A4: and the deflection change of the corresponding point is taken as the vertical distance displacement change of the reference point and the beam bottom before and after loading.
B crack measurement step
Step B1: acquiring an apparent image of a long-distance structure by using a long-focus digital camera 12 and a high-definition digital camera 11, selecting surface characteristic points, and acquiring the physical distance of a detected object by using a prism-free laser range finder 13;
the image and the space angle are adjusted by adopting the numerical control cradle head 14, and the camera detects the surface of the bridge tunnel through the motion of the cradle head;
step B2: and acquiring a crack image through the structural appearance image.
The long-focus digital camera 12 and the high-definition digital camera 11 are combined with each other to obtain a structural appearance image of a long-distance bridge and tunnel, meanwhile, the numerical control holder 14 is adopted to enlarge the image obtaining range, the image obtaining precision is improved in a laser fixed-point mode, and then crack information is obtained through image analysis.
As shown in fig. 2: the object length L, the image length through the lens is L, the object distance u, the image distance v, the focal length f, satisfies the formula: v = (fu)/(u-f).
The object plane and the image plane are parallel, then L = (u/v) L.
As shown in fig. 3, in step 1, the data processing for prism-free laser range finder acquisition includes: obtaining a coordinate conversion formula between the pixel number occupied by the crack graph in the image and the actual physical width, wherein the area of the CCD is a multiplied by b, and the image resolution is s1×s2Substituting camera formation of image CCD's relevant parameter calculation crack actual width, horizontal length is: l = [ (u-f)/f)]·(am1/s1) (ii) a The longitudinal length is: l = [ (u-f)/f)]·(bm2/s2)。
Wherein, a is the long side size of the camera imaging CCD, b is the short side size of the camera imaging CCD, and s1Is a long-side pixel, s2Is the short edge pixel, u is the object distance, f is the focal length, m1M is the number of pixels occupied by the crack width in the image2The number of pixels occupied by the crack length in the image is taken as the number of pixels; l1=am1/s1，l2=bm2/s2。
As shown in fig. 3: during shooting, three directions x, y and z of the optical axis of the camera can deflect, and the relative deflection angles of the three directions are acquired through the numerical control holder: alpha is alphaX、αY、αZTo l, to1，l2And (5) correcting: l1=cosαX、Y、Z·（am1/s1），l2=αX、Y、Z·（bm2/s2）。αX、Y、ZIs alphaXOr alphaYOr alphaZ。
The deviation of the actual width of the crack caused by the change of the deflection angle can be corrected, and the accuracy degree is improved.
Correcting the error of the focal length f, wherein f = (mbu)/(mb + s)2L), b and s2It is known that L is obtained by actual measurement.
As shown in fig. 6, 7, 8 and 9, a laser is installed at a ground fixing pointAnd the light emitter emits laser beams with unchanged spatial positions to the characteristic points of the bridge surface. The laser beam forms a laser spot on the bridge surface, and if the bridge is not deformed, the distance between the laser spot and the characteristic line of the bridge surface (such as the edge profile of the bridge) is fixed. When the bridge deforms, the distance between the laser points and the characteristic line of the bridge also changes, and the change value is the deflection value of the bridge. Then, two images containing the laser point and the outer contour are shot before and after the load is applied to the bridge, and the distance I between the laser point and the lower edge in the two images is measured by using a distance measuring technology in the imagesFront sideAnd = IRear endThen, the vertical deflection of the beam body at the measuring point is as follows: Δ u = IRear end-IFront side(ii) a Shooting two images containing corresponding laser points and outer contours before and after the application of load at different characteristic point positions of the bridge respectively, and measuring the vertical displacement delta u by using the distance measuring technologyiAnd then the final beam deflection calculation formula f = ∑ (Δ u)i/n), from i =1, to i = n.
Example 3:
a non-contact bridge and tunnel disease detection system, as shown in fig. 5, further includes an unmanned aerial vehicle system 4, where the unmanned aerial vehicle system 4 includes a quad-rotor remote control machine 41, a stability-increasing cradle head 42, a wireless image transmission communication module 43, and a high-definition camera 44; high definition camera 44 is installed on four rotor telecamera 41 through increasing steady cloud platform 42, and wireless image transmission communication module 43 is connected to high definition camera 44 electricity, and wireless image transmission communication module 43 carries out image data transmission with data processor 3.
