Device and method for detecting out-of-roundness and voidage of main cable of suspension bridge

Abstract

The invention belongs to the technical field of suspension bridge main cable detection, and particularly relates to a suspension bridge main cable out-of-roundness and void ratio detection device and method. Comprising an outer support, a balance beam is arranged at the top of the outer support, walking mechanisms are arranged on the two sides of the balance beam, a circular through hole is formed in the middle of the outer support, a high-definition camera and a laser transmitter are arranged on the two sides of the top of the inner wall of the circular through hole respectively, and an adjusting mechanism is connected between the high-definition camera and the laser transmitter and comprises a driver. The two sides of the driver are connected with limiters respectively, and the limiters are connected with the high-definition camera and the laser transmitter. According to the invention, contour collection is carried out on a tightened main cable through a laser transmitter and a high-definition camera, then collected laser contour lines are combined, out-of-roundness detection is carried out, finally, collected images are subjected to an image recognition technology to obtain front views of the images, the front views are combined again, and the porosity after cable tightening is solved. The cable tightening effect can be detected quickly, efficiently and precisely.

Description

Technical Field

[0001] The invention belongs to the technical field of main cable detection of suspension bridges, and in particular relates to a device and method for detecting out-of-roundness and void ratio of a main cable of a suspension bridge. Background Art

[0002] Suspension bridges are widely praised in large-span and super-large-span bridges for their large span capacity, reasonable force, best use of material strength, beautiful overall shape, and safe and fast construction. Suspension bridges are bridges with tensioned main cables as the main load-bearing components. The main cable is composed of several strands, which are tied with fixed binding tape to form a regular hexagonal cross-section, with hot-cast anchor heads at both ends. Due to the gaps between and inside the strands, the outer diameter of the main cable is much larger than the diameter required by the design. In order to smoothly carry out the cable clamp installation and wire winding operations in the next step, the main cable must be tightened so that the void ratio inside the main cable meets the design standard requirements.

[0003] Cable tightening is divided into two steps: pre-tightening and formal tightening. Pre-tightening adopts the method of manual tightening, which is carried out during the night when the temperature is stable. The main cable shape retainer should be removed before construction. That is, several strands of the main cable are manually bundled and tightened to minimize the space between the strands, so that the cross-section of the main cable is close to a circle, so that it can better bear the weight. Before the formal cable tightening construction, the main cable rebound rate test is carried out on the main cable to determine the void ratio of the cable tightening state and the void ratio of the tightening steel belt after leaving the cable tightening machine within about 5m. The rebound rate of the main cable is obtained by comparing the void ratio difference. The tightening force and diameter are adjusted according to the rebound rate. During the formal cable tightening process, check and adjust the tightening force to ensure the quality of the main cable tightening. The tightening interval is tightened once every 1.0m. When the cable tightening machine is tightened to the position of the steel belt tied by the pre-tightening cable, the steel belt should be removed or re-tightened to avoid affecting the tightening effect. In order to ensure that the main cable tightening effect meets the standard, it is necessary to effectively control and detect the porosity and out-of-roundness of the main cable. At present, the main cable porosity and out-of-roundness measurement methods are mainly based on manual measurement. The measurement technicians use special measuring tools to measure the main cable diameter. The main cable cross-sectional area calculation method only calculates the values ​​of the transverse and longitudinal diameters, which cannot reflect the shape of the entire cross section, that is, it cannot fully reflect the out-of-roundness of the main cable. In addition, this method is affected by various factors such as the technical level of the personnel and the measurement angle, and the measurement results are prone to errors. Some people have also proposed a method of measuring the main cable diameter using a laser measurement mechanism, but this method requires two sets of laser transmitters and receivers to work at the same time, and the measurement angle is only perpendicular to the radial direction of the main cable. The measurement result is accurate. The measurement location is mainly carried out in the air. It is difficult to ensure that the laser measurement angle is always perpendicular to the radial direction of the main cable, and the arrangement and distribution of the diameters measured at all rotation angles for out-of-roundness evaluation is relatively complicated and time-consuming. Summary of the invention

