Non-contact disc shear tool defect visual acquisition system and defect detection method

Abstract

The invention relates to the technical field of image acquisition, in particular to a non-contact visual defect acquisition system and defect detection method for disc scissors, comprising an image acquisition device and a control device electrically connected with the image acquisition device; the image acquisition device comprises a camera and an LED stroboscopic lamp, and by combining the stepping distance between acquisition frames and the acquisition position of the camera with the rotation speed of the disc shear tool, the image acquisition rhythm matched with the high-speed rotation of the disc shear tool can be realized, the detailed information of each part of the disc shear tool can be quickly acquired, and the image acquisition efficiency is improved; through matching of the PWM stroboscopic control frequency of the LED stroboscopic lamp and the exposure time of the camera, it is ensured that stable and appropriate illumination intensity and illumination time are provided when the camera is exposed every time, the problems of image blurring, inconsistent brightness and the like caused by uneven illumination or illumination change are solved, and the system is simple in structure, convenient to operate and low in cost. The problems that a traditional disc type cutter is low in detection efficiency, large in error and lagged in detection are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of image acquisition technology, specifically to a non-contact visual acquisition system and defect detection method for disc scissors. Background Technology

[0002] Against the backdrop of accelerated global industrialization, sheet and strip materials, as indispensable basic materials in numerous industrial sectors, are facing increasingly stringent production scales and quality requirements. From high-strength steel sheets used in automobile manufacturing for body structures to ultra-thin copper strips required for precision circuit boards in the electronics industry; from galvanized color-coated sheets widely used in the construction sector to titanium alloy strips with extremely demanding performance requirements in the aerospace industry, sheet and strip materials are ubiquitous. With continuous technological advancements, various industries are placing increasingly stringent standards on the specifications, precision, and surface quality of sheet and strip materials. These standards not only require uniform thickness and good flatness but also place extremely high expectations on edge quality, as edge defects can cause a series of problems during subsequent processing and use, such as affecting welding quality and leading to stress concentration.

[0003] As a core shearing device in the production of sheet and strip steel, the rotary shear plays a crucial role in precisely shearing continuously moving steel plates or strips to predetermined dimensions. Its working principle involves using the relative rotational motion of one or more pairs of disc-shaped blades to continuously shear the moving sheet or strip, thereby obtaining sheet or strip products with the required width and edge quality. The performance of the rotary shear directly affects the production efficiency, product quality, and cost control of sheet and strip steel. On high-speed continuous production lines, the rotary shear must possess stable and reliable operating performance, maintaining precise shearing accuracy and consistent shearing quality under prolonged high-speed operation.

[0004] In existing technologies, manual inspections or periodic shutdown checks are typically performed. Operators conduct visual inspections and simple measurements of the disc shears at regular intervals or during production line shutdowns. They visually inspect the blade surface for obvious defects such as chipping or cracks, and use tools like calipers to measure dimensional parameters such as the blade's diameter and thickness to determine the degree of wear and its condition. This method can detect some obvious blade problems to a certain extent, but because it relies on manual experience and subjective judgment, it suffers from low detection accuracy and a high rate of missed detections. Periodic shutdown checks are a more systematic and comprehensive method for monitoring blade condition. Companies develop regular shutdown maintenance plans based on production plans and blade lifespan, conducting comprehensive disassembly, inspection, and maintenance of the disc shears. During shutdowns, professional maintenance personnel perform detailed inspections, repairs, or replacements of the blades to ensure they operate normally in the next production cycle. While the two inspection methods mentioned above can detect relatively obvious tooling problems to some extent, they both require production line downtime. This not only consumes valuable production time and reduces efficiency, but also fails to provide real-time monitoring of tool status changes during operation. Tooling malfunctions that suddenly occur within a short period are difficult to detect promptly. This lag leads to a large number of defective products being produced before the fault is discovered, resulting in significant material waste and production line downtime. Especially in the processing of thin sheet and strip materials, even minor tooling defects can trigger continuous quality problems. Therefore, a non-contact solution that can monitor tooling status in real time during equipment operation is urgently needed.

[0005] In existing technologies, manual inspections or periodic shutdowns for checks are not only inefficient but also difficult to pinpoint momentary failures. Some automated monitoring solutions rely on multi-camera systems, which suffer from complex installation, high costs, and difficult maintenance, and cannot meet the real-time monitoring needs of high-speed rotating blades. Therefore, developing a vision acquisition system that requires no downtime, offers strong real-time performance, and is easy to install is of great significance for improving the intelligence level and production efficiency of disc shear equipment. Summary of the Invention

[0006] To address the problems of low efficiency, large errors, and delayed detection in traditional disc-type cutting tools, this invention provides a non-contact visual acquisition system and defect detection method for disc-type cutting tools.

