Long-distance displacement measuring device based on crossed sine composite stripes and measuring method thereof

Abstract

The invention relates to a long-distance displacement measuring device based on crossed sine composite stripes and a measuring method thereof. The measuring device comprises a crossed sine composite stripe target, a far-focus camera and a computer, the crossed sine composite stripe target object is attached to a to-be-monitored object and is used for acquiring displacement change information of the target monitored object; the far-focus camera is used for carrying out image acquisition on the attached crossed sine composite stripes and sending the acquired image to the computer for analysis; and the computer performs post-processing on the crossed sine composite stripe image to obtain relative displacement information of the to-be-measured object. The method and device provided by the invention have the characteristics of long detection distance, high detection precision, high sampling frequency, non-contact type, strong interference resistance and the like. Therefore, the method is applied to displacement monitoring tasks of various structures with complex environments, and has a wide application prospect.

Description

Technical Field

[0001] The invention relates to the technical field of machine vision displacement measurement, in particular to a long-distance displacement measurement device based on crossed sinusoidal composite fringes and a measurement method thereof. Background Art

[0002] With the advancement of urbanization and the improvement of modern infrastructure in the world, the safety of buildings and infrastructure under construction or in existence has attracted people's attention. It is very important to monitor the deformation and displacement response of these buildings and facilities in real time.

[0003] At present, displacement measurement mostly relies on traditional measurement methods, such as trigonometric height measurement represented by total station, various contact sensors such as linear variable differential transformer, and non-contact sensor measurement methods such as laser Doppler vibrometer (LVDs). The problems with these methods are: (1) high learning cost and inability to achieve all-weather real-time monitoring and early warning. (2) limited measurement range, large restrictions on usage scenarios, and difficult later maintenance. (3) limited service life, expensive price, and easy failure under the influence of environmental factors. (4) The accuracy of most long-distance measurement methods is millimeters and above, which cannot meet the measurement needs of small displacements.

[0004] With the development of computer vision, vision-based displacement measurement has been widely studied in the field of structural health monitoring. The existing common methods are roughly divided into three types: (1) template matching method (DIC), (2) feature point monitoring, and (3) optical flow method. For computer vision, due to hardware limitations, as the distance between the object to be measured and the camera increases, the acquired image will become blurred, distorted, and the resolution will decrease. The lack of image information will cause many computer vision-based measurement methods to have errors or failures in long-distance measurements.

[0005] In summary, in view of the existing computer vision measurement methods and the problems encountered in actual shooting, what we need to solve is how to extract as much effective information as possible from a low-resolution, severely degraded image to increase the measurement accuracy. Considering the use requirements of vision in practical applications, it is necessary to propose a displacement measurement method with higher accuracy and wider application range. Summary of the invention

[0006] In view of this, the purpose of the present invention is to provide a long-distance displacement measurement device based on cross-sinusoidal composite fringes and a measurement method thereof, wherein the measurement device has the characteristics of long detection distance, high detection accuracy, high sampling frequency, non-contact, and strong anti-interference.

[0007] To achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a long-distance displacement measurement device based on crossed sinusoidal composite stripes, comprising a crossed sinusoidal composite stripe target, a telefocus camera, and a computer; the crossed sinusoidal composite stripe target is attached to the object to be monitored to obtain displacement change information of the target monitored object; the telefocus camera is used to capture images of the attached crossed sinusoidal composite stripes and send the captured images to the computer for analysis; the computer post-processes the crossed sinusoidal composite stripe images to obtain relative displacement information of the object to be measured.

[0008] The present invention also provides a cross-sinusoidal composite stripe target based on the long-distance displacement measurement device based on cross-sinusoidal composite stripes, wherein the cross-sinusoidal composite stripe target is composed of two groups of sinusoidal stripes with completely consistent amplitude frequencies and a relative angle of 90°; wherein the edge area of ​​the cross-sinusoidal composite stripe target is 4 gray blocks and a single sinusoidal stripe pattern, and the middle is an oblique sinusoidal stripe pattern composed of cross-edge sinusoidal stripes.