[0004] In view of the above problems, the purpose of the present invention is to provide a device and method for detecting the out-of-roundness and void ratio of the main cable of a suspension bridge. The detection device uses a laser transmitter and a high-definition camera to collect the contour of the main cable after cable tightening, then combines the collected laser contour lines, and performs out-of-roundness detection. Finally, the collected image is processed through image recognition technology to obtain its front view and recombine it. The calculated diameter of the main cable is calculated by the standard circle circumference formula, and the void ratio after cable tightening is solved according to the main cable void ratio calculation formula. The cable tightening effect can be detected quickly, efficiently and accurately. While ensuring the detection accuracy, it replaces the workers' physical labor and effectively avoids the personal safety risks brought by personnel working at high altitudes.

[0005] The technical solution of the present invention is: a device for detecting the out-of-roundness and void ratio of the main cable of a suspension bridge, comprising an outer bracket, a balance beam is provided on the top of the outer bracket, walking mechanisms are provided on both sides of the balance beam, a circular through hole is provided in the middle of the outer bracket, a high-definition camera and a laser emitter are provided on both sides of the top of the inner wall of the circular through hole, an adjustment mechanism is connected between the high-definition camera and the laser emitter, the adjustment mechanism comprises a driver, limiters are connected on both sides of the driver, and the limiters are connected to the high-definition camera and the laser emitter.

[0006] The walking mechanism comprises a beam frame and a roller, wherein the beam frame is fixedly connected to the balance beam, and the roller is concave in shape and matches the outer diameter of the main cable to be detected below.

[0007] The axis where the laser transmitter transmitting probe is located is arranged perpendicular to the main cable to be detected, and the lens of the high-definition camera is directed toward the position where the laser emitted by the laser transmitter contacts the main cable to be detected.

[0008] A method for detecting the out-of-roundness and void ratio of a main cable of a suspension bridge, using the above-mentioned device for detecting the out-of-roundness and void ratio of a main cable of a suspension bridge, comprises the following steps:

[0009] S1: Pass the main cable to be inspected through the circular through hole in the middle of the outer bracket, adjust the position of the high-definition camera and the laser transmitter, and start the walking mechanism to move to the target position to be inspected;

[0010] S2: The laser transmitter emits vertical laser to the main cable, forming a single laser contour line on the surface of the main cable, and the high-definition camera collects images of the single laser contour line on the surface of the main cable;

[0011] S3: Control the high-definition camera and the laser transmitter to rotate counterclockwise in the direction of travel for one circle, repeat step S2, collect the laser contour line image of the main cable surface, and combine the single laser contour line image into a closed shape after processing, forming a circle drawn based on the closed shape;

[0012] S4: The degree of overlap between the outer diameter circle of the main cable and the circle drawn based on the closed shape is tested, and the void ratio is obtained at the same time. If the overlap is greater than 99%, the main cable has excellent roundness; if the overlap is greater than 95% and less than 99%, the main cable has good roundness; if the overlap is less than 95%, the main cable does not meet the roundness standard.

[0013] In step S3, the single laser contour line images are processed and combined into a closed shape to form a circle drawn based on the closed shape. The specific process is as follows:

[0014] S31: Through the observation angle of the single laser contour line by the high-definition camera, the images of all single laser contour lines are affine transformed to obtain the front view of the laser contour line. The affine transformation is as follows:

[0015]

[0016] In the formula, (t x ,t y ) represents the translation amount, parameter a i is the image rotation and scaling change, i = 1, 2, 3, 4, (x, y) is the coordinate before transformation, (x', y') is the coordinate after transformation;

[0017] S32: Combining the single laser contour lines after affine transformation, preprocessing the combined image, the preprocessing includes graying the image, adaptive median filtering and image binarization, performing contour edge detection on the preprocessed image, measuring the image length after contour edge detection, and obtaining the perimeter of the closed figure.

