CN115078393A - Method for detecting damage of hinge joint of simply supported hollow slab bridge based on computer vision - Google Patents
Method for detecting damage of hinge joint of simply supported hollow slab bridge based on computer vision Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30132—Masonry; Concrete
Abstract
The invention discloses a method for detecting damage of a hinge joint of a simply supported hollow slab bridge based on computer vision; the method comprises the following steps: s1: acquiring a vibration video of a section of area of any cross section of the bottom of the simply supported hollow slab bridge along the length direction of the bridge; s2: extracting an average displacement time course in a certain area of the simply supported hollow slab bridge and an average displacement time course in a certain area of the hinged joint according to a vibration video of a section of area of any cross section of the bottom of the bridge along the length direction of the bridge; s3: and constructing a relation between the average displacement time course of a certain area of the hinged joint and the rigidity of the hinged joint and the average displacement time course of a certain area of the simply-supported hollow slab bridge and the rigidity of the simply-supported hollow slab bridge, and reflecting the change of the rigidity of the hinged joint based on the damage indexes related to the average displacement difference of the certain area of two adjacent beams of the simply-supported hollow slab bridge to finally realize the damage detection of the hinged joint. The invention can predict the damage degree of the hinge joint, has high detection efficiency and accuracy, and can reduce the maintenance cost of the bridge compared with the conventional detection mode.
Description
Technical Field
The invention belongs to the technical field of bridge disease detection, and particularly relates to a method for detecting damage of a hinge joint of a simply supported hollow slab bridge based on computer vision.
Background
The simple-supported hollow slab bridge is one of the most common assembled reinforced concrete bridges in medium and small span bridges, and has the advantages of convenient construction, simple structure, low material cost, small section height and the like. Researches find that the hollow slab bridge accounts for more than 60 percent of the existing bridge in China. Under the action of vehicle load and natural environment erosion, the hinge joint of the hollow slab bridge can be damaged to different degrees. At present, a damage detection method for a hollow slab bridge hinge joint is mainly used for qualitatively judging whether the hinge joint is damaged or not through visual inspection. When water seepage from the bottom of the hollow board or longitudinal cracks in the road surface in the vicinity of the joint area are observed, the joint is identified as damaged. When these distinct features are observed, damage to the hinge joints can be very severe, requiring significant cost, time and labor to maintain the bridge, sometimes requiring tools such as boats and under-bridge inspection vehicles, and even traffic control. In addition, the accuracy of visual inspection depends highly on subjective judgment, experience, and training of the inspector, and the inspection time and the field environment (e.g., temperature) also affect the accuracy.
The prior art discloses a patent document with the application number of CN202210432849.0, which is named as a bridge monitoring method, a system and a device based on a micro-vibration amplification technology; the patent document discloses how to obtain the time course of the bridge vibration displacement. This method may be used in the present application and is described in detail in the detailed description section.
Disclosure of Invention
The invention aims to provide a method for detecting damage of a hinge joint of a simply supported hollow slab bridge based on computer vision aiming at the defects in the prior art; the seam detection method is used for solving the problems that an existing seam detection mode is lagged and is not accurate in detection.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method for detecting damage of a hinge joint of a simply supported hollow slab bridge based on computer vision comprises the following steps:
s1: acquiring a vibration video of a section of area of any cross section of the bottom of the simply supported hollow slab bridge along the length direction of the bridge;
s2: extracting an average displacement time course in a certain area of the simply supported hollow slab bridge and an average displacement time course in a certain area of the hinged joint according to a vibration video of a section of area of any cross section of the bottom of the bridge along the length direction of the bridge;
s3: the method comprises the steps of establishing a relation between the average vibration displacement time course of a certain area of the hinged joint and the rigidity of the hinged joint and the average displacement time course of the certain area of the simply-supported hollow slab bridge and the rigidity of the simply-supported hollow slab bridge, and reflecting the change of the rigidity of the hinged joint based on the damage indexes related to the average displacement difference of the certain area of two adjacent beams of the simply-supported hollow slab bridge, so that the damage degree of the hinged joint is indirectly reflected, and the damage detection of the hinged joint is realized.
