Slump detection device based on binocular vision

Abstract

The utility model relates to the technical field of concrete detection, in particular to a slump detection device based on binocular vision, which comprises a test platform and a slump test cylinder, telescopic assemblies used for synchronously lifting the slump testing cylinder are arranged at the two ends of the scale line of the testing platform, a shooting assembly is installed at the top end of the testing platform, and a pure-color background plate is arranged on the opposite side of the shooting assembly. Non-contact measurement is adopted, errors caused by unstable contact or adhesion in traditional contact measurement are avoided, interference to concrete can be reduced through non-contact measurement, the stability and accuracy of measurement are improved, and high-precision reading is achieved; according to the slump measuring device, multi-step image processing and a matching algorithm can be utilized, the slump reading precision is improved, high-precision slump measurement can be realized, and the requirement of high-precision detection is met.

Description

Technical Field

[0001] This utility model relates to the field of concrete testing technology, specifically to a slump testing device based on binocular vision. Background Technology

[0002] In existing concrete slump testing, inaccurate manual readings and errors caused by contact measurement are the main problems. Manual readings rely on the operator lifting the slump cone and measuring the height difference between the cone's height and the highest point of the slumped concrete using a ruler. This process is easily affected by human factors, such as the angle of view, and the levelness or verticality of the ruler, leading to significant reading errors. Differences in testing techniques among different operators, such as the speed of lifting the cone and the amplitude of shaking, can also cause deviations in the slump test results. Furthermore, the accuracy of manual readings is usually only at the millimeter level and is prone to errors due to fatigue or lack of experience.

[0003] Contact measurement methods also have significant drawbacks. When the measuring tool is in direct contact with the concrete, it may apply pressure or disturb the concrete, causing deformation and affecting the accuracy of the measurement results. Concrete may also adhere to the measuring tool, especially in the case of high-viscosity concrete; this adhesion further interferes with the accuracy of the measurement. These problems indicate that traditional slump testing methods are significantly insufficient in terms of accuracy and stability, making it difficult to meet the requirements of high-precision testing.

[0004] In existing patents for concrete slump testing, some devices may cause damage or interference to the concrete, thus affecting the accuracy of the test results. For example, some devices, when lifting the slump cone or measuring the concrete surface, may cause surface deformation or disturbance to the internal structure of the concrete due to direct contact. This contact measurement may not only alter the natural slump state of the concrete but may also introduce additional errors due to the adhesion between the measuring tool and the concrete. These problems make contact measurement difficult to meet practical needs in scenarios requiring high precision. Therefore, improving measurement methods to reduce interference with the concrete has become an important direction of current research.

[0005] Patent CN114858800A employs a binocular vision method for concrete slump detection. While utilizing advanced image processing technology, it still faces several challenges in practical applications. Firstly, the point set constraints in this patent are insufficient, failing to adequately consider the impact of environmental factors on the measurement results. For instance, in complex on-site environments, variations in lighting, background interference, and camera viewing angle deviations can all lead to misjudgments, thus affecting measurement accuracy. Furthermore, when dealing with irregularities on concrete surfaces, this patent may fail to accurately identify and match feature points, further reducing measurement reliability. These issues indicate that while the binocular vision method possesses certain advantages, further optimization is needed in practical applications to improve its robustness and measurement accuracy in complex environments.

[0006] Therefore, it is necessary to invent a collapse detection device based on binocular vision to solve the above problems. Utility Model Content

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a slump detection device based on binocular vision. This device solves the problem that in practical applications, factors such as changes in lighting, background interference, and camera viewing angle deviation can lead to misjudgments and affect measurement accuracy in complex on-site environments.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] A slump detection device based on binocular vision includes a test platform and a slump test cylinder. The top of the test platform is provided with a scale line for detecting slump. Both ends of the scale line of the test platform are provided with telescopic components for synchronously raising the slump test cylinder. The top of the test platform is equipped with a shooting component for multi-angle shooting of concrete. A solid color background board is provided on the opposite side of the shooting component.

[0010] In a preferred embodiment of this utility model, the shooting component is a binocular camera, and the side of the solid color background plate facing the binocular camera is provided with a plurality of feature points for reference positioning.

[0011] As a preferred embodiment of this utility model, the solid color background board is vertically installed on the top of the test platform through multiple detachable connecting blocks.

[0012] In a preferred embodiment of this utility model, the telescopic component is a telescopic rod, and a test cylinder clamp is detachably installed on the outside of the slump test cylinder. The two ends of the test cylinder clamp are respectively connected to the telescopic rods on both sides for transmission.

[0013] As a preferred embodiment of this utility model, a position sensor is provided on one side of the telescopic component, and the position sensor controls the opening of the shooting component through the control module.

[0014] In a preferred embodiment of this utility model, when the bottom end of the slump test cylinder is in contact with the test platform, the sensing end of the position sensor is pressed against the test cylinder clamp.

[0015] The technical effects and advantages provided by this utility model in the above technical solution are as follows:

[0016] This invention employs a non-contact measurement method, avoiding errors caused by unstable contact or adhesion in traditional contact measurements. Non-contact measurement reduces interference with the concrete, improving the stability and accuracy of the measurement.

