Device and method for detecting surface defects of tubular steel body

Abstract

The invention discloses a tubular steel body surface defect detection device and method, and relates to the technical field of detection equipment, the tubular steel body surface defect detection device comprises a detected steel pipe, a servo electric cylinder and a 3D camera, the 3D camera is arranged on the outer side of the detected steel pipe, the 3D camera is fixedly connected with the servo electric cylinder, and the servo electric cylinder is fixed on a device frame; the 3D cameras are respectively connected with the off-line computing system through wires; based on the equipment detection method, an on-line detection system and an off-line calculation system are included. According to the tubular steel body surface defect detection device and the detection method, non-contact measurement can be realized; online real-time detection is achieved, and the detection coverage range is widened; the detection precision is improved; the detection efficiency is improved.

Description

Technical field:

[0001] The invention relates to the technical field of detection equipment, and in particular to a device and method for detecting surface defects of a tubular steel body. Background technology:

[0002] The high stress and friction environment during the production of steel pipes can easily lead to various defects on the surface of the steel pipes, such as cracks, scratches, pits, oxide scale, etc. These defects may seriously affect the performance of the steel pipes and even lead to early failure. With the advancement of manufacturing technology, the quality requirements of steel pipes are constantly increasing, so the demand for surface defect detection is becoming more and more urgent. Traditional manual detection methods can no longer meet the needs of modern manufacturing industry for efficient and high-precision detection due to their low efficiency, poor accuracy and susceptibility to interference from human factors.

[0003] Manual visual inspection: The operator visually observes the surface of the steel pipe to find defects such as cracks, scratches, pits, decarburization layer, oxide scale, etc. that are visible to the naked eye. This requires tools such as light sources and magnifying glasses. The inspection efficiency is low and is greatly affected by subjective factors.

[0004] Visual inspection: Use image processing technology to conduct online inspection of the steel pipe surface and automatically identify the type and location of defects. The inspection method based on machine vision can greatly improve the inspection efficiency, but the robustness and accuracy of the image processing algorithm still have room for improvement, especially when facing complex steel pipe surface environments (such as lighting changes, reflections, etc.).

[0005] Ultrasonic testing: Ultrasonic technology detects defects inside and on the surface of steel pipes through the reflection of sound waves. This technology is particularly sensitive to internal defects, but has limited detection accuracy for small surface defects.

[0006] Eddy current testing: Using eddy current technology, eddy currents are generated on the surface of steel pipes through electromagnetic induction to detect defects. This method is suitable for detecting surface cracks and deep defects of conductive materials. It has high sensitivity, but the cost of the detection equipment is high and the detection effect is limited for workpieces with complex shapes.

[0007] At the same time, the traditional manual measurement method is limited by the operator's experience and technical level, and the measurement results are highly subjective and prone to errors. In addition, the detection methods of mechanical equipment often rely on complex operating steps, which not only increases the detection time, but may also damage the surface of the steel pipe and affect the final product quality. At the same time, the manual measurement method cannot perform real-time online detection and can only be completed through random inspection and delivery inspection, which reduces the quality control standards of the product and brings potential risks. Summary of the invention:

[0008] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and to provide a device and method for detecting surface defects of tubular steel bodies. It uses 3D structured light technology to accurately detect defects on the surface of steel pipes through three-dimensional reconstruction, overcoming the limitations of traditional detection methods. Compared with 2D visual detection, 3D structured light can not only avoid interference from light and reflection, but also obtain depth information, identify tiny pits and cracks, and improve detection accuracy. Compared with ultrasonic and eddy current detection, 3D structured light uses non-contact detection, which can accurately evaluate the geometric shape of surface defects without causing damage to the steel pipe.

[0009] In addition, the 3D structured light system has efficient automation capabilities, which solves the problem of strong subjectivity and low efficiency of manual inspection and can realize online real-time inspection. Compared with other inspection methods, this technology improves the detection accuracy and reliability of steel pipe surface defects, especially in complex production environments, with strong adaptability.

[0010] In order to solve the problems existing in the background technology, the present invention adopts the following technical scheme: it includes a steel pipe to be inspected, a servo electric cylinder and a 3D camera, a 3D camera is provided on the outside of the steel pipe to be inspected, the 3D camera is fixedly connected to the servo electric cylinder, the servo electric cylinder is fixed on the device frame, and the 3D camera is connected to the offline computing system through wires.

[0011] The number of the servo electric cylinders is at least four, which are evenly distributed on the outer circumference of the steel pipe to be inspected, and a 3D camera is connected to the end of each servo electric cylinder.

[0012] The detection method includes an online detection system and an offline calculation system, and the online detection system is connected with the offline calculation system.

[0013] The detection method of the online detection system is as follows:

[0014] Step 1: Synchronous trigger signal: In order to ensure the accuracy and synchronization of the surface defect detection system of the steel pipe being inspected, this system controls the operation of multiple detection devices through a synchronous trigger signal. The signal is based on the moving speed of the steel pipe being inspected to achieve real-time scanning of different positions on the surface of the steel pipe being inspected. The synchronous trigger signal ensures the consistency of the collected data in space and avoids image or data offset problems caused by time errors.

[0015] Step 2: Multi-threaded data acquisition: Under the control of synchronous trigger signals, the system collects data from multiple cameras and sensors with millisecond accuracy. Multi-threading technology is used to process data input from multiple sensors simultaneously, ensuring real-time and efficient acquisition of large amounts of image data. Each thread processes the data stream independently, ensuring synchronization and stability of data acquisition and processing.

[0016] Step 3: Multi-camera data fusion: In order to capture the complete three-dimensional information of the surface of the steel pipe being inspected, the system uses multiple 3D cameras to shoot data from different angles, and integrates these perspective data into a unified 3D model through data fusion technology. Data fusion not only solves the problem that a single 3D camera cannot fully cover, but also improves the accuracy and completeness of detection, especially for complex surface details;

[0017] Step 4: 3D reconstruction of the steel pipe surface: Based on the data collected by multiple 3D cameras, the system uses a 3D reconstruction algorithm to accurately model the steel pipe surface. By analyzing multi-view images, a high-precision 3D surface model of the inspected steel pipe is generated to reproduce the surface morphology and geometric features of the inspected steel pipe. This 3D model provides a basis for subsequent defect detection and provides intuitive 3D data support for the quality evaluation of the inspected steel pipe.

[0018] Step 5: Defect detection calculation: After completing the 3D reconstruction of the surface of the steel pipe to be inspected, the system will automatically perform defect detection on the model. By comparing the actual morphology of the surface of the steel pipe to be inspected with the preset standard, defects such as cracks, pits, scratches, etc. are detected. The system automatically identifies and classifies different types of defects through algorithms, and calculates the size, depth and location of each defect.

[0019] Step 6. Defect location recording: When the system detects defects on the surface of the inspected steel pipe, it will automatically record the specific location of the defect and store the defect type and severity in the database. This information can be used for subsequent analysis and tracking to ensure the integrity of the defect data and support quality control and improvement in production.

[0020] The detection method of the offline computing system is as follows:

[0021] Step 1: Camera calibration: In order to ensure the accuracy of the multi-3D camera system, 3D camera calibration is essential. By calibrating the 3D camera position, focal length and viewing angle, the system can reduce data distortion caused by equipment placement errors and ensure that data collected by different 3D cameras can be seamlessly integrated in three-dimensional space.

[0022] Step 2: System calibration: In addition to 3D camera calibration, system calibration further considers the geometric layout of the equipment, measurement accuracy and external environmental influences. Through calibration, the system can standardize multiple parameters to ensure the detection accuracy and consistency of various hardware in actual operation.

[0023] Step 3: Detection configuration: The offline computing system integrates the results of 3D camera calibration and online detection system calibration into standardized detection configuration files. These configuration files contain the parameters required for system operation, such as 3D camera calibration data, measurement range, and defect detection threshold, to ensure that the online detection system can continuously and efficiently detect surface defects of steel pipes.

[0024] The detection configuration in the third step of the offline computing system is combined with the multi-camera data fusion in the third step of the online detection system.

