A camera extrinsic parameter calibration method and device in a blast furnace environment

Abstract

The application discloses a camera external parameter calibration method and device in a blast furnace environment, and comprises collecting calibration images in a blast furnace blowing-down process after completing calibration environment preparation; image coordinate system coordinates and world coordinate system coordinates of first feature points and second feature points are respectively obtained by preprocessing all collected blast furnace images; a homography matrix H is calculated according to the first feature points; the homography matrix is iteratively optimized according to the second feature points, so that a camera external parameter matrix M is obtained, and a rotation matrix and a translation matrix of an industrial camera are obtained. The application solves the problem of no reference feature points in the blast furnace by using a rotatable laser to construct feature points, and can calculate a relatively accurate homography matrix under the condition of using at least four feature points, and finally obtains the rotation matrix and the translation matrix.

Description

Technical Field

[0001] This invention pertains to image processing technology in the metallurgical field, specifically relating to a method and device for calibrating camera extrinsic parameters when using a camera to measure target positions in a blast furnace environment. Background Technology

[0002] In normal ironmaking, the blast furnace is a typical high-temperature, high-pressure, and highly complex chemical reaction environment. Inside this large, sealed container, ore and reducing agents undergo continuous chemical reactions under high-temperature conditions. Due to the intense chemical reactions and high-temperature melting, coupled with the burden poured from the top of the furnace, the environment inside is extremely harsh. However, real-time acquisition of the blast furnace burden morphology can guide technicians to optimize the ironmaking process, improving efficiency and quality by adjusting operating parameters such as charging and blast volume. Furthermore, it allows for the timely detection of abnormal changes in the burden surface, such as agglomeration, air leakage, and material slippage. Therefore, real-time acquisition of the blast furnace material plane curve is of significant importance to blast furnace production.

[0003] Currently, there are various methods for obtaining the planar curve of blast furnace materials, such as radar measurement, visual measurement, and mechanical probe measurement. While mechanical probe measurement is accurate and reliable, it cannot cover every point on the furnace top, relying heavily on operator experience, which introduces significant experiential and arbitrary elements into blast furnace operation. Radar measurement offers high accuracy and stability, along with a wide measurement range, thus meeting the needs of most industrial applications. However, it is expensive, and radar installation and maintenance are complex and costly. Furthermore, it is susceptible to interference from foam, dust, and rough materials, potentially leading to measurement errors.

[0004] During normal operation of a blast furnace, images captured by cameras mounted on the furnace wall are typically completely black, with only occasional glimpses of flames inside. Visual measurements are impossible. However, when the blast furnace requires inspection, maintenance, or malfunction, a shutdown operation is necessary. During this shutdown, the temperature and pressure inside the furnace decrease accordingly. Although blasting has stopped, measures are still needed to maintain the high temperature inside the furnace, such as periodically injecting hot air or steam to prevent the temperature from dropping too rapidly. In this situation, the images captured by the cameras mounted on the furnace wall will be different. Besides the central flames, after image processing, the images captured by the cameras can clearly show the structure and condition of the furnace wall.

[0005] Extrinsic parameter calibration is performed on cameras mounted on blast furnaces. These extrinsic parameters describe the camera's position and attitude. Currently, the main methods for camera extrinsic parameter calibration include direct linear transformation, Zhang Zhengyou calibration, feature-based methods, and self-calibration methods. The direct linear transformation method calibrates the camera using at least six pairs of non-coplanar points. Considering that only cross-sections need to be measured in actual operations, calibration only needs to be performed on points on a single specified plane. The Zhang Zhengyou calibration method requires a checkerboard pattern, which is not feasible in a blast furnace environment; it must rely on existing furnace wall construction parameters as feature points. Feature-based methods require objects of known size, which is also impractical in a blast furnace. The direct linear transformation method requires camera movement, but cameras inside a blast furnace are fixed to the furnace wall, making it unsuitable for the blast furnace environment.

[0006] The most challenging aspect of calibrating camera extrinsic parameters inside a blast furnace lies in finding feature points that enable the camera to measure a specified plane. Therefore, this paper proposes a method for calibrating camera extrinsic parameters in a confined environment like a blast furnace when measuring target locations. Summary of the Invention

[0007] The purpose of this invention is to solve the problem of camera extrinsic parameter calibration when using a camera to measure the target position in a closed environment such as a blast furnace, and to provide a method and device for calibrating camera extrinsic parameters in a blast furnace environment.

[0008] The objective of this invention is achieved through the following technical solution:

[0009] A method for calibrating camera extrinsic parameters in a blast furnace environment includes the following steps after the calibration environment preparation is completed:

[0010] Step 1: Acquire calibration images during blast furnace shutdown.

[0011] During the rotation of the laser, the industrial camera continuously captures multiple images of the blast furnace. The periodic images contain laser points that the laser illuminates on the furnace wall, and the blast furnace images are sent to the processor for analysis.

[0012] Step 2: Preprocess all acquired blast furnace images to obtain the image coordinate system coordinates and world coordinate system coordinates of the first and second feature points respectively;

[0013] Specifically, it includes:

[0014] S201: Select multiple laser points as the first feature points based on the image captured by the camera, and use the center of the laser that is outside the camera's field of view as the second feature point;

[0015] S202: Based on the pre-acquired outline of the inner wall of the blast furnace and the blast furnace construction parameters, obtain the world coordinate system coordinates corresponding to the first feature point in the blast furnace image, and calculate the laser coordinates based on the laser's installation position as the world coordinate system coordinates corresponding to the second feature point;

[0016] S203: Perform laser point annotation on the blast furnace image to obtain the curve of the measurement surface formed by the laser points intersecting with the blast furnace; extract the intersection point of this curve with the outline of the inner wall of the blast furnace formed by the furnace bricks, and use it as the image coordinate system coordinates corresponding to the first feature point;

[0017] The image coordinate system coordinates of the first feature point correspond one-to-one with the world coordinate system coordinates.

[0018] S204: Mark the two vertices of the laser line in the blast furnace image, model each laser line in the image coordinate system, obtain the distance from any point to the laser line, and calculate a point that minimizes its distance to the set of lines, thereby obtaining the position of the laser center point, which is used as the image coordinate system coordinates corresponding to the second feature point;

[0019] Step 3: Image Processing

[0020] Calculate the homography matrix H based on the first feature point; iteratively optimize the obtained homography matrix H based on the coordinates of the second feature point obtained in step S204 to obtain the updated homography matrix H;

[0021] Based on the updated homography matrix H and the pre-calibrated intrinsic parameters K of the industrial camera, the extrinsic parameters M of the camera are obtained, and the position and orientation of the camera are obtained, thereby obtaining the rotation and translation matrices of the industrial camera.

[0022] Furthermore, S203 specifically includes: outlining the contour of the laser spot; recording all coordinates and corresponding gray values ​​within the contour; calculating the centroid of the laser spot using the gray-scale centroid method to obtain the coordinates of the laser point corresponding to the current blast furnace image; calculating the average value of the laser point coordinates in the same image during each rotation cycle of the laser as the laser point sequence; marking the laser point sequence on the same image to obtain the curve of the measurement surface formed by the laser points intersecting with the blast furnace.

[0023] Furthermore, the outline of the laser spot circled in S203 specifically includes:

[0024] First, the image is magnified to its maximum size using OpenCV image processing technology. The region where the possible laser center point is located is selected as the region of interest. The Canny edge detection algorithm is used to obtain a reasonable set of edge points in the image. The findContours tool is used to search for contours in the image and outline the contour of the laser spot.

[0025] Furthermore, the number of known feature points for the coordinates is no less than four.

[0026] Furthermore, in step three, when the number of first feature points is more than four, the least squares method and iterative optimization are used sequentially when calculating the homography matrix based on the first feature points to obtain the optimal solution of the homography matrix and eliminate errors. When the average error is less than 5 cm, it indicates that the first feature points are accurate, and the next step is carried out.

[0027] Furthermore, calibration environment preparation includes:

[0028] A laser and an industrial camera are installed on the throat of the furnace inside the blast furnace, on the plane to be measured. The plane on which the laser line emitted by the laser rotates coincides with the plane being measured. The industrial camera and the laser are located on the same horizontal plane, and the internal parameter K of the industrial camera is pre-calibrated.

[0029] Furthermore, the blast furnace construction parameters include: throat height and radius, furnace body height and radius, and the material dimensions used to construct the throat and furnace body;

[0030] A calibration device includes a laser, an industrial camera, and a processor. The laser and the industrial camera are installed inside a blast furnace. The industrial camera and the laser are located on the same horizontal plane, and the plane of rotation of the emitted laser line coincides with the plane of the blast furnace being measured. The plane being measured is the central cross-section of the blast furnace. The laser is connected to the processor via a PLC. The industrial camera is connected to the processor via an industrial data acquisition card. The processor is used to implement the calibration method.

[0031] Compared with the prior art, the beneficial effects of the technical solution of the present invention are:

[0032] This invention utilizes lasers to construct feature points, solving the problem of insufficient reference feature points in blast furnaces; and uses a very small number of feature points to calculate a relatively accurate homography matrix, finally obtaining the rotation matrix and translation matrix. Attached Figure Description

[0033] Figure 1 This is a blast furnace model used for illustration in the camera extrinsic parameter calibration method described in this invention;

[0034] Figure 2 These are feature points inside the blast furnace used as examples.

[0035] in:

[0036] 1: Feature point P1; 2: Feature point P2; 3: Feature point P3; 4: Feature point P4;

[0037] 5: P5 feature point; 6: P6 feature point; 7: P7 feature point; 8: Laser;

[0038] 9: Laser line Detailed Implementation

[0039] To make the objectives, technical solutions, beneficial effects, and significant advancements of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings provided in the examples of the present invention. Obviously, all the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] In the description of this application, unless otherwise expressly specified and limited, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance; the term "multiple" refers to two or more; unless otherwise specified or explained, the terms "connected," "fixed," etc., should be interpreted broadly. For example, "connected" can be a fixed connection, a detachable connection, an integral connection, or an electrical connection; "connected" can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0041] A method for calibrating camera extrinsic parameters when measuring target position using a camera in a blast furnace environment, specifically including:

[0042] Step 1: Preparation of the calibration environment:

[0043] In such Figure 1 A rotatable laser 8 is installed as a target on the throat of the blast furnace where the plane to be measured needs to be measured. The plane on which the laser line 9 emitted by the laser 8 rotates is required to coincide with the plane to be measured.

[0044] In a blast furnace environment, the plane being measured is generally the central cross-section of the blast furnace, so extra care is needed when installing the laser 8;

[0045] Prepare an industrial camera (black and white). The camera needs to be able to withstand high temperatures and ensure that it can transmit at least 10 frames per second. The resolution needs to be consistent with the measurement accuracy requirements.

[0046] Several checkerboard images were taken from different angles using the industrial camera, and the camera's intrinsic parameters were calculated using the Zhang Zhengyou calibration method. This lays the groundwork for subsequent calculations;

[0047] in, This represents the camera's focal length divided by the size of a single pixel. u0 and v0 represent the offset of the principal point in the pixel coordinate system. f is the focal length of the industrial camera. dx is the average size of each pixel in the horizontal direction of the camera. dy is the average size of each pixel in the vertical direction of the camera.

[0048] An industrial camera is installed at the same level as the laser in the throat of the blast furnace. The camera is required to be able to observe the entire plane of laser line rotation.

[0049] Obtain blast furnace construction parameters, including: throat height and radius, furnace body height and radius, and dimensions of materials (such as carbon bricks) used to construct the throat and furnace body;

[0050] Step Two: During the blast furnace shutdown process, calibration images are acquired, specifically including:

[0051] During blast furnace shutdown, the material level is low, allowing for a clear observation of the outline of the inner furnace wall, such as... Figure 2 As shown;

[0052] Rotate laser 8 to ensure that the laser beam hits the blast furnace wall;

[0053] During the rotation of laser 8, images captured by the camera are continuously acquired. The images are required to show the laser points on the furnace wall. Each rotation of the laser is recorded as one cycle, and multiple cycles of images are acquired.

[0054] Based on the laser points collected on the furnace wall, determine the plane where laser line 9 is located. Using the outline of the inner furnace wall and the blast furnace construction parameters, find as many points in the known world coordinate system as possible as feature points.

[0055] Feature points are divided into the following two parts:

[0056] 1. The first feature point whose coordinates are completely known, such as the outline of the inner wall of a blast furnace formed by furnace bricks, such as... Figure 2 The seven feature points labeled with Arabic numerals are denoted as: P1, P2, P3, P4, P5, P6, and P7. Their coordinate representations will be shown in the next preprocessing step.

[0057] 2. The second feature point with known partial information, such as the center of the laser (the center of rotation of the laser line) that is outside the camera's field of view, is denoted as P0. Its coordinate representation will be shown in the next preprocessing step.

[0058] Step 3: Preprocess the acquired calibration images to obtain calibration data, specifically including:

[0059] 1. For the first feature point whose coordinates are completely known, the number of feature points must be no less than 4.

[0060] 1) Obtain world coordinate system coordinates. Based on the camera imaging principle, acquire multiple first feature points (at least 4 non-collinear feature points) on the specified plane of the blast furnace under test on the laser rotation plane. Calculate the three-dimensional coordinates of the target points according to the blast furnace construction dimensions, denoted as P1: P2: P3: ... P n : Since only the material curve on a specified plane needs to be measured, let z wn =0, obtain the coordinates of feature point P1 in the world coordinate system: P2: P3: ... P n :

[0061] 2) Obtain the coordinates of the image coordinate system.

[0062] Laser point annotation is performed on all images acquired by the camera. The annotation process is as follows:

[0063] Since industrial cameras take black and white photos, the blast furnace image obtained is a single-channel grayscale image. First, the image is magnified to the maximum using OpenCV image processing technology. The region where the center point of the possible laser spot is located is selected as the region of interest. The Canny edge detection algorithm is used to obtain a reasonable set of edge points in the image. The findContours tool is used to search for contours in the image and circle the contour of the laser spot.

[0064] Secondly, record the coordinate information (x, y) of all points within the contour and their corresponding gray values ​​I;

[0065] Finally, the centroid of the laser spot is calculated using the gray-scale centroid method. The calculation formula is as follows:

[0066]

[0067] The obtained (x) z ,y z This refers to the coordinates of the laser point corresponding to this image.

[0068] Let the coordinates of the laser point in the i-th image within the m-th period be (x... mi ,y mi There are M cycles in total, and each cycle contains I images.

[0069] The average value of the laser points in the same image for each period is then:

[0070]

[0071] Use sequence(x)i ,y i () is used as the obtained laser point.

[0072] laser point sequence (x) i ,y i The laser points are labeled on the same image to obtain the curve of the intersection between the measurement surface formed by the laser points and the blast furnace;

[0073] The intersection point of this curve and the contour of the inner wall of the blast furnace formed by the furnace bricks is extracted as the first feature point, i.e. Figure 2 The seven feature points 1, 2, 3, 4, 5, 6, 7, labeled with Arabic numerals, are denoted as P1 in the image coordinate system. P2: P3: ... P n : This coordinate and the aforementioned world coordinate system coordinate P1: P2: P3: ... P n : One-to-one correspondence.

[0074] 2. For feature points with known partial information, take the laser center (laser line rotation center) P0, which is outside the camera's field of view, as an example.

[0075] 1) Obtain the world coordinate system coordinates of the laser center. Due to the harsh installation environment and numerous surrounding devices, although the laser is installed on the furnace throat, its exact location cannot be determined. Only the rotation plane of laser line 9 passing through the blast furnace center can be guaranteed. Figure 1 As shown.

[0076] Based on the blast furnace structural parameters, establish a coordinate system for the blast furnace cross-section diagram and calculate the linear equation of the furnace throat where laser 8 is located:

[0077] y=f(x) (3)

[0078] From this, the coordinates of the laser can be obtained:

[0079] (x,f(x0)) (4)

[0080] 2) Obtain the image coordinates of the laser center. Since the laser center is outside the image field of view, its image coordinates cannot be directly obtained. Assuming the blast furnace is a homogeneous medium, and considering that light travels in a straight line in a homogeneous medium, laser line 9 can be considered a straight line in the world coordinate system. Based on the linear invariance of light in the world and image coordinate systems, the laser line obtained in the image coordinate system is also a straight line.

[0081] Therefore, the method for obtaining the laser center coordinates in the image coordinate system is as follows:

[0082] Laser line annotation is performed on the image sequence acquired by the camera, marking the two vertices of the laser line and recording their coordinates as follows:

[0083] (u n1 ,v n1 ),(u,v n2 (5)

[0084] Where n represents the number of the image sequence;

[0085] Model each laser line in the image coordinate system. The mathematical equation for each laser line is:

[0086] (u n2 -v n1 )u+ (u n1 -v n2 )v+(u n2 -u n1 )v n1 -(v n2 -v n1 )u n1 =0 (6)

[0087] Let A be the name of the person in question. n =(v n2 -v n1 ),B n =(u n1 -u n2 ),C n =(u n2 -u n1 )v n1 -(v n2 -v n1 )u n1

[0088] Therefore, the distance from any point (u, v) in the image coordinate system to the laser line can be obtained as follows:

[0089]

[0090] Assume the range of values ​​for the laser center point (u0, v0) is {(u0, v0)|u a <u0<u b ,v a <v0<v b};

[0091] The center point of the laser can be obtained using the following method:

[0092]

[0093] Where d mn It is {(u0,v0)|u a <u0<u b ,v a <v0<v b The distance from the nth point within the range to the mth laser line. The laser center point (u0, v0) is used as the image coordinate system coordinates corresponding to the second feature point.

[0094] Step 4: Image Processing

[0095] 1. Calculate the initial value of the homography matrix H using feature points whose coordinates are completely known:

[0096] 1) If the number of feature points is exactly 4, they are denoted as follows:

[0097]

[0098] according to Calculate the homography matrix This is denoted as AH = U, that is:

[0099]

[0100] Finally, the homography matrix H = A can be obtained. -1 U.

[0101] 2) If the number of feature points is more than 4, they are respectively denoted as

[0102]

[0103] according to Calculate the homography matrix Recorded as Right now:

[0104]

[0105] Finally, based on the least squares method... Find the optimal solution of the homography matrix.

[0106] 2. Error calculation.

[0107] 1) If the number of feature points is exactly 4, there is no room for error calculation. Refer to the subsequent iterative optimization.

[0108] 2) If the number of feature points is more than 4, then use the solution... and pixel coordinate system coordinates The world coordinate system coordinates are calculated as follows:

[0109]

[0110] Then calculate the average error:

[0111]

[0112] When the required average error error < 5 cm, it indicates that the calculation is reasonable, and proceed to the next step. If the average error erro ≥ 5 cm, it indicates that the first feature point is inaccurate or has errors, and recalibration is required.

[0113] 3. Use the center P0 of the laser (the rotation center of the laser line) outside the camera's field of view to iteratively optimize the homography matrix.

[0114] 1) Using the center (u0, v0) of the laser in the image coordinate system and the homography matrix H obtained in Step 3, the center coordinates (x 01 ′, y 01 ′) of the laser in the world coordinate system can be calculated as: (x -1 ′, y

[0115] ′) = H 01 ·(u0, v0); 01 According to Step 3, (x

[0116] ′, y 01 ′) should be located on the line y = f(x). However, due to errors in the calculation of the homography matrix H, therefore: 01 ′) The point on the line y = f(x) closest to (x 01 , y 01 ) is taken as the first iteration coordinates (x

[0117] 3) On the basis of the original corresponding relationship of feature points, add (x 01 , y 01 ) ~ (u0, v0), and use formula (11) to calculate the homography matrix again

[0118] 4) After calculation, without including the feature point of the laser center, recalculate the error according to formula (13). When the newly calculated error error1 < error0, repeat the iterative optimization until error n+1 -error n ≤ 0.1 and stop.

[0119] 4. If a camera model needs to be established, the following steps can be used for calculation:

[0120] Using H = KM, the external camera parameters M can be calculated as:

[0121] M = K -1 H (14)

[0122] Where matrix K represents the camera intrinsic parameters calculated in step one.

[0123] because

[0124]

[0125] The rotation matrix can be obtained. Translation matrix

[0126] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style of the specification is merely for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in the embodiments can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for calibrating camera extrinsic parameters in a blast furnace environment, characterized in that, After completing the calibration environment preparation, the following steps are included: Step 1: Acquire calibration images during blast furnace shutdown. During the rotation of the laser, the industrial camera continuously captures multiple images of the blast furnace. Each rotation of the laser is recorded as one cycle, and multiple cycle images are obtained. The cycle images contain the laser points that the laser illuminates on the furnace wall, and the blast furnace images are sent to the processor for analysis. Step 2: Preprocess all acquired blast furnace images to obtain the image coordinates and world coordinates of the first and second feature points respectively; specifically including: S201: Select multiple laser points as the first feature points based on the image captured by the camera, and use the center of the laser that is outside the camera's field of view as the second feature point; S202: Based on the pre-acquired outline of the inner wall of the blast furnace and the blast furnace construction parameters, obtain the world coordinate system coordinates corresponding to the first feature point in the blast furnace image, and calculate the laser coordinates based on the laser's installation position as the world coordinate system coordinates corresponding to the second feature point; S203: Perform laser point annotation on the blast furnace image to obtain the curve of the measurement surface formed by the laser points intersecting with the blast furnace; extract the intersection point of this curve with the outline of the inner wall of the blast furnace formed by the furnace bricks, and use it as the image coordinate system coordinates corresponding to the first feature point; The image coordinate system coordinates of the first feature point correspond one-to-one with the world coordinate system coordinates. S204: Mark the two vertices of the laser line in the blast furnace image, model each laser line in the image coordinate system, obtain the distance from any point to the laser line, and calculate a point that minimizes its distance to the set of lines, thereby obtaining the position of the laser center point, which is used as the image coordinate system coordinates corresponding to the second feature point; Step 3: Image Processing Calculate the homography matrix H based on the first feature point; iteratively optimize the obtained homography matrix H based on the coordinates of the second feature point obtained in step S204 to obtain the updated homography matrix H; Based on the updated homography matrix H and the pre-calibrated intrinsic parameters K of the industrial camera, the extrinsic parameters M of the camera are obtained, thereby acquiring the rotation and translation matrices of the industrial camera.

2. The camera extrinsic parameter calibration method of claim 1, wherein, Step S203 specifically includes: outlining the laser spot; recording all coordinates and corresponding gray values ​​within the outline; calculating the centroid of the laser spot using the gray-scale centroid method to obtain the coordinates of the laser point corresponding to the current blast furnace image; calculating the average value of the laser point coordinates in the same image during each rotation cycle of the laser as the laser point sequence; marking the laser point sequence on the same image to obtain the curve of the measurement surface formed by the laser points intersecting with the blast furnace.

3. The camera extrinsic parameter calibration method according to claim 2, characterized in that, Step S203, outlining the laser spot, specifically includes: First, the image is magnified to its maximum size using OpenCV image processing technology. The center point of the possible laser spot is selected as the focus. The Canny edge detection algorithm is used to obtain a reasonable set of edge points in the image. The findContours tool is used to search for contours in the image and outline the contour of the laser spot.

4. The camera extrinsic parameter calibration method of claim 1, wherein, The number of known feature points for the coordinates shall not be less than 4.

5. The camera extrinsic parameter calibration method of claim 4, wherein, In step three, when the number of first feature points is greater than four, the least squares method and iterative optimization are used sequentially when calculating the homography matrix based on the first feature points to obtain the optimal solution of the homography matrix and eliminate errors. When the average error... If the first feature point is accurate, proceed to the next step.

6. The camera extrinsic parameter calibration method according to claim 1, characterized in that, Calibration environment preparation includes: A laser and an industrial camera are installed on the throat of the furnace where the plane to be measured needs to be measured inside the blast furnace; the plane of rotation of the laser line (9) emitted by the laser (8) is kept coincident with the plane to be measured; the industrial camera and the laser (8) are located on the same horizontal plane, and the internal parameters K of the industrial camera are pre-calibrated.

7. The camera extrinsic parameter calibration method according to claim 1, characterized in that, The blast furnace construction parameters include: throat height and radius, furnace body height and radius, and the material dimensions used to construct the throat and furnace body.

8. A calibration device, characterized by The system includes a laser (8), an industrial camera, and a processor. The laser and the industrial camera are installed inside the blast furnace. The industrial camera and the laser (8) are located on the same horizontal plane, and the plane of rotation of the emitted laser line (9) coincides with the plane of the blast furnace being measured. The plane of measurement is the central section of the blast furnace. The laser (8) is connected to the processor via a PLC. The industrial camera is connected to the processor via an industrial acquisition card. The processor is used to implement the camera extrinsic parameter calibration method according to claim 1.

Images