[0009] The present invention also provides a long-distance displacement measurement method based on crossed sinusoidal composite fringes based on the long-distance displacement measurement device based on crossed sinusoidal composite fringes, comprising the following steps:

[0010] Step S1: designing a new artificial target based on cross-sinusoidal composite stripes to collect the position information of the object being measured;

[0011] Step S2: attaching a cross-sine composite fringe pattern to the object to be tested; placing a telephoto camera at a suitable position, setting reasonable parameters such as focal length and aperture, and ensuring clear camera imaging;

[0012] Step S3: When the object to be measured moves in the plane, the relative position of the fringe pattern attached to the object to be measured on the imaging sensor of the acquisition camera also changes accordingly; the camera position is kept unchanged, and a fringe image with position information is acquired through camera acquisition;

[0013] Step S4: The collected fringe signal is transmitted to a computer, and the computer pre-processes the fringe signal and extracts the displacement information of the object to be measured.

[0014] In a preferred embodiment, the step S4 specifically includes the following steps:

[0015] Step S41: pre-processing the acquired fringe image, including noise reduction, sharpening, and contrast enhancement methods, to facilitate subsequent processing;

[0016] Step S42: taking any row of the single sinusoidal region of the stripes as a reference, calculating the Pearson correlation coefficients of the other rows row by row, and obtaining the Pearson correlation coefficient curves of the stripes on the X-axis and the Y-axis;

[0017] Step S43: By cross-correlating the correlation coefficient curves before and after the displacement, the relative displacement information of the object to be measured in the before and after captured images is obtained through the index of the maximum cross-correlation value.

[0018] In a preferred embodiment, the step S42 is specifically as follows:

[0019] The single sinusoidal stripe area around the stripe pattern is selected as the reference line. After calculating the Pearson correlation coefficient to remove the curve, the curve is Fourier transformed, and the correlation coefficient curve is upsampled by zero padding in the frequency domain. Then, the time domain information is returned by inverse Fourier transform to increase the pixel resolution of the displacement. The Pearson correlation coefficient calculation formula is as follows:

[0020]

[0021] where ρ X,Y is the correlation coefficient PCC; coν(X,Y) is the covariance of X and Y; σ X is the standard deviation of X; σ Y is the standard deviation of Y; i and Y i is the value of the ith data point; and are the means of X and Y respectively.

[0022] In a preferred embodiment, the step S43 is specifically as follows:

[0023] By cross-correlating the correlation coefficient curves before and after the displacement, the relative displacement information of the object to be measured in the before and after collected images is obtained through the maximum cross-correlation value index; the Pearson correlation coefficient curve before the displacement is selected, and the autocorrelation operation is performed to obtain the maximum correlation value index; the Pearson correlation coefficient curves of the images before and after the displacement are selected, and the cross-correlation calculation is performed to obtain the maximum correlation value index; the two are subtracted to obtain the displacement distance of the object to be measured on the imaging sensor in pixels; after correcting the displacement value through the energy center of gravity method, the real displacement distance of the object to be measured is obtained through the proportional factor; the formula for calculating the cross-correlation coefficient is as follows:

[0024]

[0025] Where x[n] is the value of the reference frame signal x at time point n; y[n+k] is the value of the displacement frame signal y at time point n+k; k is the displacement value, which can be positive, negative or zero; R xy[k] is the cross-correlation value of signal x and signal y at time lag k.

[0026] Compared with the prior art, the present invention has the following beneficial effects: the present invention provides a long-distance displacement measurement device and method based on crossed sinusoidal composite stripes, by attaching crossed sinusoidal composite stripes to the object to be measured, collecting the motion image of the object to be measured by a telephoto camera, and finally analyzing and processing the stripe image by a computer to obtain the two-dimensional displacement of the object to be measured. Compared with the existing algorithms, the calculation method has small calculation amount, simple device, strong anti-interference ability, wide working range, high precision, strong practicality and broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic diagram of the structure of the measuring device of an embodiment of the present invention. A three-dimensional coordinate is established at the center point of the cross-sinusoidal composite fringe pattern, the camera optical axis perpendicular to the camera imaging surface is defined as the Z axis, the horizontal direction perpendicular to the imaging optical axis is defined as the X axis, and the vertical direction perpendicular to the imaging optical axis is defined as the Y axis.