[0017] High-precision readings: By using a binocular camera and a solid-color background, multi-step image processing and matching algorithms improve the accuracy of slump readings. This enables high-precision slump measurement, meeting the requirements of high-precision testing.

[0018] High degree of automation: The setup of the telescopic rod and test cylinder clamps reduces manual intervention, improving testing efficiency and result stability. Automated measurement reduces the impact of human factors on measurement results, improving test repeatability and reliability.

[0019] The slump reading device of this instrument uses a binocular camera and multiple feature points on a solid-color background plate, and employs advanced image processing technology and three-dimensional coordinate reconstruction methods to achieve high-precision, non-contact measurement of concrete slump, making it suitable for various concrete testing scenarios. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the slump test cylinder of this utility model before it is lifted.

[0021] Figure 2 This is a schematic diagram of the slump test cylinder of this utility model after it has been lifted.

[0022] Figure 3 This is a schematic diagram of the structure of the position sensor and the test cylinder clamp under the contact and compression state.

[0023] Explanation of reference numerals in the attached diagram: 1. Binocular camera; 2. Telescopic rod; 3. Solid color background board; 4. Slump test cylinder; 5. Feature point; 6. Test cylinder fixture; 7. Test platform; 8. Position sensor. Detailed Implementation

[0024] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0025] This utility model provides, for example Figure 1-3 The illustrated slump detection device based on binocular vision includes a test platform 7 and a slump test cylinder 4. The top of the test platform 7 is equipped with a scale for detecting slump, and telescopic components for synchronously raising the slump test cylinder 4 are located at both ends of the scale. A camera assembly for multi-angle imaging of the concrete is mounted on the top of the test platform 7, and a solid-color background plate 3 is positioned opposite the camera assembly. The image data captured by the camera assembly is processed using the Harris corner detection algorithm to accurately extract key corner points from the images, providing a benchmark for subsequent matching. This algorithm can effectively identify significant feature points in the image, improving matching accuracy.

[0026] The Normalized Cross-Correlation (NCC) algorithm is used to coarsely match the extracted corner points and preliminarily determine the positions of corresponding points in the image. The NCC algorithm can effectively handle noise and illumination changes in the image, improving the robustness of the matching.

[0027] By combining grayscale information and epipolar constraints for precise matching, matching accuracy is further improved. This combination of grayscale information and epipolar constraints enables more accurate identification and matching of feature points, reducing false matches.

[0028] The imaging component is a binocular camera 1. The solid-color background plate 3 has multiple feature points 5 on its side facing the binocular camera 1 for reference positioning. The binocular camera 1 can calculate the distance to objects by the differences between the images captured by the two cameras and generate depth information using the principle of triangulation.

[0029] The solid-color background panel 3 is vertically mounted on the top of the test platform 7 via multiple detachable connecting blocks. The solid-color background panel 3 reduces background interference and improves the accuracy of image processing. It effectively reduces background interference in image processing and improves the accuracy of feature point extraction.

[0030] Coordinate points with known coordinates are set on the background board as a reference coordinate system for calibration and positioning. Using these known coordinate points, precise calibration and positioning of the collapse image can be achieved.

[0031] By employing the image processing and matching algorithms described above, and combining them with known coordinate points, a three-dimensional coordinate reconstruction is performed on the slump image to accurately calculate the concrete slump. This three-dimensional coordinate reconstruction provides more accurate slump measurement results and reduces human error.

[0032] The telescopic assembly is a telescopic rod 2. A test cylinder clamp 6 is detachably installed on the outside of the slump test cylinder 4. Both ends of the test cylinder clamp 6 are connected to the telescopic rods 2 on both sides for transmission. The telescopic assembly can also use a telescopic cylinder, electric threaded rod, or other device to drive the test cylinder clamp 6 to rise synchronously, ensuring the smooth vertical rise of the slump test cylinder 4.

[0033] A position sensor 8 is installed on one side of the telescopic component. The position sensor 8 controls the opening of the imaging component via a control module. When the sensing end of the position sensor 8 separates from the bottom end of the test cylinder clamp 6, the position sensor 8 sends a signal, which, through the control module, controls the opening of the imaging component. This reduces manual intervention and improves testing efficiency and result stability. Automated measurement can reduce the impact of human factors on measurement results and improve test repeatability and reliability.

[0034] When the bottom end of the slump test cylinder 4 is in contact with the test platform 7, the sensing end of the position sensor 8 is pressed against the test cylinder clamp 6. The position sensor 8 detects whether the slump test cylinder 4 and the test platform 7 are in contact and whether they are stably in contact, facilitating calibration to ensure the placement of the slump test cylinder 4 meets requirements.

[0035] The position sensor 8 is electrically connected to the binocular camera 1. The position sensor 8 is electrically connected to the binocular camera 1 via wires and a control module.

[0036] Implementation method:

[0037] Preparation:

[0038] Place the slump test cylinder on a flat base and secure it with a foot pedal to ensure stability. Clean the inner wall of the slump test cylinder and the surface of the base, ensuring there is no debris or oil. Evenly fill the slump test cylinder 4 with the concrete mixture in three layers, tamping each layer 25 times in a spiral direction from the outside in to ensure compaction. After tamping, use a scraper to level the concrete surface, making it flush with the cylinder opening.