Further, in step S1, the beam bottom vibration video is captured by multiple high-speed cameras arranged at the beam bottom in real time.
Further, in step S2, the extracting process of the average displacement time of a certain region of the simply supported hollow slab bridge bottom and the average displacement time of a certain region of the hinge joint includes:
s2.1: preprocessing a vibration video at the bottom of the beam by a space-time context tracking algorithm and a defogging algorithm to remove the interference of rain, haze and hot waves on the video;
s2.2: amplifying the beam bottom vibration video of the frequency base band of interest by using a motion amplification algorithm based on deep learning, adding the video image subjected to amplification back to the high-pass residual part and the low-pass residual part image sequence, and reconstructing the amplified image sequence by using a plurality of controllable pyramids to output the amplified vibration video;
s2.3: marking the measuring points in the reconstructed amplified simply supported hollow slab bridge vibration video, segmenting the measuring points in the amplified simply supported hollow slab bridge vibration video by using a trained Mask R-CNN network, obtaining pixel-level coordinates of centroids of all measuring points in a simply supported hollow slab bridge vibration image sequence through regression analysis, subtracting the centroid coordinates of a subsequent frame image starting from a 2 nd frame image from the centroid coordinates of a 1 st frame image to obtain pixel-level vibration displacement time courses of all point groups of the simply supported hollow slab bridge bottom and the hinge joint in a certain area, converting the pixel-level displacement into a physical displacement time course according to a size factor to obtain the physical displacement time course of each beam on the simply supported hollow slab bridge, representing the difference value of the physical displacement time courses of the adjacent simply supported hollow slab bridge bottoms into the hinge joint physical displacement time course, averaging the physical displacement time courses of the simply supported hollow slab bridge bottom and the hinge joint all point groups in the certain area, specifically, the algebraic sum of the physical displacement time courses of all point groups of the central line of the bottom of a single hollow slab in a certain area along the length direction of the simply supported hollow slab bridge is calculated, the algebraic sum of the physical displacement time courses of all the point groups is divided by the number of the point groups on the central line of the bottom of the hollow slab bridge to obtain the average displacement time course in the certain area of the bottom of the single hollow slab bridge, the average displacement time course in the certain area of the bottom of each simply supported hollow slab bridge can be calculated by repeating the steps, the average displacement time courses in the certain area of the bottoms of two adjacent hollow slab bridges are differed, and the average displacement time course in the certain area of the hinge joint can be obtained.
Further, in step S3, the relation between the average displacement time of a certain region of the hinge joint and the rigidity of the hinge joint and the average displacement time of a certain region of the simple supported hollow slab bridge and the rigidity of the simple supported hollow slab bridge is defined as:
in the formula (I), the compound is shown in the specification,
the ratio of the average displacement of a certain area of the hinge joint to the average displacement of a certain area of a hollow slab beam;
is the ratio of the stiffness of the hinge joint to the stiffness of a hollow slab beam.
The invention has the beneficial effects that:
the detection method is characterized in that the average vibration displacement time course of a certain area of adjacent simply supported hollow slab bridges is obtained based on computer vision, and then the average vibration displacement time course of the certain area of the hinged joint is extracted, and the extraction of the average displacement time course of the area can reduce detection errors; after the relation between the average vibration displacement time course and the rigidity of a certain area of the hinge joint and the average vibration displacement time course and the rigidity of a certain area of the simply supported hollow slab bridge is established, the change situation of the rigidity of the joint is indirectly reflected through the change of the average vibration displacement of the certain area of the adjacent simply supported hollow slab bridge, so that a judgment basis is provided for the damage situation of the hinge joint, and the damage detection of the hinge joint is realized; the detection method can predict the damage degree of the hinge joint in advance, is efficient in detection and more accurate in detection, and can reduce the maintenance cost of the bridge compared with the existing detection mode.