Corresponding to the above method, step 1 may be replaced by: and acquiring the physical distance and the structure apparent image of the detected object by adopting the unmanned aerial vehicle system 4. For the acquisition of the images, it may be further assisted by the drone system 4.
The pan-tilt head adopting Phantom 2 Vision + in Da Jiang can correct the actions of pitching, heeling and horizontal steering three axes, so that the four-rotor remote control machine cannot influence the stability of a camera picture. Phantom 2 Vision + like the first generation, can take the picture of RAW format, can correct the fish eye deformation effect to the effect of normal no deformation through Adobe Lightrom software. The unmanned aerial vehicle adopts a 5400mAh lithium battery, the weight of the battery is 1242g, the hovering precision can reach 0.8m vertically and 2.5m horizontally in a safe flying state, and the maximum flying speed can reach 15 m/s.
The bridge and tunnel images can be shot in a short distance, the dead angle can be avoided being shot through remote control, and the bridge and tunnel images can be obtained more comprehensively.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
Claims (2)
1. A bridge disease multifunctional non-contact detection method is characterized in that a bridge disease multifunctional non-contact detection system is adopted to detect deflection or detect deflection and cracks simultaneously, and the detection system comprises a non-contact detector (1), a laser projection subsystem (2) and a data processor (3) for processing measurement data and presenting data processing results; the non-contact detector (1) comprises a high-definition digital camera (11), a long-focus digital camera (12), a prism-free laser range finder (13), a numerical control holder (14) and a bracket (15);
wherein, the long-focus digital camera (12) is connected with the high-definition digital camera (11) and is used for acquiring the apparent image of the long-distance structure;
the numerical control holder (14) is arranged below the high-definition digital camera (11) and is used for the high-definition digital camera (11) to acquire images and space angle information of different parts of the bridge and tunnel;
the prism-free laser range finder (13) is used for measuring the physical distance of the detected object; the laser projection subsystem (2) comprises a laser indicator array (21), a high-precision control holder (22) and a high-stability bracket (23);
the laser indicator array (21) is used for projecting a plurality of laser indicating points with fixed spatial positions on the surface of a bridge or tunnel, the position of the laser points is dynamically adjusted by controlling the horizontal and vertical rotation of the holder (22) with high precision, and the high-stability support (23) is used for supporting the laser indicator array (21);
the unmanned aerial vehicle system (4) comprises a four-rotor remote control machine (41), a stability augmentation cloud platform (42), a wireless image transmission communication module (43) and a high-definition camera (44); the high-definition camera (44) is installed on the four-rotor remote control aircraft (41) through the stability augmentation cloud platform (42), the high-definition camera (44) is electrically connected with the wireless image transmission communication module (43), and the wireless image transmission communication module (43) and the data processor (3) are used for image data transmission;
the method for detecting the bridge diseases by adopting the multifunctional non-contact detection system comprises the following specific steps:
a deflection detection step
Step A1: a plurality of laser indication points are formed through a laser projection subsystem (2) with a fixed position, and a 'reference point' with a fixed space position is determined in each preset area in a laser indication mode;
step A2: before loading, a long-focus digital camera (12) and a high-definition digital camera (11) are adopted to obtain an apparent image of a long-distance structure, a surface reference point is selected, and a physical distance of a detected object is obtained through a prism-free laser range finder (13); the camera obtains images of a plurality of preset areas through the movement of the cradle head by adjusting the images and the space angle through a numerical control cradle head (14);
