KR101174105B1 - Non-contact method for generating parameter data for measuring displacement of structure - Google Patents

Non-contact method for generating parameter data for measuring displacement of structure Download PDF

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Publication number
KR101174105B1
KR101174105B1 KR20100078266A KR20100078266A KR101174105B1 KR 101174105 B1 KR101174105 B1 KR 101174105B1 KR 20100078266 A KR20100078266 A KR 20100078266A KR 20100078266 A KR20100078266 A KR 20100078266A KR 101174105 B1 KR101174105 B1 KR 101174105B1
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South Korea
Prior art keywords
target
camera
data
image
target image
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KR20100078266A
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Korean (ko)
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KR20120015819A (en
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김광수
심재위
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김광수
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Abstract

A method of generating parametric data for measuring structure displacement using a non-contact multichannel digital camera is provided. By combining a non-contact multi-channel camera, a plurality of targets, which are installed at a plurality of operating points of the structure, are captured and collected at a low speed, and a target image that is visible when the target image is confirmed by the user through a setting change process. Ensure the optimal state for a clear image. When the combination and recognition of the contactless multi-channel camera is maintained at an optimal state, the plurality of targets are photographed at high speed by the contactless multi-channel camera and stored as a text file. The x-axis and y-axis data for each camera are monitored to check the state of the structure for each part, and the stored target image is reproduced at medium speed. Read the target image data stored as the text file, accumulate the recognized target movement coordinates according to time, construct a graph, and use the target coordinates for the time to perform fast Fourier transform process to measure the structure displacement. Output as input parameter data.

Description

Non-contact method for generating parameter data for measuring displacement of structure}

The present invention relates to measurement of structure displacement, and more particularly, to a method of measuring displacement of a structure, such as a bridge.

Multi-channel non-contact displacement sensor is a measurement system for examining the structural stability of facilities such as bridges and buildings. Currently, inspections and safety checks for the maintenance of bridges, tunnels, buildings, etc. are carried out regularly. Structural characteristics of the structure are generally different from those at the time of initial design, and the dynamic characteristics of the structure may change due to the stiffness deterioration due to the cracking of the member and the aging of the structure.

Observation of changes in the dynamics of the structure allows the location of damage and quantitative assessment. Dynamic instrumentation is a representative instrument used to monitor structures such as bridges, tunnels and buildings. Current measurement methods use contact sensors that connect each sensor and instrument to a 1: 1 connection, which requires a lot of cabling and installation costs for fixtures to secure the sensors, and is an ancillary method for amplifying and storing signals. Equipment is required. Therefore, the equipment used for safety diagnosis is impractical or expensive equipment, and it is not universal to be applied to structures such as bridges and tunnels. In addition, all these displacement measuring instruments rely on total imports.

Recently, there is a growing interest in the maintenance of structures such as bridges and tunnels. In particular, structural safety is required due to natural disasters and aging of structures. Degraded structures, aging structures, etc., may lead to large catastrophe due to uncertainty of safety. Therefore, it is very important to efficiently analyze and estimate the current state of the structure in order to prevent the loss of life and economic by taking measures to prevent, repair, and reinforcement.

SUMMARY OF THE INVENTION The present invention has been made to improve the above-mentioned conventional problems, and an object thereof is to provide a method for generating parameter data for measuring structure displacement using a non-contact multichannel digital camera.

The parameter data generation method for measuring displacement of a non-contact structure according to the present invention includes (i) combining a non-contact multi-channel camera and changing a setting while capturing and collecting a plurality of targets installed at predetermined intervals at a plurality of operating points of the structure at low speeds. Securing an optimal state such that the target image visible when the target image is checked by the user becomes a clear image while the process is performed; (ii) photographing the plurality of targets at high speed with the contactless multichannel camera and storing the text in a text file when the combination and recognition of the contactless multichannel camera remain optimal; (iii) monitoring x-axis and y-axis data for each camera to check the state of the structure for each part and reproducing the stored target image at medium speed; And (iv) reading the target image data stored in the text file, accumulating the recognized target movement coordinates according to time, constructing a graph, and performing data using a fast Fourier transform process using the target coordinates for the time. And outputting it as input parameter data for measuring the structure displacement.

As described above, the dynamic displacement measuring system of a structure using a non-contact multi-channel digital camera is very economical because it uses a video image of the camera, it is possible to measure the vibration and dynamic characteristics of the structure is difficult to access. More importantly, this measurement system will be helpful for the development of structural design technology by measuring the displacement of bridges and buildings through wind tunnel and vibration tests.

1 is a flowchart illustrating a method of generating parameter data for measuring a non-contact structure displacement according to an exemplary embodiment of the present invention.
FIG. 2 is a diagram illustrating a non-contact multi-channel digital camera system that may be applied to the method for generating parametric data for non-contact structure displacement measurement described in FIG. 1.
3 and 4 are diagrams illustrating target image data displayed on a screen according to an exemplary embodiment of the present invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Referring to FIG. 1, operation points and roles are assigned to six digital cameras for overall monitoring (step 1). FIG. 2 is a diagram illustrating a non-contact multi-channel digital camera system that may be applied to the method for generating parametric data for non-contact structure displacement measurement described in FIG. 1.

The plurality of targets are installed at the first target 212 installed at the center point of the left pier of the bridge, the second target 214 provided at the center point of the right pier of the bridge 200, and the center point of the bridge 200. A third target 216, a fourth target 218 installed at an pier point between the first target 212 and the third target 216, and the second target 214 and the third target ( 216 includes a fifth target 220 installed at the pier point between.

For efficient monitoring of bridges, the efficient placement of cameras on bridges consists of six units. That is, the non-contact multi-channel camera 230 includes a first camera 232 for capturing the entire bridge pier; And five second cameras 234 respectively photographing the first targets 212 to the fifth target 220.

Such a camera configuration may be regarded as an optimal configuration for increasing data reliability and preventing distortion in an image.

Next, Low-Speed Image Acquisition is a process of checking the combination and recognition of cameras for the surrounding environment and the structure after the initial target is installed. While shooting and collecting a plurality of targets installed at a low speed, a setting change process is performed to secure an optimal state such that the target image seen when the target image is confirmed by the user becomes a clear image (step 2). The optimal state is modified according to the position, focus, brightness, etc. of the target. This system is a system that measures the displacement by recognizing the change of target by loading a file after saving the high speed image. Existing products do not recognize the target properly when checking the data after measurement or because of the influence of the surroundings. If it is wrong, there is inconvenience to measure several times. It is a function to check whether the target recognizes it while collecting the image at low speed. In this part, we work to collect high quality images. The most influential one can adjust the focus by using the lens 235 of the camera, the brightness can be adjusted by using the aperture.

In this case, the six cameras 232 and 234 are photographed at a speed of 30 frames per second, and the optimal state is secured while storing the image and changing the settings. When a signal is sent from a PC (not shown) to a contactless digital camera, the camera collects the image. This video is stored inside the PC. The PC is connected to the IEEE1394B type camera and stores the image data in binary format. After reloading the image data saved in this binary type and learning the target (Image Learning), the target is recognized using the Pattern Matching function. This is expressed by the recognized X and Y coordinates and this data is saved as txt or xls (Excel) file. In this case, since the pattern matching algorithm is further added to the low speed image storage method, the speed is lower than that of the high speed image storage method. Shooting 30 frames per second can proceed quickly and easily whether the image and the target is recognized, and represents the parameters for the camera obtained in the process according to the embodiment of the present invention.

  IEEE 1394 Link to Image

  2. Camera Config & Attributes

   -Auto Exposure

   -Brightness

   -Frame Rate

   -Gain

   -Gamma

   -Sharpness

   -Shutter Speed

   -Trigger Delay

 3.Camera Image Save

After that, if the combination and recognition of the contactless multichannel camera remain optimal, Hi-Speed Image Acquisition captures the plurality of targets at high speed with the contactless multichannel camera and stores them in a memory (not shown) as a text file. (Step 3). At this time, the video is recorded at 125 frames per second to store the video. The captured video cannot be viewed at the same time, and the video is not displayed on the PC screen. The reason for shooting at high speed in step 3 is that the vibration generated by the structure is about 4 to 15 Hz. In order to measure this, vibration must be measured at least 5 times the shooting speed, and a fast Fourier transform (FFT) is possible. Therefore, the sum of the speed collected by the program and the speed at which the image is stored can be up to 125 frames. This can speed up if the computer and OS performance increase. The parameters for the camera obtained in the process of the present invention are shown in the table below.

 IEEE 1394 Link to Image

 2. Camera Config & Attributes

   -Auto Exposure

   -Brightness

   -Frame Rate

   -Gain

   -Gamma

   -Sharpness

   -Shutter Speed

   -Trigger Delay

3.Camera Image Save

4. Image Acquisition Data View

Afterwards, Image Acquisition Data View is a process of simultaneously displaying images and data photographed at high speed, and monitoring x-axis and y-axis data for each camera to check the state of the bridge 200 as the structure for each part, and storing the stored target image. Is played at medium speed, for example, at a rate of 100 frames per second (step 4).

The playback at the rate of 100 frames allows the user to check the data while checking the image at the time when the image and the data exactly match without distortion in the process of the present invention. The table below shows the parameters for the camera obtained in the process of the present invention.

 1. Specify Target and Image Learn Function

 2. Region of Interest assignment function

 3. Pattern Matching Function

 4. Image transformation coordinate function (X, Y biaxial transformation)

 5. Edge recognition function

 6. Image zoom in / out, pan and tilt, current coordinate recognition function

 7. FFT frequency conversion function

It is configured to monitor data of X axis and Y axis of each camera and to check up to 6 data at the same time. 3 and 4 are diagrams illustrating target image data displayed on a screen according to an exemplary embodiment of the present invention. In addition, six screens as shown in FIG. 3 and FIG. 4 can be viewed at the same time so that the state of the bridge can be immediately confirmed for each part.

Data Result is a function that retrieves the data stored in a text file, analyzes and reprocesses the graphs and phenomena, and stores the data by reading the target image data stored in the text file and accumulating the recognized target movement coordinates according to time. Then, the data obtained by performing the FFT process using the target coordinates for the time is output as input parameter data for measuring the structure displacement (step 5). Load the image saved at high speed and accumulate the recognized target movement coordinates according to time to express it as a graph. If the FFT is performed using the coordinates of the target for this time, the frequency band applied to the structure at that time can be identified, and the data can be used as parameter input data data in the simulation tool.

The input parameter data for measuring the displacement of the structure is input to a structural analysis simulation program and used as data to make it possible to check the state and deformation of the bridge by performing structural analysis in the program. This program uses LabVIEW to divide the CPU into up to 8 CPUs using a single PC, and stores the images of six cameras on one PC (not shown). Data measurement speed is 100 Sample / Sec and video image is composed of terabyte mass storage device (not shown) using RAID method.

 1. Image Calibration-Current image coordinates are converted to actual displacement

    Function to correct coordinates to 0 points

 2. Function to convert image to displacement of X, Y coordinate

 3. A function to recognize (learn) a target

 4. Image Pattern Matching Function

 5. FFT frequency conversion function of the measurement data over time

200: bridge 212: first target
214: second target 216: third target
218: fourth target 220: fifth target
230: non-contact multi-channel camera 232: first camera
234: second camera 235: lens

Claims (4)

(i) A plurality of targets installed at a plurality of operating points of the structure at regular intervals by combining a non-contact multi-channel camera comprising a first camera photographing to monitor the entire structure and a second camera photographing each target separately. Capturing at low speed and collecting the data to secure an optimal state such that the target image visible when the target image is confirmed by the user is a clear image while undergoing a setting change process;
(ii) photographing the plurality of targets at high speed with the contactless multichannel camera and storing the text in a text file when the combination and recognition of the contactless multichannel camera remain optimal;
(iii) monitoring x-axis and y-axis data for each camera to check the state of the structure for each part and reproducing the stored target image at medium speed; And
(iv) reading the target image data stored in the text file, accumulating the recognized target movement coordinates according to time, constructing a graph, and constructing a data structure by performing a fast Fourier transform process using the target coordinates for the time; And outputting as input parameter data for displacement measurement.
The method according to claim 1, wherein the structure is a bridge, the plurality of targets are a first target installed at the center point of the left pier of the bridge, a second target installed at the center point of the right pier of the bridge, installed in the center point of the bridge A non-contact structure displacement including a third target, a fourth target installed at a pier point between the first target and the third target, and a fifth target installed at a pier point between the second target and the third target. How to create parameter data for measurement. delete The contactless structure of claim 1, wherein at step (i) it is photographed at a rate of 30 frames per second, at step (ii) it is photographed at a rate of 125 frames per second and at step (iii) a non-contact structure is reproduced at a rate of 100 frames per second. Method of generating parametric data for displacement measurement.
KR20100078266A 2010-08-13 2010-08-13 Non-contact method for generating parameter data for measuring displacement of structure KR101174105B1 (en)

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Cited By (1)

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KR101193076B1 (en) 2011-03-08 2012-10-22 주식회사 포스코건설 System for real-time measuring penetration depth of pile using 3D photogrammetry

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KR101395544B1 (en) * 2012-08-21 2014-05-14 인하대학교 산학협력단 System and method for calibrating of object for measuring deformation structure
KR101696629B1 (en) * 2015-07-10 2017-01-17 경북대학교 산학협력단 System and method for warning collapse using monitoring of structure deformation
CN110455207B (en) * 2019-07-18 2024-04-23 浙江同禾传感技术有限公司 Online recognition device for hinge joint state of bridge beam slab and use method thereof
CN110779615A (en) * 2019-11-05 2020-02-11 四川双元智能科技有限公司 Method and device for measuring object vibration by using optical principle
CN111610519A (en) * 2020-06-11 2020-09-01 石家庄铁道大学 Non-contact type measuring method for dynamic deformation of small bridge structure
KR102408456B1 (en) * 2020-11-10 2022-06-13 (주)더길 High-angle image extensometer using color channel separation
CN112762841A (en) * 2020-12-30 2021-05-07 天津大学 Bridge dynamic displacement monitoring system and method based on multi-resolution depth features
CN115993094B (en) * 2023-03-01 2023-09-12 大连交通大学 Large membrane structure roof displacement monitoring method and system based on CCD camera

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KR100726009B1 (en) * 2006-10-13 2007-06-08 최성환 System and method for measuring displacement of structure

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KR101193076B1 (en) 2011-03-08 2012-10-22 주식회사 포스코건설 System for real-time measuring penetration depth of pile using 3D photogrammetry

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