Drawings
FIG. 1 is a flow chart of the detection method of the present invention;
FIG. 2 is a schematic diagram of a high-speed camera acquiring a beam bottom vibration video of a simply supported hollow slab bridge according to the invention;
FIG. 3 is a schematic diagram showing the relationship between the displacement and the rigidity of the adjacent simply supported hollow slab bridges and the hinge joints.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings.
As shown in fig. 1 to 3, a method for detecting damage to a hinge joint of a simply supported hollow slab bridge based on computer vision; the method mainly comprises the following steps:
s1: obtaining a vibration video of a section (0.1-0.2 m) of any cross section of the bottom of the simply supported hollow slab bridge along the length direction of the bridge; the method comprises the following steps that a beam bottom vibration video is obtained through real-time shooting of a plurality of high-speed cameras arranged at the beam bottom, wherein the high-speed cameras are arranged at beam piers or other suitable positions without vibration; the beam bottom vibration video can also be continuously shot and collected within a certain time by adopting an unmanned aerial vehicle carrying a high-speed camera.
S2: extracting an average displacement time course of a certain area of the simply supported hollow slab bridge and an average displacement time course of a certain area of the hinged joint according to the beam bottom vibration video; the method specifically comprises the following steps:
s2.1: and preprocessing the vibration video at the bottom of the beam by a space-time context tracking algorithm and a defogging algorithm to remove the interference of rain, haze and hot waves on the video. The beam bottom vibration video image acquired by the high-speed camera can be influenced by rain, haze and heat waves; when the vibration video of the hinged joint is amplified by utilizing the motion amplification based on deep learning, the motion of raindrops, haze and hot waves is amplified in equal proportion, and finally the motion of the raindrops, the haze and the hot waves can be amplified greatly, so that the motion of the hinged joint of the simply-supported hollow slab bridge is submerged, the vibration displacement of the hinged joint cannot be accurately identified, and the identification accuracy can be improved by preprocessing the vibration video at the bottom of the beam through a space-time context tracking algorithm and a defogging algorithm.
S2.2: and amplifying the beam bottom vibration video of the baseband of the frequency of interest by using a deep learning-based motion amplification algorithm. Firstly, carrying out complex controllable pyramid decomposition on a beam bottom vibration video sequence to obtain local amplitude spectrums and phase spectrums in different scales and directions; and secondly, calculating a phase difference according to the local phase spectrum, performing unwrapping processing on the phase, and extracting a phase difference signal of the baseband of the frequency of interest by utilizing linear phase band-pass filtering. Thirdly, by selecting a proper amplification factor
And amplifying different interested frequency base bands to realize the amplification of the vibration amplitude of the vibration video at the bottom of the beam of the interested frequency base band. And finally, reconstructing the video image after the amplification processing by using the plurality of controllable pyramids, and outputting the amplified vibration video.
The principle of motion amplification based on deep learning is specifically described asThe following: assuming that the one-dimensional space domain signal of the beam bottom vibration is
，
Is composed of
The micro-vibration displacement generated by simply supporting the hollow slab bridge in the time domain is amplified by a factor
Obtaining amplified vertical vibration space domain signals of the simply supported hollow slab bridge as
That is to say, the vibration displacement amplitude of the simply supported hollow slab bridge is amplified
And (4) doubling. Firstly, the first step is to
Represented as a superposition of a series of complex sinusoidal signals. Namely, it is
In the formula (I), the compound is shown in the specification,
is the circular frequency of a certain sub-sinusoidal signal.
For a certain circular frequency of
Has the following complex sinusoidal signals:
to pair
Linear amplification
Adding after doubling
Then there is
S2.3: marking the measuring points in the reconstructed amplified simply supported hollow slab bridge vibration video, segmenting the measuring points in the amplified simply supported hollow slab bridge vibration video by using a trained Mask R-CNN network, obtaining pixel-level coordinates of centroids of all measuring points in a simply supported hollow slab bridge vibration image sequence through regression analysis, subtracting the centroid coordinates of a subsequent frame image starting from a 2 nd frame image from the centroid coordinates of a 1 st frame image to obtain pixel-level vibration displacement time courses of all point groups of the simply supported hollow slab bridge bottom and the hinge joint in a certain area, converting the pixel-level displacement into a physical displacement time course according to a size factor to obtain the physical displacement time course of each beam on the simply supported hollow slab bridge, representing the difference value of the physical displacement time courses of adjacent simply supported hollow slab bridges into the physical displacement time course of the hinge joint, averaging the physical displacement time courses of all the simply supported hollow slab bridge bottom and the hinge joint in the certain area, specifically, the algebraic sum of the physical displacement time courses of all point groups of the central line of the bottom of a single hollow slab in an area of 0.1-0.2 m in the length direction of the simply supported hollow slab bridge is calculated, the algebraic sum of the physical displacement time courses of all the point groups is divided by the number of the point groups on the central line of the bottom of the hollow slab bridge to obtain the average displacement time course in a certain area of the bottom of the single hollow slab bridge, the average displacement time course in the certain area of the bottom of the simply supported hollow slab bridge can be calculated by repeating the steps, the average displacement time courses in the certain area of the bottom of two adjacent hollow slab bridges are differed, and the average displacement time course in the certain area of the hinge joint can be obtained. The vibration displacement time-course response is extracted through Mask R-CNN, the problem that targets need to be installed manually when the displacement time-course response is extracted through digital image correlation and template matching algorithms is effectively solved, and the extraction of the vibration displacement of the hinge joint can be realized without the targets.
The vibration displacement time course of all point groups of a certain cross section of the simply supported hollow slab bridge along one section of the length direction of the bridge is calculated firstly, the average displacement of the bottoms of the two hollow slab beams and the hinged joint in a certain area is calculated through the vibration displacement time courses of all the point groups in the certain area, accidental errors caused by factors such as testing conditions, illumination transformation and temperature change during the displacement time course of a single point are effectively avoided, and the recognition accuracy of the displacement time courses of the two hollow slab beams and the hinged joint at the certain cross section of the simply supported hollow slab bridge is improved.
When the size factor is acquired, when the optical axis of the camera is vertical to the plane of the hinge joint structure, namely the optical axis is collinear with the normal line of the structure plane,
the scale factor is represented by formula (1) or formula (2):
or
In the formula (I), the compound is shown in the specification,Dselecting the size of an object in the plane of the structure;dfor its corresponding number of pixels in the image plane;fis the focal length of the lens;Zis the distance of the camera to the plane of the structure;
is the pixel size.
When the camera optical axis is not perpendicular to the hinge joint structure plane, namely, the optical axis and the structure plane normal line have an included angle, the scale factor is as shown in formula (3):
in the formula (I), the compound is shown in the specification,
is the angle between the optical axis of the camera and the normal of the plane of the structure.
Extracting the average displacement time course of a certain area of the simply supported hollow slab bridge and the average displacement time course of a certain area of the hinged joint according to the beam bottom vibration video, wherein the displacement time courses can be extracted according to the method, but not limited to the method; for example, patent documents with application number CN202210432849.0 entitled bridge monitoring method, system and apparatus based on micro vibration amplification technology disclose a method for obtaining vibration displacement time course of bridge, which can be directly applied to simple supported hollow slab bridge and can obtain vibration displacement time course of simple supported hollow slab bridge.
S3: establishing a relationship between the average displacement time course of a certain region of the hinge joint and the rigidity of the hinge joint and the average displacement time course of a certain region of the simply-supported hollow slab bridge and the rigidity of the simply-supported hollow slab bridge, specifically, referring to fig. 3, the rigidities of two adjacent hollow slab beams (the square frames of 1 and 2 are shown in the figure) and the hinge joint are respectively
、
And
the average displacement in a section of area of two adjacent hollow plate beams and the hinge joint is respectively
、
And
the concentrated force F acts on the left hollow slab beam (beam of the hollow slab bridge). The mid-span deflection of the simply supported beam in the elastic stage is in direct proportion to the magnitude of concentrated load, and under the assumption of force balance and deformation coordination, the following equation can be obtained:
in the formula (I), the compound is shown in the specification,M，N，Pthe number of the point groups of the central line of the bottom of the two adjacent hollow slab bridges in a certain area and the number of the point groups of the central line of the hinge joint in a certain area are respectively.