[0039] Stillness and Photography:

[0040] After filling, allow the concrete mixture to stand for a period of time, usually 1-2 minutes, to ensure that the concrete is fully stable inside the slump test cylinder 4. Use the clamps to smoothly lift the slump test cylinder 4, ensuring the cylinder is vertically upward during lifting to avoid shaking. Simultaneously with lifting the slump test cylinder 4, the position sensor 8 separates from the test cylinder clamp 6, and the binocular camera 1 on the device is activated to capture multi-angle images of the slumped concrete, obtaining high-precision image data.

[0041] Image processing and recognition:

[0042] Harris Corner Recognition: This algorithm accurately extracts key corner points from images. These corner points serve as reference points for subsequent matching, improving the accuracy of image processing.

[0043] NCC coarse matching: The Normalized Cross-Correlation (NCC) algorithm is used to coarsely match the extracted corner points to preliminarily determine the positions of corresponding points in the image. The NCC algorithm can effectively handle noise and illumination changes in the image, improving the robustness of the matching.

[0044] Gray-scale matching: Combines gray-scale information for further matching, using gray-scale differences to identify and match feature points, thereby further improving matching accuracy.

[0045] Epipolar constraints: By utilizing epipolar constraints, matching points are precisely corrected to ensure their accuracy. Epipolar constraints can effectively reduce false matching and improve the accuracy of 3D coordinate reconstruction.

[0046] Known point correction: A solid-color background plate 3 is added to the device, and some feature points 5 with known coordinates are set on the background plate. The image is calibrated and positioned using the known feature points 5, further improving the accuracy of the measurement.

[0047] 3D coordinate reconstruction and reading:

[0048] Using the image processing and matching algorithms described above, combined with known coordinate points, the slump image is reconstructed in three dimensions to accurately calculate the coordinates of the highest point after the concrete collapses. Finally, a series of coordinate points are read, and the difference between the highest point of the collapsed concrete and the slump cone height of 300mm is calculated. This difference is the slump data of the concrete.

[0049] Data recording and analysis:

[0050] Record and analyze the measured slump data. Multiple measurements can assess the flowability and uniformity of the concrete. Observe the cohesiveness and water retention of the concrete, and record its appearance characteristics, such as the presence of segregation or bleeding.

[0051] This invention employs a non-contact measurement method, avoiding errors caused by unstable contact or adhesion in traditional contact measurements. Non-contact measurement reduces interference with the concrete, improving measurement stability and accuracy.

[0052] High-precision readings: By using a binocular camera 1 and a solid-color background 3, multi-step image processing and matching algorithms can be employed to improve the accuracy of slump readings. This enables high-precision slump measurement, meeting the requirements of high-precision detection.

[0053] High degree of automation: The setup of the telescopic rod 2 and the test cylinder clamp 6 reduces manual intervention, improving testing efficiency and result stability. Automated measurement can reduce the impact of human factors on measurement results, improving test repeatability and reliability.

[0054] The slump reading device of this instrument uses a binocular camera 1 and multiple feature points 5 on a solid-color background plate 3 to achieve high-precision, non-contact measurement of concrete slump through advanced image processing technology and three-dimensional coordinate reconstruction method, which is suitable for various concrete testing scenarios.

[0055] The above description is only a preferred embodiment of the present utility model. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present utility model, and these improvements and modifications should also be considered within the protection scope of the present utility model.

Claims

1. A collapse detection device based on binocular vision, characterized in that: The test platform (7) includes a test platform (7) and a slump test cylinder (4). The top of the test platform (7) is provided with a scale line for detecting slump. Both ends of the scale line of the test platform (7) are provided with telescopic components for synchronously raising the slump test cylinder (4). The top of the test platform (7) is equipped with a shooting component for taking pictures of concrete from multiple angles. A solid color background plate (3) is provided on the opposite side of the shooting component.

2. The collapse detection device based on binocular vision according to claim 1, characterized in that: The shooting component is a binocular camera (1), and the solid color background plate (3) has multiple feature points (5) on the side facing the binocular camera (1) for reference positioning.

3. The collapse detection device based on binocular vision according to claim 1, characterized in that: The solid color background plate (3) is vertically installed on the top of the test platform (7) via multiple detachable connecting blocks.

4. The collapse detection device based on binocular vision according to claim 1, characterized in that: The telescopic component is a telescopic rod (2), and a test tube clamp (6) is detachably installed on the outside of the slump test tube (4). The two ends of the test tube clamp (6) are respectively connected to the telescopic rods (2) on both sides for transmission.

5. The collapse detection device based on binocular vision according to claim 4, characterized in that: A position sensor (8) is provided on one side of the telescopic component, and the position sensor (8) controls the opening of the shooting component through the control module.

6. The collapse detection device based on binocular vision according to claim 5, characterized in that: When the bottom end of the slump test cylinder (4) is in contact with the test platform (7), the sensing end of the position sensor (8) is pressed against the test cylinder clamp (6).

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