[0018] The process of graying the combined image in step S32 is as follows: weighted averaging is performed on the three components R, G, and B of the single laser contour line image with different weights, wherein the weight coefficients of R, G, and B are selected as 0.3, 0.59, and 0.11, respectively, to gray the image. The specific formula is as follows:

[0019] g(i,j)=0.3R(i,j)+0.59G(i,j)+0.11B(i,j) (2)

[0020] Where R(i,j) represents the grayscale value of the red channel at (i,j), G(i,j) represents the grayscale value of the green channel at (i,j), B(i,j) represents the grayscale value of the blue channel at (i,j), and g(i,j) is the grayscale value of the grayscale image, which is the weighted average of the brightness of the three channels, and the weighting coefficient is determined by the sensitivity of the human eye to the three colors.

[0021] In step S32, the combined image is pre-processed by adaptive median filtering, and the maximum value W of the f(i, j) filter window is set.max and the minimum value W min ,h max 、h med and h min They are the maximum, median and minimum grayscale values ​​of all pixels in the filter window W(i,j), respectively. The specific process is:

[0022] The first step is to set W(i,j)=W min , when A1>0 and A2<0, go to the second step, otherwise, expand the size of the filter window W(i,j) and repeat the first step until W(i,j)>W max ,h med Output as output value;

[0023]

[0024] In the formula, h max 、h med and h min They are the maximum, median and minimum grayscale values ​​of all pixels in the filter window W(i,j);

[0025] Step 2: When B1>0 and B2<0, output f(i,j); otherwise, output h med ;

[0026]

[0027] In the formula, h(i,j) represents the grayscale value of the pixel in the jth row and the ith column in the image, and h max and h min are the maximum and minimum grayscale values ​​of all pixels in the filter window W(i,j) respectively.

[0028] In step S32, the combined image is preprocessed by using the average value method, and the specific process is: the combined image is averaged by the global threshold, and the average value k is set as the threshold, and the binarization is performed. The value greater than the threshold is set to 255, and the value less than the threshold is set to 0. The average value k is as follows:

[0029]

[0030] In the formula, i represents the gray value, p i is the probability of the pixel with gray value i appearing.

[0031] In step S32, the combined image is subjected to contour edge detection using the Canny detection algorithm, and the specific process is as follows:

[0032] In the first step, a Gaussian filter is used to smooth the combined image;

[0033] Use the Gaussian filter G(x,y) to perform a convolution operation on the combined image f(x,y) to form a smoothed image f s (x,y), the Gaussian filter convolution operation is as follows:

[0034]

[0035] f s (x,y)=G(x,y)·f(x,y) (7)

[0036] Where · is the convolution symbol, G(x,y) is the Gaussian filter, f(x,y) is the combined image, and f s (x,y) is the smoothed image;

[0037] The second step is to calculate the gradient magnitude and angle

[0038] The finite difference of the first-order partial derivative is used to calculate the gradient amplitude and angle of each pixel, and the image f is calculated using formulas (8) and (9). s (x, y) is convolved to obtain the gradient value G in the x, y direction x ,G y , as shown in formulas (10) and (11):

[0039]

[0040] G x =S x ·f s (x,y) (10)

[0041] G y =S y ·f s (x,y) (11)

[0042] In the formula, S x , S y is the convolution kernel, G x ,G y is the gradient value in the x and y directions;

[0043] The gradient value and angle are calculated as shown in formulas (12) and (13);

[0044]

[0045] In the formula, G is the calculated gradient value, and θ is the angle;

[0046] The third step is non-maximum suppression;

[0047] In the Canny detection algorithm, non-maximum suppression is performed on the amplitude along the gradient direction, that is, non-maximum suppression is performed along the four gradient directions of 0°, 45°, 90°, and 135°.

[0048] Step 4: Double threshold algorithm detection and edge connection;

[0049] After the image is non-maximum suppressed, many discrete points are displayed on the image, the edge points are connected, and the noise points are removed. When the gradient value of the edge pixel is higher than the high threshold, it is marked as a strong edge pixel and its pixel value is set to 255; when the gradient value of the edge pixel is less than the high threshold and greater than the low threshold, it is marked as a weak edge pixel and the pixel value remains unchanged; when the gradient value of the edge pixel is less than the low threshold, the pixel point will be suppressed and the pixel value of the pixel point will be set to 0.

[0050] The process of determining the porosity in step S4 is as follows: Since the measured closed image is approximately a standard circle and the circumference is known, the diameter can be obtained by the circumference formula, as shown in the following formula:

[0051]

[0052] In the formula, C is the circumference, π is the pi, and D is the calculated diameter of the main cable;

[0053] The main cable void ratio is solved as follows:

[0054]

[0055] Where K is the porosity of the main cable, n is the total number of steel wires, d is the diameter of the steel wires, and D is the diameter of the main cable after tightening.

[0056] The technical effects of the present invention are: 1. The detection device of the present invention collects the image of the main cable through a high-definition camera and a laser transmitter, obtains the front view of the laser contour line through a radial transformation method, combines the laser contour lines after affine transformation, and measures its length through image preprocessing such as graphic grayscale, adaptive median filtering and image binarization, and quickly calculates the main cable void ratio through the void ratio solution formula; 2. The present invention uses the method of drawing a standard circle to compare the laser contour line to efficiently detect the out-of-roundness after cable tightening and make an effect evaluation, and can quickly, efficiently and accurately detect the cable tightening effect; 3. Compared with the manual detection method, the present invention has the characteristics of high efficiency, high quality and high precision. While ensuring the detection accuracy, it replaces the physical labor of workers and effectively avoids the personal safety risks brought by personnel working at high altitudes.

[0057] The following is a further description with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1The present invention is a schematic structural diagram of a device for detecting out-of-roundness and void ratio of a main cable of a suspension bridge according to an embodiment of the present invention.

[0059] Figure 2 It is a schematic structural diagram of the walking mechanism of an embodiment of the present invention.

[0060] Figure 3 This is a schematic diagram of the positions of a high-definition camera and a laser transmitter according to an embodiment of the present invention.

[0061] Figure 4 This is a schematic diagram of single laser contour line acquisition according to an embodiment of the present invention.

[0062] Figure 5 The figure is a flow chart of main cable out-of-roundness detection according to an embodiment of the present invention.

[0063] Figure 6 This is a flow chart of laser contour measurement according to an embodiment of the present invention.

[0064] Figure numerals: 1-main cable, 2-balance beam, 3-travel mechanism, 4-external bracket, 5-high-definition camera, 6-laser transmitter, 7-limiter, 8-driver, 9-single laser contour line, 10-circle drawn based on the closed shape, 21-roller, 22-beam frame. DETAILED DESCRIPTION

[0065] Example 1

[0066] like Figure 1 to Figure 4 As shown, a device for detecting the out-of-roundness and void ratio of the main cable of a suspension bridge comprises an outer bracket 4, a balance beam 2 is arranged on the top of the outer bracket 4, walking mechanisms 3 are arranged on both sides of the balance beam 2, a circular through hole is formed in the middle of the outer bracket 4, a high-definition camera 5 and a laser emitter 6 are respectively arranged on both sides of the top of the inner wall of the circular through hole, an adjustment mechanism is connected between the high-definition camera 5 and the laser emitter 6, the adjustment mechanism comprises a driver 8, limiters 7 are respectively connected on both sides of the driver 8, and the limiters 7 are connected to the high-definition camera 5 and the laser emitter 6.

[0067] The walking mechanism 3 includes a beam frame 22 and a roller 21. The beam frame 22 is fixedly connected to the balance beam 2. The roller 21 is concave in shape and matches the outer diameter of the main cable 1 to be detected below.

[0068] The axis of the laser transmitter 6 where the transmitting probe is located is arranged perpendicular to the main cable 1 to be detected, and the lens of the high-definition camera 5 is directed toward the position where the laser emitted by the laser transmitter 6 contacts the main cable 1 to be detected.

[0069] The detection device of the present invention collects the main cable image through a high-definition camera and a laser transmitter, obtains the front view of the laser contour line through a radial transformation method, combines the laser contour lines after affine transformation, and measures their lengths through image preprocessing such as graphic grayscale, adaptive median filtering and image binarization, and quickly calculates the main cable void ratio through the void ratio solution formula.

[0070] A method for detecting the out-of-roundness and void ratio of a main cable of a suspension bridge, using the above-mentioned device for detecting the out-of-roundness and void ratio of a main cable of a suspension bridge, comprises the following steps:

[0071] S1: Pass the main cable 1 to be detected through the circular through hole in the middle of the outer bracket 4, adjust the positions of the high-definition camera 5 and the laser transmitter 6, and start the walking mechanism 3 to move to the target position to be detected;

[0072] S2: The laser transmitter 6 transmits vertical laser to the main cable 1, forming a single laser contour line 9 on the surface of the main cable 1, and the high-definition camera 5 collects images of the single laser contour line 9 on the surface of the main cable 1;

[0073] S3: Control the high-definition camera 5 and the laser transmitter 6 to rotate counterclockwise in the direction of travel for one circle, repeat step S2, collect the laser contour line image of the main cable surface, and combine the single laser contour line 9 image into a closed shape after processing, forming a circle 10 drawn based on the closed shape;

[0074] S4: The degree of overlap between the outer diameter circle of the main cable 1 and the circle 10 drawn based on the closed shape is detected, and the void ratio is obtained at the same time. If the overlap is greater than 99%, the main cable has excellent roundness; if the overlap is greater than 95% and less than 99%, the main cable has good roundness; if the overlap is less than 95%, the main cable does not meet the roundness standard.

[0075] In step S3, the single laser contour lines 9 are processed and combined into a closed shape to form a circle 10 drawn based on the closed shape. The specific process is as follows:

[0076] S31: Through the observation angle of the high-definition camera 5 on the single laser contour line 9, the images of all single laser contour lines 9 are affine transformed to obtain the front view of the laser contour line. The affine transformation is as follows:

[0077]

[0078] In the formula, (t x ,t y ) represents the translation amount, parameter a i is the image rotation and scaling change, i = 1, 2, 3, 4, (x, y) is the coordinate before transformation, (x', y') is the coordinate after transformation;

[0079] S32: Combine the single laser contour lines 9 after affine transformation, preprocess the combined image, the preprocessing includes graphic grayscale, adaptive median filtering and image binarization, perform contour edge detection on the preprocessed image, measure the image length after contour edge detection, and obtain the perimeter of the closed figure.

[0080] The process of graying the combined image in step S32 is as follows: weighted averaging is performed on the three components R, G, and B of the single laser contour line 9 image with different weights, wherein the weight coefficients of R, G, and B are selected as 0.3, 0.59, and 0.11, respectively, to gray the image. The specific formula is as follows:

[0081] g(i,j)=0.3R(i,j)+0.59G(i,j)+0.11B(i,j) (2)

[0082] Where R(i,j) represents the grayscale value of the red channel at (i,j), G(i,j) represents the grayscale value of the green channel at (i,j), B(i,j) represents the grayscale value of the blue channel at (i,j), and g(i,j) is the grayscale value of the grayscale image, which is the weighted average of the brightness of the three channels, and the weighting coefficient is determined by the sensitivity of the human eye to the three colors.

[0083] In step S32, the combined image is pre-processed by adaptive median filtering, and the maximum value W of the f(i, j) filter window is set. max and the minimum value W min ,h max 、h med and h min They are the maximum, median and minimum grayscale values ​​of all pixels in the filter window W(i,j), respectively. The specific process is:

[0084] The first step is to set W(i,j)=W min , when A1>0 and A2<0, go to the second step, otherwise, expand the size of the filter window W(i,j) and repeat the first step until W(i,j)>W max ,h med Output as output value;

[0085]

[0086] In the formula, h max 、h med and h min They are the maximum, median and minimum grayscale values ​​of all pixels in the filter window W(i,j);

[0087] Step 2: When B1>0 and B2<0, output f(i,j); otherwise, output hmed ;

[0088]

[0089] In the formula, h(i,j) represents the grayscale value of the pixel in the jth row and the ith column in the image, and h max and h min are the maximum and minimum grayscale values ​​of all pixels in the filter window W(i,j) respectively.

[0090] In step S32, the combined image is preprocessed by using the average value method, and the specific process is: the combined image is averaged by the global threshold, and the average value k is set as the threshold, and the binarization is performed. The value greater than the threshold is set to 255, and the value less than the threshold is set to 0. The average value k is as follows:

[0091]

[0092] In the formula, i represents the gray value, p i is the probability of the pixel with gray value i appearing.

[0093] In step S32, the combined image is subjected to contour edge detection using the Canny detection algorithm, and the specific process is as follows:

[0094] In the first step, a Gaussian filter is used to smooth the combined image;

[0095] Use the Gaussian filter G(x,y) to perform a convolution operation on the combined image f(x,y) to form a smoothed image f s (x,y), the Gaussian filter convolution operation is as follows:

[0096]

[0097] f s (x,y)=G(x,y)·f(x,y) (7)

[0098] Where · is the convolution symbol, G(x,y) is the Gaussian filter, f(x,y) is the combined image, and f s (x,y) is the smoothed image;

[0099] The second step is to calculate the gradient magnitude and angle

[0100] The finite difference of the first-order partial derivative is used to calculate the gradient amplitude and angle of each pixel, and the image f is calculated using formulas (8) and (9). s (x, y) is convolved to obtain the gradient value G in the x, y direction x ,G y , as shown in formulas (10) and (11):

[0101]

[0102] G x =S x ·f s (x,y) (10)

[0103] G y =S y ·f s (x,y) (11)

[0104] In the formula, S x , S y is the convolution kernel, G x ,G y is the gradient value in the x and y directions;

[0105] The gradient value and angle are calculated as shown in formulas (12) and (13);

[0106]

[0107] In the formula, G is the calculated gradient value, and θ is the angle;

[0108] The third step is non-maximum suppression;

[0109] In the Canny detection algorithm, non-maximum suppression is performed on the amplitude along the gradient direction, that is, non-maximum suppression is performed along the four gradient directions of 0°, 45°, 90°, and 135°.

[0110] Step 4: Double threshold algorithm detection and edge connection;

[0111] After the image is non-maximum suppressed, many discrete points are displayed on the image, the edge points are connected, and the noise points are removed. When the gradient value of the edge pixel is higher than the high threshold, it is marked as a strong edge pixel and its pixel value is set to 255; when the gradient value of the edge pixel is less than the high threshold and greater than the low threshold, it is marked as a weak edge pixel and the pixel value remains unchanged; when the gradient value of the edge pixel is less than the low threshold, the pixel point will be suppressed and the pixel value of the pixel point will be set to 0.

[0112] The process of determining the porosity in step S4 is as follows: Since the measured closed image is approximately a standard circle and the circumference is known, the diameter can be obtained by the circumference formula, as shown in the following formula:

[0113]

[0114] In the formula, C is the circumference, π is the pi, and D is the calculated diameter of the main cable;

[0115] The main cable void ratio is solved as follows:

[0116]

[0117] Where K is the porosity of the main cable, n is the total number of steel wires, d is the diameter of the steel wires, and D is the diameter of the main cable after tightening.

[0118] The present invention uses a method of drawing a standard circle to compare with the laser contour line, so as to efficiently detect the out-of-roundness after cable tightening and make an effect evaluation, and can quickly, efficiently and accurately detect the cable tightening effect; compared with the manual detection method, the present invention has the characteristics of high efficiency, high quality and high precision. While ensuring the detection accuracy, it replaces the physical labor of workers and effectively avoids the personal safety risks brought by personnel working at high altitudes.

[0119] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A device for detecting the out-of-roundness and porosity of the main cable of a suspension bridge, characterized in that: The invention comprises an outer bracket (4), a balance beam (2) is arranged on the top of the outer bracket (4), walking mechanisms (3) are arranged on both sides of the balance beam (2), a circular through hole is formed in the middle of the outer bracket (4), a high-definition camera (5) and a laser emitter (6) are arranged on both sides of the top of the inner wall of the circular through hole, an adjustment mechanism is connected between the high-definition camera (5) and the laser emitter (6), the adjustment mechanism comprises a driver (8), and limiters (7) are connected on both sides of the driver (8), and the limiters (7) are connected to the high-definition camera (5) and the laser emitter (6).

2. According to claim 1, a device for detecting out-of-roundness and porosity of main cables of a suspension bridge, characterized in that: The walking mechanism (3) comprises a beam frame (22) and a roller (21), wherein the beam frame (22) is fixedly connected to the balance beam (2), and the roller (21) is concave in shape and matches the outer diameter of the main cable (1) to be detected below.

3. The device for detecting out-of-roundness and porosity of main cables of a suspension bridge according to claim 1, characterized in that: The axis of the laser transmitter (6) where the transmitting probe is located is arranged perpendicular to the main cable (1) to be detected, and the lens of the high-definition camera (5) is directed toward the position where the laser emitted by the laser transmitter (6) contacts the main cable (1) to be detected.

4. A method for detecting the out-of-roundness and void ratio of a main cable of a suspension bridge, using a device for detecting the out-of-roundness and void ratio of a main cable of a suspension bridge as claimed in claim 1, characterized in that: The following steps are involved: S1: Pass the main cable (1) to be detected through the circular through hole in the middle of the outer bracket (4), adjust the positions of the high-definition camera (5) and the laser transmitter (6), and start the walking mechanism (3) to move to the target position to be detected; S2: The laser transmitter (6) transmits vertical laser light to the main cable (1), forming a single laser contour line (9) on the surface of the main cable (1), and the high-definition camera (5) collects images of the single laser contour line (9) on the surface of the main cable (1); S3: Control the high-definition camera (5) and the laser transmitter (6) to rotate counterclockwise in the direction of travel for one circle, repeat step S2, collect the laser contour line image of the main cable surface, and process the single laser contour line (9) image to form a closed shape, thereby forming a circle (10) drawn based on the closed shape; S4: Detect the overlap between the outer diameter circle of the main cable (1) and the circle (10) drawn based on the closed shape, and obtain the void ratio. If the overlap is greater than 99%, the main cable has excellent roundness; if the overlap is greater than 95% and less than 99%, the main cable has good roundness; If the overlap is less than 95%, the roundness of the main cable does not meet the standard.

5. A method for detecting out-of-roundness and void ratio of a main cable of a suspension bridge according to claim 4, characterized in that: In step S3, the single laser contour lines (9) are processed and combined into a closed shape to form a circle (10) drawn based on the closed shape. The specific process is as follows: S31: Using the high-definition camera (5) to observe the single laser contour line (9), an affine transformation is performed on the images of all single laser contour lines (9) to obtain a front view of the laser contour line. The affine transformation is as follows: In the formula, (t x ,t y ) represents the translation amount, parameter a i is the image rotation and scaling change, i = 1, 2, 3, 4, (x, y) is the coordinate before transformation, (x', y') is the coordinate after transformation; S32: Combining the single laser contour lines (9) after affine transformation, preprocessing the combined image, the preprocessing including image grayscale, adaptive median filtering and image binarization, performing contour edge detection on the preprocessed image, measuring the image length after contour edge detection, and obtaining the perimeter of the closed figure.

6. A method for detecting out-of-roundness and void ratio of a main cable of a suspension bridge according to claim 5, characterized in that: The process of preprocessing the combined image into grayscale in step S32 is: using a weighted average method to perform weighted average on the three components R, G, and B of the single laser contour line (9) image with different weights, wherein the weight coefficients of R, G, and B are selected as 0.3, 0.59, and 0.11 respectively, to perform image grayscale. The specific formula is as follows: g(i,j)=0.3R(i,j)+0.59G(i,j)+0.11B(i,j) (2) Where R(i,j) represents the grayscale value of the red channel at (i,j), G(i,j) represents the grayscale value of the green channel at (i,j), B(i,j) represents the grayscale value of the blue channel at (i,j), and g(i,j) is the grayscale value of the grayscale image, which is the weighted average of the brightness of the three channels, and the weighting coefficient is determined by the sensitivity of the human eye to the three colors.

7. A method for detecting out-of-roundness and void ratio of a main cable of a suspension bridge according to claim 5, characterized in that: In step S32, the combined image is pre-processed by adaptive median filtering, and the maximum value W of the f(i, j) filter window is set. max and the minimum value W min ,h max 、h med and h min They are the maximum, median and minimum grayscale values ​​of all pixels in the filter window W(i,j), respectively. The specific process is: The first step is to set W(i,j)=W min , when A1>0 and A2<0, go to the second step, otherwise, expand the size of the filter window W(i,j) and repeat the first step until W(i,j)>W max ,h med Output as output value; In the formula, h max 、h med and h min They are the maximum, median and minimum grayscale values ​​of all pixels in the filter window W(i,j); Step 2: When B1>0 and B2<0, output f(i,j); otherwise, output h med ; In the formula, h(i,j) represents the grayscale value of the pixel in the jth row and the ith column in the image, and h max and h min are the maximum and minimum grayscale values ​​of all pixels in the filter window W(i,j) respectively.

8. A method for detecting out-of-roundness and void ratio of a main cable of a suspension bridge according to claim 5, characterized in that: In step S32, the combined image is preprocessed by using the average value method, and the specific process is: the combined image is averaged by the global threshold, the average value k is set as the threshold, and the binarization is performed, and the value greater than the threshold is set to 255. The values ​​less than the threshold are set to 0, and the average value k is as follows: In the formula, i represents the gray value, p i is the probability of the pixel with gray value i appearing.

9. A method for detecting out-of-roundness and void ratio of main cables of a suspension bridge according to claim 5, characterized in that: In step S32, the combined image is subjected to contour edge detection using the Canny detection algorithm, and the specific process is as follows: In the first step, a Gaussian filter is used to smooth the combined image; Use the Gaussian filter G(x,y) to perform a convolution operation on the combined image f(x,y) to form a smoothed image f s (x,y), the Gaussian filter convolution operation is as follows: f s (x,y)=G(x,y)·f(x,y) (7) Where · is the convolution symbol, G(x,y) is the Gaussian filter, f(x,y) is the combined image, and f s (x,y) is the smoothed image; The second step is to calculate the gradient magnitude and angle The finite difference of the first-order partial derivative is used to calculate the gradient amplitude and angle of each pixel, and the image f is calculated using formulas (8) and (9). s (x, y) is convolved to obtain the gradient value G in the x, y direction x ,G y , as shown in formulas (10) and (11): G x =S x ·f s (x,y) (10) G y =S y ·f s (x,y) (11) In the formula, S x , S y is the convolution kernel, G x ,G y is the gradient value in the x and y directions; The gradient value and angle are calculated as shown in formulas (12) and (13); In the formula, G is the calculated gradient value and θ is the angle; The third step is non-maximum suppression; In the Canny detection algorithm, the amplitude is suppressed along the gradient direction, that is, along 0°, 45°, 90°, Non-maximum suppression is performed in four gradient directions of 135°; Step 4: Double threshold algorithm detection and edge connection; After the image is non-maximum suppressed, many discrete points are displayed on the image, the edge points are connected, and the noise points are removed. When the gradient value of the edge pixel is higher than the high threshold, it is marked as a strong edge pixel and its pixel value is set to 255; when the gradient value of the edge pixel is less than the high threshold and greater than the low threshold, it is marked as a weak edge pixel and the pixel value remains unchanged; when the gradient value of the edge pixel is less than the low threshold, the pixel point will be suppressed and the pixel value of the pixel point will be set to 0.

10. A method for detecting out-of-roundness and void ratio of main cables of a suspension bridge according to claim 5, characterized in that: The process of determining the void ratio in step S4 is as follows: Since the measured closed image is approximately a standard circle and the circumference is known, the circumference formula is used to determine the void ratio. The diameter can be calculated as follows: In the formula, C is the circumference, π is the pi, and D is the calculated diameter of the main cable; The main cable void ratio is solved as follows: Where K is the porosity of the main cable, n is the total number of steel wires, d is the diameter of the steel wires, and D is the diameter of the main cable after tightening.

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