Assuming equal stiffness of the individual sheets of hollow-slab beams, i.e.
Then, equations (4) - (6) can be written as:
the ratio of the displacement difference (hinge joint displacement) of the adjacent two hollow plate beams to the average displacement of the adjacent two hollow plate beams can be expressed as follows:
order to
、
Then equation (10) can be simplified as:
In the formula (I), the compound is shown in the specification,
the displacement of the hinge joint is the ratio of the displacement of the hollow plate beam 1;
is the rigidity ratio of the hinge joint to the hollow plate girder 1.
As can be seen from equation (11), when the hinge joint is broken, the average displacement ratio in the region of the hinge joint increases as the rigidity of the hinge joint decreases. The average displacement in the area of the hinge joint can be characterized by the average displacement difference in the area of two adjacent beams. Therefore, the change of the rigidity of the hinge joint can be represented by a damage index related to the average displacement difference in the areas of the two adjacent beams, so that the damage degree of the hinge joint is indirectly reflected. The damage of the hinge joint is monitored by taking the ratio of the average displacement difference in the area and the average displacement in the area of two adjacent hollow slab beams as a damage index, and the average vibration displacement time course in the hinge joint area measured in real time is substituted by a formula (10), so that the damage of the hinge joint of the simply supported hollow slab bridge can be monitored.
When the relative displacement ratio exceeds a preset threshold value, the hinge joint of the simply supported hollow slab bridge is considered to be damaged, an early warning signal is automatically sent to the monitoring cloud platform, the damage position and the damage degree of the hinge joint are judged, and the real-time online monitoring of the damage of the hinge joint of the simply supported hollow slab bridge is realized.
Claims (4)
1. A method for detecting damage of a hinge joint of a simply supported hollow slab bridge based on computer vision is characterized by comprising the following steps:
s1: acquiring a vibration video of a section of area of any cross section of the bottom of the simply supported hollow slab bridge along the length direction of the bridge;
s2: extracting an average displacement time course in a certain area of the simply supported hollow slab bridge and an average displacement time course in a certain area of the hinged joint according to a vibration video of a section of area of any cross section of the bottom of the bridge along the length direction of the bridge;
s3: the method comprises the steps of establishing a relation between the average displacement time course of a certain area of the hinged joint and the rigidity of the hinged joint and the average displacement time course of the certain area of the simply-supported hollow slab bridge and the rigidity of the simply-supported hollow slab bridge, and reflecting the change of the rigidity of the hinged joint based on the damage indexes related to the average displacement difference of the certain area of two adjacent beams of the simply-supported hollow slab bridge, so that the damage degree of the hinged joint is indirectly reflected, and the damage detection of the hinged joint is realized.
2. The method for detecting damage to the hinge joint of the simply supported hollow slab bridge based on the computer vision as claimed in claim 1, wherein in the step S1, the bottom vibration video is obtained by real-time shooting through a plurality of high-speed cameras arranged at the bottom of the beam.