step A3: after loading, acquiring images of different preset areas by using the method in the step A2;
step A4: the vertical distance displacement change of the laser reference point and the beam bottom before and after loading is used as the deflection change of the corresponding point;
b crack measurement step
Step B1: a long-focus digital camera (12) and a high-definition digital camera (11) are adopted to obtain an apparent image of a long-distance structure, surface characteristic points are selected, and the physical distance of a detected object is obtained through a prism-free laser range finder (13); the image and the space angle are adjusted by adopting a numerical control cradle head (14), and the camera detects the surface of the bridge and tunnel through the motion of the cradle head;
step B2: acquiring a crack image through the structural appearance image;
in step a2 or B1, the processing of the data acquired by the prism-free laser range finder (13) comprises: obtaining the image of the crack figure in the imageCoordinate conversion formula between prime number and actual physical width, area of CCD is a x b, image resolution is s1×s2Substituting camera formation of image CCD's relevant parameter calculation crack actual width, horizontal length is: l ═ f [ (u-f)/f]·(am1/s1) (ii) a The longitudinal length is: l ═ f [ (u-f)/f]·(bm2/s2) (ii) a Wherein, a is the long side size of the camera imaging CCD, b is the short side size of the camera imaging CCD, and s1Is a long-side pixel, s2Is the short edge pixel, u is the object distance, f is the focal length, and the error of the focal length f is corrected, f ═ mbu)/(mb + s2L), b and s2As is known, L is obtained by actual measurement; m is1M is the number of pixels occupied by the crack width in the image2The number of pixels occupied by the crack length in the image is taken as the number of pixels; l is1＝am1/s1，L2＝bm2/s2；
Obtaining relative deflection angles of three directions through a numerical control cradle head: alpha is alphaX、αY、αZTo L for1，L2And (5) correcting: l is1＝cosαX、Y、Z·(am1/s1)，L2＝cosαX、Y、Z·(bm2/s2) (ii) a Measuring the distance I from the laser point to the lower edge in the two images by using a distance measuring technology in the imagesFront sideAnd ═ IRear endThen, the vertical deflection of the beam body at the measuring point is as follows: Δ u ═ IRear end-IFront side(ii) a Shooting two images containing corresponding laser points and outer contours before and after the application of load at different characteristic point positions of the bridge respectively, and measuring the vertical displacement delta u by using the distance measuring technologyiAnd the final beam deflection calculation formula f ═ sigma (delta u)i/n)。
2. The multifunctional non-contact detection method for bridge diseases according to claim 1, characterized in that: step a2 or B1 was replaced with: and an unmanned aerial vehicle system (4) is adopted to obtain the physical distance and the structure apparent image of the detected object.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711130182.4A CN108106801B (en) | 2017-11-15 | 2017-11-15 | Bridge and tunnel disease non-contact detection system and detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711130182.4A CN108106801B (en) | 2017-11-15 | 2017-11-15 | Bridge and tunnel disease non-contact detection system and detection method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108106801A CN108106801A (en) | 2018-06-01 |
| CN108106801B true CN108106801B (en) | 2021-11-05 |
Family
ID=62206801
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711130182.4A Active CN108106801B (en) | 2017-11-15 | 2017-11-15 | Bridge and tunnel disease non-contact detection system and detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108106801B (en) |
Families Citing this family (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108287164B (en) * | 2017-12-23 | 2021-03-23 | 深圳天眼激光科技有限公司 | Crack detection system |
| CN108731736B (en) * | 2018-06-04 | 2019-06-14 | 山东大学 | Wall radar photoelectricity robot system is climbed automatically for bridge tunnel Structural defect non-destructive testing diagnosis |