[0007] To achieve the above objectives, the present invention employs the following technical solution: This invention provides a non-contact visual acquisition system for defects in disc scissors, including an image acquisition device and a control device electrically connected to the image acquisition device; The image acquisition device includes a camera and an LED strobe light. The camera is equipped with a zoom lens, which is parallel to the circular scissor blade. The LED strobe light is located on the same side as the camera, and the PWM strobe control frequency of the LED strobe light satisfies the following:

[0008] in, This refers to the PWM flicker control frequency for the LED strobe light. For camera exposure time; The inter-frame step distance of the camera satisfies:

[0009] The camera's acquisition position satisfies:

[0010] in, This represents the inter-frame step distance of the camera. The rotational angular velocity of the disc scissors. The camera's acquisition frequency. Let be the circumference of the disc scissors. To collect the location before the update, To collect the updated location; Both the LED strobe light and the camera are connected to a control device.

[0011] Optionally, the device includes a photoelectric sensor disposed on the disc shear assembly for detecting the rotational speed of the disc shears.

[0012] Optionally, the photoelectric sensor is an NPN photoelectric three-wire sensor.

[0013] Optionally, the control device includes a DC power supply and a solid-state relay, a Raspberry Pi, and an optocoupler module connected to the DC power supply; The Raspberry Pi connects to a photoelectric sensor, a camera, and an LED strobe light. It is used to drive the photoelectric sensor to detect the cutting tool rotation speed in real time, acquire the pulse signal from the photoelectric sensor, and control the camera acquisition position, exposure time parameters, and LED strobe light flashing frequency based on the pulse signal from the photoelectric sensor. Both the optocoupler module and the solid-state relay are connected to the Raspberry Pi and are used to work with the Raspberry Pi to reduce the pulse signal of the photoelectric sensor to a safe signal, ensuring that the logic level of the Raspberry Pi is compatible while achieving electrical isolation.

[0014] Optionally, the focal length of the zoom lens satisfies:

[0015] in, The focal length of the zoom lens. This refers to the distance between the zoom lens and the circular scissor. Let be the side length of the camera sensor. This refers to the field of view width of the zoom lens.

[0016] Optionally, when 45rpm≤ When the speed is <150 rpm, the space ratio of the PWM flicker control frequency of the LED strobe light is 50%; when 150 rpm ≤ At speeds <600 rpm, the space ratio of the PWM strobe control frequency of the LED strobe light is 100%.

[0017] Optionally, the camera's shooting range coverage satisfies: The basic area covered by the camera when the disc scissors rotate once is the same size area. satisfy: ,in,

[0018] Zero-crossing handling after the disc scissors complete one revolution: When At that time, it was divided into Two shooting areas; Within the basic shooting range covered by the circular scissors rotating in one revolution, when the camera captures the first... In each coverage area At that time, the camera took the first shot. Each coverage interval is taken as a merged coverage interval satisfy: ; in, Indicates the rotation of the disc scissors. lock up; The starting position of the area covered by the camera when the disc scissors rotates one full circle; The endpoint of the area covered by the camera's view of the disc scissors rotating one full circle; For the rotating disc scissors The last coverage area captured by the camera in the circle; For the rotating disc scissors The starting coverage area captured by the camera in the circle; Indicates the number of shots taken by the camera One coverage area, The first shot taken by the camera The endpoint value of each coverage interval, The first shot taken by the camera The starting value of each coverage interval; The first shot taken by the camera Each coverage interval endpoint value, The first shot taken by the camera The starting value of each coverage interval.

[0019] Optionally, it also includes an adjustable bracket, on which both the camera and the LED strobe light are mounted.

[0020] Optionally, the adjustable bracket includes a base, on which a support rod is rotatably connected. A first adjustment rod, a second adjustment rod, and a mounting plate are sequentially hinged to the support rod, and the camera and LED strobe light are mounted on the mounting plate.

[0021] A non-contact method for detecting defects in disc scissors using the aforementioned non-contact visual acquisition system for disc scissor defects includes: Obtain the rotational speed and circumference of the disc shears; Based on the rotational speed and circumference of the disc scissors, the image acquisition parameters of the image acquisition device are controlled by the control device, and image acquisition is performed; the image acquisition parameters include camera acquisition position, exposure time parameters, coverage area, and the flashing frequency and spatial occupancy of the LED strobe light; Image analysis was performed on the acquired images to obtain the defect detection results of the non-contact disc scissors.

[0022] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a non-contact visual acquisition system for defects in disc scissors, comprising an image acquisition device and a control device electrically connected to the image acquisition device. The image acquisition device includes a camera and an LED strobe light. By combining the camera's inter-frame step distance and acquisition position with the rotation speed of the disc scissors, an image acquisition rhythm matching the high-speed rotation of the disc scissors can be achieved, quickly acquiring detailed information about various parts of the disc cutter and improving image acquisition efficiency. Matching the PWM strobe control frequency of the LED strobe light with the camera's exposure time ensures stable and appropriate light intensity and duration during each camera exposure, avoiding problems such as image blurring and inconsistent brightness caused by uneven or changing illumination. This ensures the clarity and accuracy of the acquired images, providing a reliable data foundation for subsequent defect judgment and analysis, and reducing detection errors caused by image quality issues. The camera is equipped with a zoom lens, which is parallel to the disc scissors. The zoom lens can adjust its focal length according to actual detection needs, ensuring clear cutter images are obtained at different distances. The parallel installation method ensures consistent image acquisition perspective, allowing the acquired images to accurately reflect the actual condition of the tool surface. This reduces detection errors caused by perspective deviations or inaccurate focusing, improving the accuracy of defect detection. Finally, the control device connects to the image acquisition device to receive image data from the camera in real time. Based on preset algorithms and standards, the images are analyzed to quickly determine if the tool has defects. Once a defect is detected, the control device immediately sends a signal, providing real-time feedback on the detection results. This real-time control and feedback mechanism allows inspectors to understand the tool's status promptly, avoiding the delays in result transmission that may exist in traditional inspection methods. This high-speed data processing and transmission capability ensures efficient inspection, reduces detection lag time, and improves the real-time performance of the entire inspection system. The device has a simple structure and effectively solves the problems of low efficiency, large errors, and detection lag in traditional disc-type tool inspection, providing a more efficient, accurate, and real-time solution for the quality inspection of disc-type shears.

[0023] This includes a photoelectric sensor mounted on the disc shear assembly to detect the rotational speed of the disc shear. The photoelectric sensor detects the rotational speed of the disc shear in real time, and the camera is adjusted according to the real-time rotational speed detected by the photoelectric sensor. This ensures that the camera's acquired parameters are closely matched with the actual movement state of the cutter, thereby ensuring that the acquired images can clearly and accurately reflect the true situation of each part of the cutter during the rotation process, avoiding image blurring or omission of key parts, and improving the accuracy of defect detection.

[0024] The photoelectric sensor is an NPN three-wire photoelectric sensor. The NPN three-wire photoelectric sensor can generate a rotational speed signal by detecting the light pulses reflected from the cutting tool. This clear rotational speed signal output method allows the control device to accurately and reliably identify the sensor's state, avoiding misjudgments caused by signal ambiguity or vagueness, ensuring stable transmission of the rotational speed detection signal, and providing a solid foundation for subsequent operations such as adjusting image acquisition parameters based on rotational speed.

[0025] The control device includes a DC power supply and a solid-state relay, a Raspberry Pi, and an optocoupler module connected to the DC power supply. The Raspberry Pi, as the core of the control device, can simultaneously connect to a photoelectric sensor, a camera, and an LED strobe light, enabling centralized control of the entire vision acquisition system. This highly integrated design reduces the number of control components in the system, simplifies the system architecture, and makes system installation, debugging, and maintenance more convenient and faster. Simultaneously, the Raspberry Pi can drive the photoelectric sensor to detect the tool rotation speed in real time and quickly acquire the pulse signal output by the photoelectric sensor. Based on this real-time data, the Raspberry Pi can precisely control the camera's acquisition position and exposure time parameters, as well as the LED strobe light's flash frequency. This real-time control capability ensures a high degree of synchronization between image acquisition and tool movement, enabling the acquired image to clearly and accurately reflect the actual state of the tool during rotation, providing a high-quality data foundation for subsequent defect detection. For example, when the tool rotation speed changes, the Raspberry Pi can immediately adjust the camera parameters to ensure that image quality is not affected. The optocoupler module can electrically isolate the pulse signal output by the photoelectric sensor and convert the signal level into a safe signal compatible with the Raspberry Pi's logic level. This electrical isolation effectively prevents interference signals such as high voltage and high current from the photoelectric sensor side from damaging the Raspberry Pi, improving the system's reliability and stability. Solid-state relays further enhance signal processing reliability; under the control of the Raspberry Pi, they can safely switch circuit connections, ensuring stable system operation under various conditions.

[0026] Determining the focal length by considering the distance between the zoom lens and the circular scissors, the side length of the camera sensor, and the field of view of the zoom lens ensures that the field of view captured by the lens precisely and completely covers the area of ​​the circular scissors that needs to be inspected. This avoids both excessively large fields of view that include too much irrelevant information, leading to image redundancy and increased data processing burden, and excessively small fields of view that miss critical parts of the tool. This guarantees the completeness and specificity of image acquisition, laying the foundation for accurate defect detection. Simultaneously, a suitable focal length ensures clear and sharp imaging on the camera sensor, forming a clear image, reducing image blurring and distortion, improving defect identifiability, and facilitating subsequent image analysis and processing.

[0027] When 45rpm≤ When the speed is <150 rpm, the space ratio of the PWM flicker control frequency of the LED strobe light is 50%; when 150 rpm ≤ At speeds <600 rpm, the space ratio of the PWM strobe control frequency of the LED strobe lamp is 100%. Using different space ratios of PWM strobe control frequencies at different speeds can ensure the continuous stability of the light source within the exposure window, avoid brightness fluctuations caused by low-frequency flicker, prevent a surge in image noise due to low exposure, reduce image blurring caused by the disc scissors during cutting motion, reduce the heat power of the bulb, and improve its lifespan. At the same time, it can ensure that high-speed moving targets still receive sufficient illumination under short exposure times.

[0028] By dynamically matching the camera's shooting range coverage conditions with the disc scissors, the system can find the optimal sampling frequency through adaptive matching of rotational speed changes, effectively shortening the complete acquisition time of the tool surface, ensuring no omissions in tool surface coverage under full rotational speed conditions, and always completing acquisition in the theoretically shortest time, effectively avoiding the problem of poor detection reliability caused by time redundancy or missed detection risks.

[0029] The adjustable bracket not only provides reliable support for the camera and LED strobe light, but also enables multi-dimensional flexible adjustment of the camera, ensuring that the camera can capture the best angle image of the tool, and the strobe light can provide the most effective illumination.

[0030] This invention also provides a non-contact method for detecting defects in disc scissors using the aforementioned non-contact visual acquisition system. This method acquires the rotational speed and circumference of the disc scissors; then, based on the rotational speed and circumference, a control device controls the image acquisition parameters of the image acquisition device and acquires images. The image acquisition parameters include camera acquisition position, exposure time, coverage area, LED strobe frequency, and spatial occupancy. Finally, image analysis is performed on the acquired images to obtain the non-contact disc scissors defect detection result. This method can acquire the scissor rotational speed information in real time and quickly adjust the image acquisition parameters according to changes in rotational speed. When the scissor rotational speed fluctuates, the control device can immediately adjust parameters such as camera acquisition position, exposure time, and strobe frequency to ensure that image acquisition is always synchronized with the movement of the scissors. The entire detection process is highly automated, with each step closely integrated, requiring no manual intervention. This not only improves detection speed but also reduces the impact of human factors on the detection results, ensuring the stability and consistency of the detection. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the installation state structure of a non-contact disc scissor defect visual acquisition system according to the present invention.

[0032] Figure 2 This is a structural diagram of the acquisition device of a non-contact visual acquisition system for disc scissors defects according to the present invention.

[0033] Figure 3 This is a structural diagram of the control device for a non-contact disc scissor defect visual acquisition system according to the present invention.

[0034] Figure 4 This is a comparison chart showing the trend of image sharpness scores between images captured by a camera when the PWM strobe control frequency of the LED strobe light is controlled by the present invention and when the strobe light is kept constantly on.

[0035] Figure 5 A comparison of six-dimensional clarity under different PWM flicker control frequency settings.

[0036] Figure 6 This is a discrete graph comparing the time of the fixed sampling coverage interval with the dynamic coverage interval adjustment of the present invention.

[0037] Figure 7 This is a schematic diagram illustrating the process of a non-contact disc scissor defect detection method using a non-contact disc scissor defect visual acquisition system according to the present invention.

[0038] Among them, 1-photoelectric sensor, 2-disc shear assembly, 3-disc shears, 4-image acquisition device, 5-cable, 6-control device, 7-LED strobe light, 8-camera, 9-zoom lens, 10-fixing device, 11-adjustable bracket, 111-base, 112-support rod, 113-first adjustment rod, 114-second adjustment rod, 115-mounting plate, 61-DC power supply, 62-solid-state relay, 63-Raspberry Pi, 64-optocoupler module. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0040] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0041] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0042] In the description of the embodiments of the present invention, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0043] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0044] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention according to the specific circumstances.

[0045] The present invention will be further described in detail below with reference to specific embodiments. These descriptions are for explanation purposes only and are not intended to limit the scope of the invention.

[0046] See Figure 1 The present invention discloses a non-contact visual acquisition system for defects in disc scissors, including an image acquisition device 4, a control device 6 electrically connected to the image acquisition device 4, an adjustable bracket 5 connected to the image acquisition device 4, and a photoelectric sensor 1 disposed on the disc scissor assembly device 2. See Figure 2 The image acquisition device 4 includes a camera 8 and an LED strobe light 7. Both the LED strobe light 7 and the camera 8 are connected to the control device 6 via cables 5. The camera 8 is a micro-snow global shutter camera equipped with a zoom lens 9, acquiring images of the surface of the disc scissors 3 using direct illumination. The zoom lens 9 is parallel to the disc scissors 3, and the LED strobe light 7 and the camera 8 are located on the same side. Furthermore, the PWM strobe control frequency of the LED strobe light 7 satisfies the following:

[0047] in, This refers to the PWM flicker control frequency of the LED strobe light 7. For camera 8, the exposure time is 8. The inter-frame step distance of the camera 8 satisfies:

[0048] Duty cycle is a core parameter in PWM flicker control frequency, representing the proportion of high-level time within one cycle, and directly affecting the average power of the output signal. The larger the light intensity, the greater the average light intensity perceived by the human eye, and the brighter the image. Due to the change in mechanical rotation speed of the disc scissors 3 from low to high speed, the PWM flicker control frequency is limited by the hardware. Unable to achieve the high frequency of the disc scissors 3 during the high-speed phase, the lighting strategy needs to be dynamically adjusted in conjunction with real-time monitoring of the rotation speed. When 45rpm≤ At speeds <150 rpm, the space ratio of the PWM flicker control frequency of the LED strobe light 7 is 50%. Experiments have verified that the PWM frequency... 1kHz, duty cycle The exposure time is 50. 2ms, PWM frequency With exposure time The settings ensure a stable light source within the exposure window, preventing brightness fluctuations caused by low-frequency flicker; prevent a surge in image noise due to low exposure; reduce image blurring caused by the cutting motion of the disc scissors; and reduce the heat power of the bulb, extending its lifespan.

[0049] When 150rpm≤ At speeds <600 rpm, the spatial occupancy of the PWM strobe control frequency of the LED strobe light 7 is 100%. By eliminating motion blur in high-speed images with low camera light intake through low exposure time, the PWM duty cycle is increased to 100%, ensuring that high-speed moving targets still receive sufficient illumination even with short exposure times.

[0050] In the rapidly rotating disc scissors 3, in order to prevent losses caused by missed detections during camera acquisition, the status of the disc scissors 3 needs to be detected in real time. The non-contact disc scissors 3 surface is acquired with dynamic step coverage to ensure that the complete disc scissors surface is acquired in the shortest time.

[0051] The acquisition position of the camera 8 satisfies:

[0052] in, The inter-frame step distance for camera 8. The rotational angular velocity of the disc scissors 3 is... The sampling frequency of camera 8, Let 3 be the circumference of the disc scissors. To collect the location before the update, To collect the updated location; The basic area covered by the circular scissor-like tool rotating three times in one revolution. satisfy: ,in,

[0053] Zero-crossing handling after the disc scissors complete one revolution: When At that time, it was divided into Two shooting areas; Within the basic shooting range covered by the circular scissors tool 3 rotating once, when camera 8 takes the first shot... In each coverage area At that time, the 8th shot was taken by camera. Each coverage interval is taken as a merged coverage interval satisfy: ; in, This indicates that the disc scissors rotated 3 times. lock up; The starting position of the area covered by the camera 8 after the disc scissors 3 rotates one full circle; The endpoint of the area covered by the camera 8 is captured by rotating the disc scissors 3 one full revolution; For the disc scissors, rotate 3rd time The last coverage area captured by camera 8 in the circle; For the disc scissors, rotate 3rd time The initial coverage area captured by camera 8 in the circle; Indicates the 8th shot taken by camera 8 One coverage area, The first shot taken by camera 8 The endpoint value of each coverage interval, The first shot taken by camera 8 The starting value of each coverage interval; The first shot taken by camera 8 Each coverage interval endpoint value, The first shot taken by camera 8 The starting value of each coverage interval.

[0054] The focal length of the zoom lens 9 satisfies:

[0055] in, The focal length of zoom lens 9. The distance between the zoom lens 9 and the disc scissors 3. The side length of the camera's 8 sensors. This refers to the field of view of the zoom lens 9; for example, for safety and to detect minute defects in the blade, the object distance between the camera and the disc scissors 3 in actual operation... The field of view of the camera (8) is controlled within 10-20cm. The focal length is calculated using the formula above, with a focal length controlled between 3 and 5 cm and a camera sensor diagonal length of 6.3 mm. The focal length range is 12.6–44mm, and a zoom lens of 8–50mm is selected.

[0056] See Figure 3 The control device 6 includes a DC power supply 61 and a solid-state relay 62, a Raspberry Pi 63, and an optocoupler module 64 connected to the DC power supply 61. The Raspberry Pi 63 connects to a photoelectric sensor 1, a camera 8, and an LED strobe light 7. It is used to drive the photoelectric sensor 1 to detect the tool rotation speed in real time, acquire the pulse signal of the photoelectric sensor 1, and control the camera 8 to acquire position, exposure time parameters, and LED strobe light 7 strobe frequency according to the pulse signal of the photoelectric sensor 1. The photoelectric sensor 1 is an NPN photoelectric triwire sensor used to detect the rotational speed of the disc scissors 3. The optocoupler module 64 and the solid-state relay 62 are both connected to the Raspberry Pi 63 and are used to work with the Raspberry Pi 63 to reduce the pulse signal of the photoelectric sensor 1 to a safe signal, ensuring that the logic level of the Raspberry Pi 63 is compatible while achieving electrical isolation.

[0057] The Raspberry Pi 63 processes pulse signals through signal conditioning circuitry. It utilizes the dynamic step-size coverage algorithm described in the formula above: based on the circumference and angular velocity of the disc shears 3 and the sampling frequency of the camera 8, it dynamically adjusts the camera 8 parameters using inter-frame displacement formulas, position update calculations, and interval merging strategies to ensure complete surface acquisition without omissions in the shortest possible time. For synchronization control, the Raspberry Pi 63 employs a PWM-based dynamic adjustment strategy for the LED strobe light 7: at low speeds, it uses 1kHz and a 50% duty cycle to suppress image flicker and improve image quality; at high speeds, it switches to a 100% constant-on mode with a 30-microsecond short exposure to improve motion blur. The Raspberry Pi 63 connects to a host PC, which remotely controls the Raspberry Pi 63 via SSH / VNC and transmits data using SCP / SFTP protocols. The PC performs high-load image processing and storage, meeting the real-time defect detection requirements in high-speed cutting scenarios. The specific remote control and data transmission methods for the PC are as follows: SSH is a protocol used to securely access remote computers over insecure networks. VNC provides a graphical user interface for remotely accessing a Raspberry Pi 63. nmap is an IP scanning tool; the command `nmap -sn 192.168.1.0 / 24` can be used to find the IP addresses of the Raspberry Pi 63 and the PC on the local network. To connect to the Raspberry Pi 63 via SSH and VNC Viewer, open a terminal on the Raspberry Pi 63 and type `sudo raspi-config`. Select "Interfacing Options," then click "SSH" and "VNC," and select "Enable." Enter the Raspberry Pi 63's IP address found by nmap and its hostname in the VNC Viewer to establish a remote connection.

[0058] The data transfer method using SCP and SFTP servers is as follows: SCP is a secure file transfer protocol based on SSH. SFTP is a file transfer protocol based on SSH; simply enter the PC's IP address, username, and password to transfer image data acquired by the Raspberry Pi 63 to the PC. By offloading computational tasks to the PC, the Raspberry Pi 63 does not need to perform high-load computations, thus avoiding system lag, overheating, or misjudgments caused by limited computing resources. Simultaneously, the PC can utilize more powerful GPUs and CPUs for parallel computing, improving detection speed; the Raspberry Pi transmits images over the network, and the PC can simultaneously store the data and leverage big data analysis and model optimization to improve detection results.

[0059] The adjustable bracket 11 includes a base 111, on which a support rod 112 is rotatably connected. A first adjustment rod 113, a second adjustment rod 113, and a mounting plate 114 are sequentially hinged on the support rod 112. The camera 8 and the LED strobe light 7 are mounted on the mounting plate 114 and fixed by a fixing device 10.

[0060] This visual acquisition system for defects in a disc shear tool employs dynamic step-size coverage precision control, using a Raspberry Pi 63 to drive a high-speed industrial camera 8. This system accurately captures a sequence of images of the disc shear tool 3's surface during high-speed rotation, ensuring no blurring or omissions. Based on real-time monitoring of the disc shear tool 3's rotational speed and geometric parameters, the system dynamically optimizes the camera's shooting position and frame rate, ensuring full coverage acquisition of the entire circumference of the tool in the shortest possible time. Simultaneously, the dynamic adjustment of the PWM strobe illumination strategy effectively overcomes the imaging challenges posed by high-speed motion, significantly improving image clarity and signal-to-noise ratio. The Raspberry Pi 63 then transmits the acquired optimal frame rate video stream through... The command efficiently extracts a structured sequence of images. This process constructs a high-quality, high-coverage tool surface image dataset, laying a solid and reliable data foundation for subsequent deep learning training, defect detection model development, and real-time online image analysis on a host PC. Compared to traditional multi-camera surround solutions, this system uses a single high-speed industrial camera to cover the entire tool surface, reducing camera procurement costs. The Raspberry Pi serves as the control center, replacing an expensive industrial PC and further reducing hardware expenses. Furthermore, traditional multi-camera systems require precise calibration of the positions and angles of multiple cameras, resulting in complex installation and high maintenance costs. The single-camera Raspberry Pi solution only requires adjustment of the universal bracket, significantly reducing installation and debugging time.

[0061] See Figure 4 and Figure 5 To comprehensively evaluate the effectiveness of flicker reduction technology, a multi-dimensional sharpness evaluation method was adopted. Using a static sharpness image as the baseline of 100, the average sharpness score for a moving, constantly lit image was 37.7, while the average score for a moving, flickering image reached 64.2. Furthermore, Figure 5 The sharpness performance of three image states was compared from six dimensions using radar charts. The results show that the flicker adjustment of the present invention is superior to that of the LED 7 in the motion-on state in all indicators, including Brenner, Tenengrad, SMD, Robert gradient, and frequency domain energy (FDE), confirming the comprehensive effectiveness of the technology and fully demonstrating the effectiveness and practicality of flicker improvement technology in enhancing image sharpness.

[0062] See Figure 6 By comparing the time discreteness of the fixed coverage step size and the dynamic step size coverage adjustment of the present invention, it was found that the system can ensure that the tool surface is covered without omission under full speed conditions and always completes the acquisition in the theoretical shortest time.

[0063] See Figure 7 The present invention also provides a non-contact method for detecting defects in disc scissors using the aforementioned non-contact disc scissor defect visual acquisition system, comprising: Obtain the rotational speed and circumference of the disc shears 3; Based on the rotational speed and circumference of the disc scissors 3, the control device 6 controls the image acquisition parameters of the image acquisition device 4 and performs image acquisition; the image acquisition parameters include the acquisition position of the camera 8, exposure time parameters, coverage area, and the flashing frequency and spatial proportion of the LED strobe light 7. Image analysis was performed on the acquired images to obtain the defect detection results of the non-contact disc scissors.

[0064] Under the real-time precise control of the dynamic step-size coverage algorithm, this method can accurately capture unblurred and complete serialized images of the surface of the disc shear tool 3 during high-speed rotation. Based on real-time monitoring of the tool's rotation speed and geometric parameters, the camera's shooting position and frame rate are dynamically optimized to ensure full coverage acquisition of the entire circumference of the tool in the shortest possible time. Simultaneously, the dynamic adjustment of the PWM strobe illumination strategy effectively overcomes the imaging challenges posed by high-speed motion, significantly improving image clarity and signal-to-noise ratio. The optimal frame rate video stream is then captured using a Raspberry Pi and transmitted via... The command efficiently extracts a structured sequence of images, enabling the construction of a high-quality, high-coverage dataset of images of the three surfaces of a disc scissors. This lays a solid and reliable data foundation for subsequent deep data training, defect detection model development, and real-time online image analysis on a host PC.

[0065] In summary, this invention provides a non-contact visual acquisition system and defect detection method for disc scissors. By dynamically matching the real-time rotation speed of the disc scissors 3 to control the coverage step size of the camera 8, the sampling position and frequency are automatically optimized. This ensures no blind spots covering the tool surface under high-speed rotation and dynamically adjusts camera parameters and algorithm thresholds to quickly adapt to tools of different sizes. Through the strobe control LED strobe light 7 imaging technology, which is adaptive to the exposure time of the camera 8, it can stably capture minute defects such as chipped edges and cracks in the complex conditions of continuous strip cutting, preventing strip breakage accidents caused by missed detections. The photoelectric sensor signal is isolated and level-converted to resist electromagnetic interference and voltage fluctuations in the workshop, ensuring stable rotation speed feedback. A Raspberry Pi 63 is remotely controlled by a host computer, allowing the Raspberry Pi 63 to focus on real-time acquisition and control, avoiding resource overload. High-resolution images are remotely processed on the PC to achieve millisecond-level defect recognition. This allows for long-term stable operation in high-temperature, high-noise industrial environments, reducing downtime losses due to false alarms. The system and defect detection method provided by this invention are also applicable to defect detection or image acquisition of other disc-type mechanical structures.

[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the technical solution of the present invention in any way. Those skilled in the art should understand that, without departing from the spirit and principles of the present invention, the technical solution can be modified and replaced in several simple ways, and these modifications and replacements are all within the scope of protection covered by the claims.

Claims

1. A non-contact visual acquisition system for defects in disc scissors, characterized in that, Includes an image acquisition device and a control device electrically connected to the image acquisition device; The image acquisition device includes a camera and an LED strobe light. The camera is equipped with a zoom lens, which is parallel to the circular scissor blade. The LED strobe light is located on the same side as the camera, and the PWM strobe control frequency of the LED strobe light satisfies the following: in, This refers to the PWM flicker control frequency for the LED strobe light. For camera exposure time; The inter-frame step distance of the camera satisfies: The camera's acquisition position satisfies: in, This represents the inter-frame step distance of the camera. The rotational angular velocity of the disc scissors. The camera's acquisition frequency. Let be the circumference of the disc scissors. To collect the location before the update, To collect the updated location; Both the LED strobe light and the camera are connected to a control device.

2. The non-contact disc scissor defect visual acquisition system according to claim 1, characterized in that, This includes a photoelectric sensor mounted on the disc shear assembly for detecting the rotational speed of the disc shears.

3. The non-contact disc scissor defect visual acquisition system according to claim 2, characterized in that, The photoelectric sensor is an NPN three-wire photoelectric sensor.

4. The non-contact disc scissor defect visual acquisition system according to claim 2 or 3, characterized in that, The control device includes a DC power supply and a solid-state relay, a Raspberry Pi, and an optocoupler module connected to the DC power supply. The Raspberry Pi connects to a photoelectric sensor, a camera, and an LED strobe light. It is used to drive the photoelectric sensor to detect the cutting tool rotation speed in real time, acquire the pulse signal from the photoelectric sensor, and control the camera acquisition position, exposure time parameters, and LED strobe light flashing frequency based on the pulse signal from the photoelectric sensor. Both the optocoupler module and the solid-state relay are connected to the Raspberry Pi and are used to work with the Raspberry Pi to reduce the pulse signal of the photoelectric sensor to a safe signal, ensuring that the logic level of the Raspberry Pi is compatible while achieving electrical isolation.

5. The non-contact disc scissor defect visual acquisition system according to claim 1, characterized in that, The focal length of the zoom lens satisfies: in, The focal length of the zoom lens. This refers to the distance between the zoom lens and the circular scissor. Let be the side length of the camera sensor. This refers to the field of view width of the zoom lens.

6. The non-contact visual acquisition system for disc scissors defects according to claim 1, characterized in that, When 45rpm≤ When the speed is <150 rpm, the space ratio of the PWM flicker control frequency of the LED strobe light is 50%; when 150 rpm ≤ At speeds <600 rpm, the space ratio of the PWM strobe control frequency of the LED strobe light is 100%.

7. The non-contact circular scissor defect visual acquisition system according to claim 1, characterized in that, The camera's shooting range coverage satisfies: The basic area covered by the camera when the disc scissors rotate once is the same size area. satisfy: ,in, Zero-crossing handling after the disc scissors complete one revolution: When At that time, it was divided into Two shooting areas; Within the basic shooting range covered by the circular scissors rotating in one revolution, when the camera captures the first... In each coverage area At that time, the camera took the first shot. Each coverage interval is taken as a merged coverage interval satisfy: ； in, Indicates the rotation of the disc scissors. lock up; The starting position of the area covered by the camera when the disc scissors rotates one full circle; The endpoint of the area covered by the camera's view of the disc scissors rotating one full circle; For the rotating disc scissors The last coverage area captured by the camera in the circle; For the rotating disc scissors The starting coverage area captured by the camera in the circle; Indicates the number of shots taken by the camera One coverage area, The first shot taken by the camera The endpoint value of each coverage interval, The first shot taken by the camera The starting value of each coverage interval; The first shot taken by the camera Each coverage interval endpoint value, The first shot taken by the camera The starting value of each coverage interval.

8. The non-contact disc scissor defect visual acquisition system according to claim 1, characterized in that, It also includes an adjustable bracket, on which both the camera and the LED strobe light are mounted.

9. The non-contact circular scissor defect visual acquisition system according to claim 8, characterized in that, The adjustable bracket includes a base, on which a support rod is rotatably connected. A first adjustment rod, a second adjustment rod, and a mounting plate are sequentially hinged to the support rod. The camera and LED strobe light are mounted on the mounting plate.

10. A non-contact method for detecting defects in disc scissors using the non-contact visual acquisition system for disc scissor defects according to any one of claims 1-9, characterized in that, include: Obtain the rotational speed and circumference of the disc shears; Based on the rotational speed and circumference of the disc scissors, the image acquisition parameters of the image acquisition device are controlled by the control device, and image acquisition is performed; the image acquisition parameters include camera acquisition position, exposure time parameters, coverage area, and the flashing frequency and spatial occupancy of the LED strobe light; Image analysis was performed on the acquired images to obtain the defect detection results of the non-contact disc scissors.

Images