[0028] Figure 2 and Figure 3 Schematic diagram of the implementation process of stripe preprocessing in an embodiment of the present invention.

[0029] Figures 4 to 7 It is a schematic diagram of measurement results in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0031] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0032] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations.

[0033] like Figure 1As shown, this embodiment provides a vision-based long-distance displacement measurement device based on crossed sinusoidal composite stripes, including a crossed sinusoidal composite stripe target, a telephoto camera, and a computer; the crossed sinusoidal composite stripe target is attached to the object to be monitored to obtain displacement change information of the target monitored object; the telephoto camera is used to capture images of the attached crossed sinusoidal composite stripes, and send the captured images to the computer for analysis; the computer post-processes the crossed sinusoidal composite stripe images to obtain relative displacement information of the object to be measured.

[0034] In this embodiment, the image processing is realized by a computer, and the computer is pre-installed with a stripe information processing program. The camera is connected to the computer via a data cable, so that real-time monitoring of the unique stripe information can be realized.

[0035] The present embodiment provides a design method for a cross-sine target based on the above-mentioned device, which is characterized in that: the target is composed of two groups of sinusoidal stripes with completely consistent amplitude frequencies and a relative angle of 90°. Among them, the edge area of ​​the artificial target is 4 gray blocks and a single sinusoidal stripe pattern, and the middle is an oblique sinusoidal stripe pattern composed of cross-edge sinusoidal stripes. After the proposed stripe-based artificial target is decoded by the measurement method proposed in the present invention, it has better noise resistance and accuracy in long-distance displacement measurement work than the same type of artificial targets; it can achieve micron-level displacement measurement under long-distance monitoring. In addition, the stripe-based artificial target proposed in the present invention has good scalability. According to different application scenarios, the target in this article can achieve micron-level displacement measurement under long-distance monitoring through various signal processing methods such as filtering and windowing.

[0036] This embodiment also provides a long-distance displacement and displacement measurement method based on the above-mentioned device based on cross-sinusoidal composite fringes, comprising the following steps:

[0037] Step S1: Attach the cross-sine composite fringe pattern to the object to be measured; place the telephoto camera in a suitable position, set reasonable parameters such as focal length and aperture, and ensure that the camera image is clear. Figure 1 , establish a three-dimensional coordinate at the center point of the cross-sinusoidal composite fringe pattern, take the camera optical axis perpendicular to the camera imaging surface as the Z axis, the horizontal direction perpendicular to the imaging optical axis as the X axis, and the vertical direction perpendicular to the imaging optical axis as the Y axis.

[0038] Step S2: When the object to be measured moves in the plane, the relative position of the fringe pattern attached to the object to be measured on the imaging sensor of the acquisition camera also changes. The camera position remains unchanged, and the fringe image with position information is acquired through camera acquisition.

[0039] Step S3: The collected fringe signal is transmitted to a computer, and the computer pre-processes the fringe signal and extracts the displacement information of the object to be measured.

[0040] In this embodiment, step S3 specifically includes the following steps:

[0041] Step S31: pre-processing the acquired fringe image, including noise reduction, sharpening, contrast enhancement and other methods, to facilitate subsequent processing;

[0042] Step S32: Select the single sinusoidal stripe area around the stripe pattern as a reference line and calculate the Pearson correlation coefficient curve. After the Pearson curve is Fourier transformed, the correlation coefficient curve is upsampled by zero padding in the frequency domain, and then the time domain information is returned by inverse Fourier transform to increase the pixel resolution of the displacement and improve the pixel resolution. The Pearson correlation coefficient calculation formula is as follows:

[0043]

[0044] where ρ X,Y is the correlation coefficient PCC; coν(X,Y) is the covariance of X and Y. σ X is the standard deviation of X. Y is the standard deviation of Y. i and Y i is the value of the ith data point. and are the means of X and Y respectively.