3. The method for detecting damage to the hinge joint of the simply supported hollow slab bridge based on the computer vision as claimed in claim 1, wherein in the step S2, the extracting process of the average displacement time interval of a certain region of the simply supported hollow slab bridge bottom and the average displacement time interval of a certain region of the hinge joint comprises:
s2.1: preprocessing a vibration video at the bottom of the beam by a space-time context tracking algorithm and a defogging algorithm to remove the interference of rain, haze and hot waves on the video;
s2.2: amplifying the beam bottom vibration video of the frequency base band of interest by using a motion amplification algorithm based on deep learning, adding the video image subjected to amplification back to the high-pass residual part and the low-pass residual part image sequence, and reconstructing the amplified image sequence by using a plurality of controllable pyramids to output the amplified vibration video;
s2.3: marking the measuring points in the reconstructed amplified simply supported hollow slab bridge vibration video, segmenting the measuring points in the amplified simply supported hollow slab bridge vibration video by using a trained Mask R-CNN network, obtaining pixel-level coordinates of centroids of all measuring points in a simply supported hollow slab bridge vibration image sequence through regression analysis, subtracting the centroid coordinates of a subsequent frame image from a 2 nd frame image from the centroid coordinates of a 1 st frame image to obtain a vibrating pixel-level displacement time course of the simply supported hollow slab bridge, converting the pixel-level displacement into a physical displacement time course according to a size factor to obtain a physical displacement time course of each beam on the simply supported hollow slab bridge, representing the physical displacement time course difference value of the beam bottoms of adjacent simply supported hollow slab bridges as a hinge joint physical displacement time course, averaging the physical displacement time courses of all point groups of the simply supported hollow slab bridge bottoms and the hinge joints in a certain area, and obtaining the average displacement time course of a certain area of the simply supported hollow slab bridge bottom and the average displacement time course of a certain area of the hinged joint.
4. The method for detecting damage to the hinge joint of the simple supported hollow slab bridge based on the computer vision as claimed in claim 1, wherein in the step S3, the relationship between the hinge joint displacement time and the rigidity of the hinge joint and the displacement time and the rigidity of the simple supported hollow slab bridge is as follows:
in the formula (I), the compound is shown in the specification,
is the ratio of the displacement of the hinge joint to the displacement of one of the hollow slab beams;
is the ratio of the stiffness of the hinge joint to the stiffness of a hollow slab beam.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116559172A (en) * | 2023-04-23 | 2023-08-08 | 兰州交通大学 | Unmanned aerial vehicle-based steel bridge welding seam detection method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20130076988A (en) * | 2011-12-29 | 2013-07-09 | 한국유지관리 주식회사 | System for portable video inspection |
| US20130216089A1 (en) * | 2010-04-22 | 2013-08-22 | The University Of North Carolina At Charlotte | Method and System for Remotely Inspecting Bridges and Other Structures |
| CN110736534A (en) * | 2019-10-16 | 2020-01-31 | 福建省建筑工程质量检测中心有限公司 | vibration displacement real-time measurement method based on common camera |
| CN112051048A (en) * | 2020-09-07 | 2020-12-08 | 哈尔滨工业大学 | Hollow slab bridge hinge joint rapid evaluation method based on action of power of moving vehicle |
| CN112945969A (en) * | 2021-01-26 | 2021-06-11 | 浙江省交通运输科学研究院 | Hollow slab beam bridge hinge joint damage identification method and system based on machine vision measurement |
| CN114528887A (en) * | 2022-04-24 | 2022-05-24 | 湖南大学 | Bridge monitoring method, system and device based on micro-vibration amplification technology |
-
2022
- 2022-08-23 CN CN202211012106.4A patent/CN115078393B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130216089A1 (en) * | 2010-04-22 | 2013-08-22 | The University Of North Carolina At Charlotte | Method and System for Remotely Inspecting Bridges and Other Structures |
| KR20130076988A (en) * | 2011-12-29 | 2013-07-09 | 한국유지관리 주식회사 | System for portable video inspection |
| CN110736534A (en) * | 2019-10-16 | 2020-01-31 | 福建省建筑工程质量检测中心有限公司 | vibration displacement real-time measurement method based on common camera |
| CN112051048A (en) * | 2020-09-07 | 2020-12-08 | 哈尔滨工业大学 | Hollow slab bridge hinge joint rapid evaluation method based on action of power of moving vehicle |
| CN112945969A (en) * | 2021-01-26 | 2021-06-11 | 浙江省交通运输科学研究院 | Hollow slab beam bridge hinge joint damage identification method and system based on machine vision measurement |
| CN114528887A (en) * | 2022-04-24 | 2022-05-24 | 湖南大学 | Bridge monitoring method, system and device based on micro-vibration amplification technology |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116559172A (en) * | 2023-04-23 | 2023-08-08 | 兰州交通大学 | Unmanned aerial vehicle-based steel bridge welding seam detection method and system |
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