| CN110220659B (en) * | 2018-06-19 | 2021-06-08 | 宜昌明磊建设工程有限公司 | Bridge column crack detection device |
| CN110702077A (en) * | 2018-07-10 | 2020-01-17 | 汤慧 | Intelligent range finder and range finding method |
| CN109406525B (en) * | 2018-08-24 | 2023-06-16 | 辽宁省交通规划设计院有限责任公司 | Bridge apparent disease detection system and detection method thereof |
| CN109444163B (en) * | 2018-08-24 | 2023-07-14 | 辽宁省交通规划设计院有限责任公司 | System for obtaining perspective distortion inverse transformation matrix |
| CN109374651B (en) * | 2018-11-02 | 2021-04-27 | 深圳大学 | Large bridge detection method and detection device based on tethered unmanned aerial vehicle |
| CN109682316A (en) * | 2018-11-19 | 2019-04-26 | 湖北电鹰科技有限公司 | Distress in concrete recognition methods and system based on unmanned plane imaging |
| CN109405764B (en) * | 2018-11-27 | 2020-05-12 | 傅博 | Automatic deformation monitoring system based on laser ranging |
| CN109813231B (en) * | 2019-01-14 | 2020-02-14 | 中山大学 | Method for measuring vertical dynamic disturbance of high-speed railway bridge |
| CN109798874B (en) * | 2019-01-14 | 2020-02-14 | 中山大学 | Method for measuring vertical dynamic disturbance of high-speed railway bridge |
| CN110110112A (en) * | 2019-05-05 | 2019-08-09 | 中国民用航空飞行学院 | It is a kind of based on liftable trolley around machine check method and system |
| CN110132151B (en) * | 2019-05-29 | 2020-12-11 | 河海大学 | Concrete arch dam underwater crack electric control itinerant monitoring device and using method thereof |
| CN110487188B (en) * | 2019-09-12 | 2024-05-03 | 山东交通学院 | Bridge crack detecting system |
| CN112342908B (en) * | 2020-09-30 | 2022-02-08 | 山东大学 | Primary-secondary type infrastructure disease detection and repair system and method |
| CN112171692B (en) * | 2020-10-15 | 2023-12-12 | 吉林大学 | Intelligent bridge deflection detection device and method |
| CN113157005B (en) * | 2021-04-22 | 2022-11-11 | 中煤科工集团重庆研究院有限公司 | Rotating holder for monitoring deformation of tunnel section and control system thereof |
| CN113340405B (en) * | 2021-07-09 | 2023-03-17 | 中铁七局集团有限公司 | Bridge vibration mode measuring method, device and system |
| CN113884011A (en) * | 2021-09-16 | 2022-01-04 | 刘逸 | Non-contact concrete surface crack measuring equipment and method |
| CN115219507B (en) * | 2022-07-18 | 2023-04-07 | 兰州工业学院 | Health monitoring method applied to bridge and tunnel structure maintenance |
| CN116045830B (en) * | 2022-08-25 | 2023-08-08 | 北京城建集团有限责任公司 | Automatic measuring system for door-span type crack development |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201173847Y (en) * | 2008-04-01 | 2008-12-31 | 重庆交通大学 | Wireless remote control type deflection measuring systems for bridge loading experiment |
| CN102519383A (en) * | 2011-12-27 | 2012-06-27 | 中铁大桥局集团武汉桥梁科学研究院有限公司 | Bridge dynamic deflection facula imaging measuring device and method |
| CN102564335A (en) * | 2012-01-16 | 2012-07-11 | 苏州临点三维科技有限公司 | Method for measuring deformation of large-scale tunnel |
| CN104613891A (en) * | 2015-02-10 | 2015-05-13 | 上海数久信息科技有限公司 | Bridge deflection detection system and detection method |
| CN105735150A (en) * | 2016-03-04 | 2016-07-06 | 浙江大学 | Movable multi-view visual bridge conventional detection method |
| 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 |
| CN106225708A (en) * | 2016-08-30 | 2016-12-14 | 北京航空航天大学 | A kind of generic video deflection metrology system insensitive to ambient light |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4958306A (en) * | 1988-01-06 | 1990-09-18 | Pacific Northwest Research & Development, Inc. | Pavement inspection apparatus |
| AUPP107597A0 (en) * | 1997-12-22 | 1998-01-22 | Commonwealth Scientific And Industrial Research Organisation | Road pavement deterioration inspection system |
| CN2767955Y (en) * | 2005-01-28 | 2006-03-29 | 赵启林 | Bridge detecting instrument system based on digital photographing technique |
| US7937229B2 (en) * | 2007-05-29 | 2011-05-03 | Massachusetts Institute Of Technology | System and method for detecting damage, defect, and reinforcement in fiber reinforced polymer bonded concrete systems using far-field radar |
| US9014415B2 (en) * | 2010-04-22 | 2015-04-21 | The University Of North Carolina At Charlotte | Spatially integrated aerial photography for bridge, structure, and environmental monitoring |