[0025] The beneficial effects of the present invention are:

[0026] 1. Non-contact measurement can be achieved;

[0027] 2. Online real-time detection to improve detection coverage;

[0028] 3. Improve detection accuracy;

[0029] 4. Improve detection efficiency. Description of the drawings:

[0030] Figure 1 It is a schematic diagram of the structure of the detection device of the present invention;

[0031] Figure 2 It is a system flow chart of the detection method of the present invention;

[0032] Figure 3 It is a schematic diagram of the detection range of the present invention. Specific implementation method:

[0033] Refer to each Figure 1 The present invention specifically adopts the following implementation mode: including a steel pipe 3 to be inspected, a servo electric cylinder 1 and a 3D camera 2. The 3D camera 2 is arranged outside the steel pipe 3 to be inspected. The 3D camera 2 is fixedly connected to the servo electric cylinder 1. The servo electric cylinder 1 is fixed on the device frame. The 3D camera 2 is connected to the offline computing system through wires. The number of the servo electric cylinders 1 is at least four, which are evenly distributed on the outer circumference of the steel pipe 3 to be inspected, and a 3D camera is connected to the end of each servo electric cylinder 1.

[0034] The detection method comprises an online detection system and an offline calculation system, and the online detection system is connected with the offline calculation system.

[0035] The detection method of the online detection system is as follows:

[0036] Step 1: Synchronous trigger signal: In order to ensure the accuracy and synchronization of the surface defect detection system of the steel pipe 3 to be inspected, the system controls the operation of multiple detection devices through a synchronous trigger signal. The signal is based on the moving speed of the steel pipe 3 to be inspected, and realizes real-time scanning of different positions on the surface of the steel pipe 3 to be inspected. The synchronous trigger signal ensures the consistency of the collected data in space, avoiding the image or data offset problem caused by time error;

[0037] Step 2: Multi-threaded data acquisition: Under the control of synchronous trigger signals, the system collects data from multiple cameras and sensors with millisecond accuracy. Multi-threading technology is used to process data input from multiple sensors simultaneously, ensuring real-time and efficient acquisition of large amounts of image data. Each thread processes the data stream independently, ensuring synchronization and stability of data acquisition and processing.

[0038] Step 3: Multi-camera data fusion: In order to capture the complete three-dimensional information of the surface of the steel pipe 3 being inspected, the system uses multiple 3D cameras 2 to shoot data from different angles, and integrates these perspective data into a unified 3D model through data fusion technology. Data fusion can not only solve the problem that a single 3D camera 2 cannot fully cover the entire area, but also improve the accuracy and completeness of the inspection, especially for complex surface details;

[0039] Step 4: 3D reconstruction of the steel pipe surface: Based on the data collected by the multiple 3D cameras 2, the system uses a 3D reconstruction algorithm to accurately model the steel pipe surface. By analyzing the multi-view images, a high-precision 3D surface model of the inspected steel pipe 3 is generated to reproduce the surface morphology and geometric features of the inspected steel pipe 3. The 3D model provides a basis for subsequent defect detection and provides intuitive 3D data support for the quality evaluation of the inspected steel pipe 3.

[0040] Step 5: Defect detection calculation: After completing the 3D reconstruction of the surface of the steel pipe 3 to be inspected, the system will automatically detect defects on the model. By comparing the actual morphology of the surface of the steel pipe 3 to the preset standard, defects such as cracks, pits, scratches, etc. are detected. The system automatically identifies and classifies different types of defects through algorithms, and calculates the size, depth and position of each defect.

[0041] Step 6. Defect location recording: When the system detects defects on the surface of the inspected steel pipe 3, it will automatically record the specific location of the defect and store the defect type and severity in the database. This information can be used for subsequent analysis and tracking to ensure the integrity of the defect data and support quality control and improvement in production.

[0042] The detection method of the offline computing system is as follows:

[0043] Step 1: Camera calibration: In order to ensure the accuracy of the multi-3D camera 2 system, 3D camera 2 calibration is essential. By calibrating the position, focal length and viewing angle of the 3D camera 2, the system can reduce data distortion caused by equipment placement errors and ensure that the data collected by different 3D cameras 2 can be seamlessly integrated in three-dimensional space.

[0044] Step 2: System calibration: In addition to the calibration of 3D camera 2, the system calibration further considers the geometric layout of the equipment, measurement accuracy and external environmental influence. Through calibration, the system can standardize multiple parameters to ensure the detection accuracy and consistency of various hardware in actual operation.

[0045] Step 3: Detection configuration: The offline computing system integrates the results of 3D camera 2 calibration and online detection system calibration into standardized detection configuration files. These configuration files contain the parameters required for system operation, such as 3D camera 2 calibration data, measurement range and defect detection threshold, to ensure that the online detection system can continuously and efficiently perform steel pipe surface defect detection.

[0046] The detection configuration in the third step of the offline computing system is combined with the multi-camera data fusion in the third step of the online detection system.

[0047] In the process of the detection method, the second and third steps in the online detection system may not be set up for multi-threading. According to different detection targets and detection scenarios, the order of the third, fourth and fifth steps in the online detection system may be adjusted.

[0048] Reference Figure 1 and Figure 3 The design of the inspection device is due to the fact that the steel pipe inspection products have various models and their positions will change when they are transported on the power roller. Due to its high-precision characteristics, the field of view of the 3D camera 2 usually does not cover too much range. We designed the private service electric cylinder 1 to adjust the depth of field of the 3D camera 2 to ensure that the camera can shoot the steel pipe surface at its optimal imaging distance and angle.

[0049] For the detection device, an integral fixing mechanism is added to fix all 3D cameras 2 and the electric cylinder 1, and can move up and down as the diameter of the detection steel pipe 3 changes. And the number of detection devices can be increased or decreased, the minimum number is 4, and there is no upper limit on the number.

[0050] Reference Figure 2 and Figure 3 , the design of the detection method uses 3D structured light to reconstruct the geometric features of the surface of the steel pipe 3 to detect the size, depth and type of surface defects; at the same time, visible light is used to collect two-dimensional images of the surface of the steel pipe 3 to detect the color, texture and other characteristics of the surface. Through the combination of these two technologies, this system realizes comprehensive detection of defects. The 3D structured light detection results are cross-validated by visible light detection to ensure the accuracy and consistency of the detection results, and the detection data is stored in the system.

[0051] During the inspection process, 3D structured light projects a structured grating onto the surface of the steel pipe, and uses the camera of the 3D camera 2 to capture the deformation of the reflected light to generate a three-dimensional model of the steel pipe, and detect the subtle concave and convex changes on the surface of the inspected steel pipe 3. The system uses an algorithm to analyze the reconstructed 3D data, automatically identifies geometric defects such as cracks and dents, and accurately calculates the size and position of the defects. At the same time, the visible light system performs two-dimensional inspection of the steel pipe surface through high-resolution images, identifies surface visual defects such as scratches and uneven colors, and compares them with the inspection data of the 3D structured light to further confirm the type and range of the defects.

[0052] The detection method of the present invention has multiple advantages. First, 3D structured light can accurately model the surface morphology of steel pipes and detect small geometric changes; second, the fused visible light detection supplements the detection of color and texture, ensuring comprehensive coverage of surface defects. In addition, through the cross-validation of the two technologies, the reliability of detection is improved, and the phenomenon of missed detection and false detection is reduced. The system can collect, process and store data in real time, ensuring the efficiency and accuracy of detection.

[0053] In summary, this device and method for detecting surface defects of tubular steel bodies uses 3D structured light technology to accurately detect defects on the surface of steel pipes through three-dimensional reconstruction, overcoming the limitations of traditional detection methods. Compared with 2D visual detection, 3D structured light can not only avoid interference from light and reflection, but also obtain depth information, identify tiny pits and cracks, and improve detection accuracy. Compared with ultrasonic and eddy current detection, 3D structured light uses non-contact detection, which can accurately evaluate the geometric shape of surface defects without causing damage to the steel pipe.

[0054] In addition, the 3D structured light system has efficient automation capabilities, which solves the problem of strong subjectivity and low efficiency of manual inspection and can realize online real-time inspection. Compared with other inspection methods, this technology improves the detection accuracy and reliability of steel pipe surface defects, especially in complex production environments, with strong adaptability.

Claims

1. A device for detecting surface defects of a tubular steel body, characterized in that: The device comprises a steel pipe to be inspected (3), a servo electric cylinder (1) and a 3D camera (2). The 3D camera (2) is arranged outside the steel pipe to be inspected (3). The 3D camera (2) is fixedly connected to the servo electric cylinder (1). The servo electric cylinder (1) is fixed on a device frame. The 3D camera (2) is connected to an offline computing system via wires.

2. The device for detecting surface defects of a tubular steel body according to claim 1, characterized in that: The number of the servo electric cylinders (1) is at least four, which are evenly distributed on the outer circumference of the steel pipe (3) to be inspected, and the end of each servo electric cylinder (1) is connected to a 3D camera.

3. A detection method for the surface defect detection device for a tubular steel body according to claim 1, characterized in that: It includes an online detection system and an offline calculation system, and the online detection system is connected with the offline calculation system.

4. The detection method for a tubular steel body surface defect detection device according to claim 3, characterized in that: The detection method of the online detection system is as follows: Step 1: Synchronous trigger signal: In order to ensure the accuracy and synchronization of the surface defect detection system of the steel pipe (3) being inspected, the system controls the operation of multiple detection devices through a synchronous trigger signal. The signal is based on the moving speed of the steel pipe (3) being inspected to achieve real-time scanning of different positions on the surface of the steel pipe (3) being inspected. The synchronous trigger signal ensures the consistency of the collected data in space and avoids the image or data offset problem caused by time error. Step 2: Multi-threaded data acquisition: Under the control of synchronous trigger signals, the system collects data from multiple cameras and sensors with millisecond accuracy. Multi-threading technology is used to process data input from multiple sensors simultaneously, ensuring real-time and efficient acquisition of large amounts of image data. Each thread processes the data stream independently, ensuring synchronization and stability of data acquisition and processing. Step 3: Multi-camera data fusion: In order to capture the complete three-dimensional information of the surface of the steel pipe (3) being inspected, the system uses multiple 3D cameras (2) to capture data from different angles and integrates these perspective data into a unified 3D model through data fusion technology. Data fusion not only solves the problem that a single 3D camera (2) cannot fully cover the entire area, but also improves the accuracy and completeness of the inspection, especially for complex surface details. Step 4: 3D reconstruction of the steel pipe surface: Based on the data collected by the multiple 3D cameras (2), the system uses a 3D reconstruction algorithm to accurately model the steel pipe surface. By analyzing the multi-view images, a high-precision 3D surface model of the inspected steel pipe (3) is generated to reproduce the surface morphology and geometric features of the inspected steel pipe (3). The 3D model provides a basis for subsequent defect detection and provides intuitive 3D data support for quality evaluation of the inspected steel pipe (3). Step 5: Defect detection calculation: After completing the 3D reconstruction of the surface of the steel pipe (3) to be inspected, the system will automatically perform defect detection on the model. By comparing the actual morphology of the surface of the steel pipe (3) to the preset standard, defects such as cracks, pits, scratches, etc. are detected. The system automatically identifies and classifies different types of defects through algorithms, and calculates the size, depth and position of each defect. Step 6. Defect location recording: When the system detects defects on the surface of the inspected steel pipe (3), it will automatically record the specific location of the defect and store the defect type and severity in the database. This information can be used for subsequent analysis and tracking to ensure the integrity of the defect data and support quality control and improvement in production.

5. The detection method for a tubular steel body surface defect detection device according to claim 3, characterized in that: The detection method of the offline computing system is as follows: Step 1: Camera calibration: In order to ensure the accuracy of the multi-3D camera (2) system, 3D camera (2) calibration is essential. By calibrating the position, focal length and viewing angle of the 3D camera (2), the system can reduce data distortion caused by equipment placement errors and ensure that the data collected by different 3D cameras (2) can be seamlessly integrated in three-dimensional space. Step 2: System calibration: In addition to the calibration of the 3D camera (2), the system calibration further considers the geometric layout of the equipment, measurement accuracy, and external environmental influences. Through calibration, the system can standardize multiple parameters to ensure the detection accuracy and consistency of various hardware in actual operation. Step 3: Detection configuration: The offline computing system integrates the results of the 3D camera (2) calibration and the online detection system calibration into standardized detection configuration files. These configuration files contain the parameters required for system operation, such as the 3D camera (2) calibration data, measurement range, and defect detection threshold, to ensure that the online detection system can continuously and efficiently perform steel pipe surface defect detection.

6. A detection method for a tubular steel body surface defect detection device according to claim 4 or 5, characterized in that: The detection configuration in the third step of the offline computing system is combined with the multi-camera data fusion in the third step of the online detection system.

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