[0045] Step S33: By cross-correlating the correlation coefficient curves before and after the displacement, the relative displacement information of the object to be measured in the before and after collected images is obtained through the maximum cross-correlation value index. Select the Pearson correlation coefficient curve before the displacement, perform autocorrelation operation, and obtain the maximum correlation value index; select the Pearson correlation coefficient curves of the images before and after the displacement, perform cross-correlation calculation, and obtain the maximum correlation value index; subtract the two to obtain the displacement distance of the object to be measured on the imaging sensor in pixels. After correcting the displacement value by the energy center of gravity method, the actual displacement distance of the object to be measured is obtained by the proportional factor. The formula for calculating the cross-correlation coefficient is as follows:

[0046]

[0047] Where x[n] is the value of the reference frame signal x at time point n. y[n+k] is the value of the displacement frame signal y at time point n+k. k is the displacement value, which can be positive, negative or zero. xy[k] is the cross-correlation value of signal x and signal y at time lag k.

[0048] Figure 2 and Figure 3 It is a schematic diagram of the system principle of the present invention. Figure 2 (a) is a schematic diagram of the cross-sinusoidal composite fringes used in this method; Figure 2 (b) is the gray value of a single-sided stripe, which is a combination of the sinusoidal curves between the two straight lines. Figure 2 (c) is a schematic diagram of the Pearson correlation coefficient calculation curve for the stripe image row by row along the Y axis; Figure 3 It is the correlation coefficient curve before and after displacement.

[0049] Figure 3 and Figure 4 This is the experimental result obtained by the displacement measurement experiment of this embodiment. In the experiment, an industrial camera (PointGray, maximum frame rate 165frame / s) with a resolution of 1920×1200 pixels is used to capture the image of the composite stripes, and a telephoto lens (JARAY, focal length 420mm~800mm F8.3) is used for imaging. The displacement platform used is THORLAB: MTS25 / M-Z8. The composite stripe image is attached to a one-dimensional displacement platform, and a known displacement is generated by the displacement platform to simulate the movement of the object under test. In order to verify the performance of this algorithm and measurement system for displacement measurement at different distances, the displacement platform with a stripe pattern is placed at a distance of 20m and 50m from the imaging camera for experiments.

[0050] Before performing displacement measurement, the camera should be calibrated. After setting up the measurement system, set the displacement platform for continuous movement. Set the displacement platform to perform continuous step-down movement, with single-step descent distances of 1mm, 0.1mm, 50μm, 25μm and 10μm, and a total of 5 settlements were collected in one group. A telephoto camera was used to capture the movement, and the displacement result graph obtained by the test is shown in the figure. It can be seen from the experimental results that when the test distance is 20m, the method in this paper has a good measurement effect for step displacements of 1mm, 0.1mm, and 50μm. There is obvious noise when measuring the 10μm step displacement, but the displacement curve can still be clearly distinguished. When the test distance is 50m, the method in this paper can still measure a single 25μm displacement.

[0051] Figure 5 This is the experimental result obtained by the vibration measurement experiment of this embodiment. The algorithm in this paper has the function of vibration analysis and is suitable for vibration monitoring of various types of buildings. The displacement platform is replaced with an exciter, which outputs vibrations with an amplitude of 0.5mm and frequencies of 1Hz and 10Hz respectively. The system performance is verified by comparing it with an eddy current displacement sensor (ECDS). It can be seen from the experimental results that the amplitude and frequency of the vibration generated by the exciter are accurately recorded. Figure 6 These are the 1Hz and 10Hz vibration curves and spectra at a measurement distance of 20m. Figure 7 These are the 1Hz and 10Hz vibration curves and spectra at a measurement distance of 50m.

[0052] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A long-distance displacement measurement device based on cross-sinusoidal composite fringes, characterized in that: The invention comprises a cross-sinusoidal composite fringe target, a telefocus camera and a computer; the cross-sinusoidal composite fringe target is attached to the object to be monitored and used to obtain displacement change information of the target monitored object; the telefocus camera is used to collect images of the attached cross-sinusoidal composite fringe and send the collected images to the computer for analysis; the computer performs post-processing on the cross-sinusoidal composite fringe images to obtain relative displacement information of the object to be measured.

2. A cross-sinusoidal composite fringe target for a long-distance displacement measurement device based on cross-sinusoidal composite fringe according to claim 1, characterized in that: The cross-sinusoidal composite stripe target is composed of two groups of sinusoidal stripes with completely consistent amplitude frequencies and a relative angle of 90°; wherein, the edge area of ​​the cross-sinusoidal composite stripe target is 4 gray blocks and a single sinusoidal stripe pattern, and the middle is an oblique sinusoidal stripe pattern composed of cross-edge sinusoidal stripes.

3. A long-distance displacement measurement method based on crossed sinusoidal composite fringes based on the long-distance displacement measurement device based on crossed sinusoidal composite fringes according to claim 1, characterized in that: The following steps are involved: Step S1: designing a new artificial target based on cross-sinusoidal composite stripes to collect the position information of the object being measured; Step S2: attaching a cross-sine composite fringe pattern to the object to be tested; placing a telephoto camera at a suitable position, setting reasonable parameters such as focal length and aperture, and ensuring clear camera imaging; Step S3: When the object to be measured moves in the plane, the relative position of the fringe pattern attached to the object to be measured on the imaging sensor of the acquisition camera also changes accordingly; the camera position is kept unchanged, and a fringe image with position information is acquired through camera acquisition; Step S4: The collected fringe signal is transmitted to a computer, and the computer pre-processes the fringe signal and extracts the displacement information of the object to be measured.

4. The long-distance displacement measurement method based on cross-sinusoidal composite fringes according to claim 3 is characterized in that: The step S4 specifically comprises the following steps: Step S41: pre-processing the acquired fringe image, including noise reduction, sharpening, and contrast enhancement methods, to facilitate subsequent processing; Step S42: taking any row of the single sinusoidal region of the stripes as a reference, calculating the Pearson correlation coefficients of the other rows row by row, and obtaining the Pearson correlation coefficient curves of the stripes on the X-axis and the Y-axis; Step S43: By cross-correlating the correlation coefficient curves before and after the displacement, the relative displacement information of the object to be measured in the before and after captured images is obtained through the index of the maximum cross-correlation value.

5. The long-distance displacement measurement method based on cross-sinusoidal composite fringes according to claim 4 is characterized in that: The step S42 is specifically as follows: The single sinusoidal stripe area around the stripe pattern is selected as the reference line. After calculating the Pearson correlation coefficient to remove the curve, the curve is Fourier transformed, and the correlation coefficient curve is upsampled by zero padding in the frequency domain. Then, the time domain information is returned by inverse Fourier transform to increase the pixel resolution of the displacement. The Pearson correlation coefficient calculation formula is as follows: where ρ X,Y is the correlation coefficient PCC; coν(X,Y) is the covariance of X and Y; σ X is the standard deviation of X; σ Y is the standard deviation of Y; i and Y i is the value of the ith data point; and are the means of X and Y respectively.

6. The long-distance displacement measurement method based on cross-sinusoidal composite fringes according to claim 4 is characterized in that: The step S43 is specifically as follows: By cross-correlating the correlation coefficient curves before and after the displacement, the relative displacement information of the object to be measured in the before and after collected images is obtained through the maximum cross-correlation value index; the Pearson correlation coefficient curve before the displacement is selected, and the autocorrelation operation is performed to obtain the maximum correlation value index; the Pearson correlation coefficient curves of the images before and after the displacement are selected, and the cross-correlation calculation is performed to obtain the maximum correlation value index; Subtract the two to obtain the displacement distance of the object to be measured on the imaging sensor in pixels; after correcting the displacement value by the energy center of gravity method, the actual displacement distance of the object to be measured is obtained by the proportional factor; the calculation formula of the mutual correlation coefficient is as follows: Where x[n] is the value of the reference frame signal x at time point n; y[n+k] is the value of the displacement frame signal y at time point n+k; k is the displacement value, which can be positive, negative or zero; R xy[k] is the cross-correlation value of signal x and signal y at time lag k.

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