| US10459615B2 (en) * | 2014-12-11 | 2019-10-29 | Rdi Technologies, Inc. | Apparatus and method for analyzing periodic motions in machinery |
| CN105975972B (en) * | 2016-04-27 | 2019-05-07 | 湖南桥康智能科技有限公司 | Bridge Crack detection and feature extracting method based on image |
| CN106123797A (en) * | 2016-08-29 | 2016-11-16 | 北京交通大学 | Bridge floor deflection metrology system based on image procossing and method |
| CN106918598B (en) * | 2017-03-08 | 2019-06-21 | 河海大学 | Bridge pavement strain and crack detection analysis system and method based on digital picture |
-
2017
- 2017-11-15 CN CN201711130182.4A patent/CN108106801B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201173847Y (en) * | 2008-04-01 | 2008-12-31 | 重庆交通大学 | Wireless remote control type deflection measuring systems for bridge loading experiment |
| CN102519383A (en) * | 2011-12-27 | 2012-06-27 | 中铁大桥局集团武汉桥梁科学研究院有限公司 | Bridge dynamic deflection facula imaging measuring device and method |
| CN102564335A (en) * | 2012-01-16 | 2012-07-11 | 苏州临点三维科技有限公司 | Method for measuring deformation of large-scale tunnel |
| 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 |
| CN104613891A (en) * | 2015-02-10 | 2015-05-13 | 上海数久信息科技有限公司 | Bridge deflection detection system and detection method |
| CN105735150A (en) * | 2016-03-04 | 2016-07-06 | 浙江大学 | Movable multi-view visual bridge conventional detection method |
| CN106225708A (en) * | 2016-08-30 | 2016-12-14 | 北京航空航天大学 | A kind of generic video deflection metrology system insensitive to ambient light |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108106801A (en) | 2018-06-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108106801B (en) | Bridge and tunnel disease non-contact detection system and detection method | |
| CN109632103B (en) | High-altitude building temperature distribution and surface crack remote monitoring system and monitoring method | |
| CN106091946B (en) | Self-calibration measuring device and method for bridge deformation or displacement parameter | |
| CN101339003B (en) | Great structure horizontal two-dimensional displacement automatic measuring equipment and method | |
| WO2016059877A1 (en) | Controller, control method, and flight vehicle device | |
| CN111866337A (en) | Intelligent inspection robot and inspection method | |
| CN101539397B (en) | Method for measuring three-dimensional attitude of object on precision-optical basis | |
| CN109186944B (en) | Airborne multi-optical-axis optical load optical axis consistency calibration method | |
| CN210946763U (en) | Slope deformation monitoring system | |
| CN103913117A (en) | Three-dimensional laser scanner positioning device and laser point cloud absolute positioning method | |
| CN111445522B (en) | Passive night vision intelligent lightning detection system and intelligent lightning detection method | |
| CN110702343B (en) | Deflection measurement system and method based on stereoscopic vision | |
| CN111999298A (en) | Unmanned aerial vehicle bridge system of patrolling and examining fast based on 5G technique | |
| JP2007107962A (en) | Measuring system of measuring object and separated measuring system under transmission line | |
| CN109813509B (en) | Method for realizing measurement of vertical dynamic disturbance degree of high-speed rail bridge based on unmanned aerial vehicle | |
| CN112762906B (en) | Multi-sensor fusion-based guiding system and guiding method | |
| CN115829918A (en) | Machine vision-based monitoring method for deformation of large facility structure | |
| CN110207605B (en) | Device and method for measuring metal structure deformation based on machine vision | |
| CN111895969A (en) | Bridge pier settlement monitoring system and monitoring method thereof | |
| CN112730422B (en) | Nuclear power station containment defect detection method and system | |
| CN110160460B (en) | Metal structure deformation measuring device and method based on digital photography | |
| CN210533296U (en) | Tunnel hole circumferential deformation monitoring system | |
| CN112265912A (en) | Integrated operation system and method of lorry-mounted crane | |
| CN112923902A (en) | Automatic monitoring system and monitoring method for three-dimensional deformation of crust fault | |
| CN210154537U (en) | Metal structure deformation measuring device based on digital photography |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |