Plasma cutting system and cutting control method

Abstract

The invention belongs to the technical field of image recognition, and particularly provides a plasma cutting system and a cutting control method.The plasma cutting system comprises robot cutting equipment, and a cutting gun is arranged on the robot cutting equipment in a matched mode; the robot cutting device comprises a robot cutting device and further comprises a mounting frame, the robot cutting device is fixedly arranged on the lower surface of the mounting frame, a visual sensor module fixedly connected with the mounting frame is arranged on one side of the robot cutting device, and the robot cutting device is connected with the visual sensor module; the visual sensor module captures image information of a cutting path of a cutting target in real time, carries out obstacle recognition on a cutting track and inputs a recognition result to the robot cutting equipment, and the robot cutting equipment controls the cutting action of the robot cutting equipment according to the recognition result; and the visual sensor module also detects the cut workpiece, and outputs prompt information when detecting that the workpiece is unqualified. And rapid detection of obstacles in a cutting track and size deviation after cutting is completed is realized.

Description

Technical Field

[0001] The present invention relates to the field of image recognition technology, and in particular to a plasma cutting system and a cutting control method. Background Art

[0002] With the development of lightweight automobiles, integrated die-casting of automobile bodies will lead a new revolution in automobile body manufacturing. In particular, integrated die-casting of the front and rear floor panels of automobiles is being gradually promoted in the automobile manufacturing industry. As for the removal of the material handle of the integrated die-casting parts of the front and rear floor panels, domestic die-casting manufacturers usually use robot plasma cutting to achieve the full removal of the material handle.

[0003] In the actual production process, there are two main problems with robot plasma cutting of die casting handles. First, if there are obstacles on the robot plasma cutting path that are not identified and cleared in advance, the cut handle will hit the obstacle and damage the cutting gun. Second, after the robot plasma cuts the handle, the cut workpiece may have dimensional deviations. Manual inspection may miss or misdetect. If it is not detected in a timely and effective manner, it will often lead to batch scrapping of workpieces with out-of-tolerance dimensions. Summary of the invention

[0004] In view of the problems existing in robot plasma cutting, the present invention provides a plasma cutting system and a cutting control method.

[0005] In a first aspect, the technical solution of the present invention provides a plasma cutting system, comprising a robot cutting device, wherein the robot cutting device is provided with a cutting gun; and further comprising a mounting frame, wherein the robot cutting device is fixedly arranged on a lower surface of the mounting frame, a visual sensor module is arranged on one side of the robot cutting device, and the visual sensor module is fixedly connected to the mounting frame, and the robot cutting device is in communication connection with the visual sensor module; The visual sensor module is used to capture the image information of the cutting path of the cutting target in real time, identify obstacles on the cutting trajectory and input the identification results to the robotic cutting device, and the robotic cutting device controls its own cutting action according to the identification results; the visual sensor module also detects the workpiece after cutting and outputs a prompt message when it detects that the workpiece is unqualified.

[0006] The visual sensor module can continuously monitor the surrounding environment during the cutting process, promptly detect and identify obstacles that may affect cutting safety, thereby effectively avoiding collisions between the cutting gun and obstacles, reducing the risk of equipment damage and accidents, and improving the safety of the work site. The system is not limited to obstacle avoidance during the cutting process, but can also perform quality inspections on workpieces after cutting. Once a workpiece is found to have quality problems or does not meet specification requirements, the visual sensor module can immediately output prompt information, allowing operators to take timely measures to correct or reprocess, ensuring the consistency and stability of product quality.

[0007] The plasma cutting system provided by the technical solution of the present invention realizes the intelligent, automated and efficient cutting operation by integrating the visual sensor module, significantly improves the cutting accuracy, efficiency and safety, reduces the production cost and labor intensity, and injects new vitality into the development of modern manufacturing industry.

[0008] As a preferred embodiment of the technical solution of the present invention, a PLC controller is provided in the robot cutting device, and the PLC controller is communicatively connected with the visual sensor module via the PROFINET communication protocol, and the visual sensor module inputs the detection result to the PLC controller.

[0009] As a preferred embodiment of the technical solution of the present invention, the visual sensor module includes an image acquisition unit, a first processing unit and a second processing unit; An image acquisition unit is used to capture the image information of the cutting path of the cutting target in real time and mark the captured image information of the cutting path as an identification image and transmit it to the first processing unit; it is also used to collect the image information of the workpiece after cutting, mark the image information of the workpiece after cutting as a size verification image and transmit it to the second processing unit; The first processing unit is used to compare the image information marked as the recognition image with the pre-stored image with the obstacle marked, and perform obstacle recognition and positioning processing on the compared image information with the obstacle, and input the processing result to the PLC controller; The second processing unit is used to compare the image information marked as the size verification image with the stored standard size workpiece image, and output a size qualified reminder message when the comparison is consistent, and output a size unqualified reminder message when the comparison is inconsistent.

[0010] By subdividing the visual sensor module into an image acquisition unit, a first processing unit, and a second processing unit, a refined processing flow of image information is realized. The image acquisition unit is responsible for capturing the cutting path and workpiece image in real time and accurately, providing a high-quality data source for subsequent processing. The first processing unit and the second processing unit focus on obstacle recognition and size verification respectively, and significantly improve the efficiency and accuracy of image processing through parallel processing.

[0011] As a preferred embodiment of the technical solution of the present invention, the first processing unit performs contrast enhancement processing on the acquired image, adopts a grayscale difference method based on edge image pixels to extract the contour of the image, and realizes the extraction of obstacle edge features in the image by clearing the pixels wrapped by the image edge and retaining the image contour; uses a Gabor wavelet filter to extract obstacle features, completes the positioning of the obstacle shape and position, and inputs the processing results into the PLC controller.

[0012] The first processing unit firstly improves the image quality by contrast enhancement processing on the acquired image, making the boundary between the obstacle and the background clearer. Subsequently, the grayscale difference method based on edge image pixels is used to extract the image contour, and the internal pixels of the image edge are cleared, retaining only the contour information. This processing method greatly highlights the edge features of the obstacle, providing a more accurate data basis for subsequent feature extraction and recognition. The obstacle feature extraction is further performed using the Gabor wavelet filter, which can accurately capture the shape and position information of the obstacle, thereby significantly improving the accuracy of obstacle recognition. The grayscale difference method based on edge image pixels and the Gabor wavelet filter have high computational efficiency in image processing. The first processing unit uses these methods to process the image, and can complete the extraction and recognition of obstacle features in a short time, ensuring the real-time nature of obstacle recognition. This is particularly important for cutting operations that require fast response and dynamic adjustment, and can avoid cutting deviations or safety accidents caused by recognition delays.

[0013] As a preferred embodiment of the technical solution of the present invention, the first processing unit filters the texture of the collected image through a Gabor wavelet filter to perform digital signal conversion; decomposes the transformed digital signal into a set of wavelet functions, and improves the resolution of the image in the time and space domain and the frequency domain through conversion factors and expansion factors; during filtering, the output of the Gabor wavelet filter is an output adjustment of the average convolution of the real and virtual filter masks of all convolution pixels in the image.

[0014] As a preferred embodiment of the technical solution of the present invention, the second processing unit determines the image edge based on the grayscale changes on both sides of the image edge, connects the edges, and performs distance measurement based on the position coordinates of the pixel points to determine the image size of the cut workpiece and compare it with the standard workpiece image size; wherein the pixels of the standard workpiece image and the cut workpiece image are the same.

[0015] The second processing unit accurately identifies the edge of the image and determines the edge position based on the grayscale changes on both sides of the edge. This method can effectively reduce the impact of edge blur or noise on the measurement results. Subsequently, by connecting the edges and using the position coordinates of the pixel points for distance measurement, the image size of the cut workpiece is accurately measured. Since the pixels of the standard workpiece image and the cut workpiece image are consistent, this pixel-level comparison method further improves the accuracy of the size measurement and ensures the accuracy and reliability of the measurement results.

[0016] Through precise dimension measurement and comparison, the second processing unit can timely detect the deviation between the cut workpiece and the standard size. Once a defective product is found, the system will output a prompt message to remind the operator to deal with it. This real-time quality control mechanism helps to ensure the consistency of product quality, reduce the defective rate, and improve customer satisfaction.

[0017] As a preferred embodiment of the technical solution of the present invention, the system also includes a host computer, which is connected to the robot cutting equipment and the visual sensor module via a wireless network to achieve the functions of remotely monitoring the cutting process, adjusting cutting parameters and receiving real-time feedback data.

[0018] By introducing a host computer and establishing a wireless network connection with the robot cutting equipment and the visual sensor module, operators can monitor the cutting process in real time from a location far away from the production site. This remote monitoring capability makes production management more convenient, no longer restricted by geographical location, and improves the flexibility and efficiency of production management.

[0019] Through remote monitoring and real-time feedback mechanisms, the host computer can promptly detect safety hazards and abnormal situations in the production process, such as equipment failure, operating errors, etc. Once a problem is found, the operator can immediately take measures to deal with it, thereby avoiding accidents and improving production safety.

[0020] As a preferred embodiment of the technical solution of the present invention, a lens protective cover is provided at the lens of the image acquisition unit of the visual sensor module to prevent the cutting dust from contaminating the lens of the visual sensor module and causing misjudgment.

[0021] In a second aspect, the technical solution of the present invention provides a cutting control method based on the plasma cutting system described in the first aspect, comprising the following steps: Establish signal interaction between the robot cutting equipment and the visual sensor module through the PROFINET communication protocol; During the cutting process, the visual sensor module captures the image information of the cutting path of the cutting target in real time, identifies obstacles on the cutting track and inputs the identification results to the robot cutting device; The robotic cutting device controls its own cutting action according to the recognition result; After cutting is completed, the visual sensor module inspects the cut workpiece and outputs a prompt message if it detects that the workpiece is unqualified.

[0022] Through the precise detection of the visual sensor module and the intelligent processing of the PLC controller, timely identification of cutting size deviations can be achieved, ensuring the quality and consistency of the cut workpiece, and further improving production efficiency and product qualification rate.

[0023] As a preferred embodiment of the technical solution of the present invention, during the cutting process, the visual sensor module captures the image information of the cutting path of the cutting target in real time, identifies obstacles on the cutting track and inputs the identification results to the robot cutting device, including the following steps: The image acquisition unit captures the image information of the cutting path of the cutting target in real time and marks the captured image information of the cutting path as an identification image and transmits it to the first processing unit; The first processing unit compares the image information marked as the recognition image with the pre-stored image with the obstacle marked, performs obstacle recognition and positioning processing on the compared image information with the obstacle, and inputs the processing result to the PLC controller.

[0024] It can be seen from the above technical solutions that the present invention has the following advantages: by integrating the visual sensor module, the system can capture the precise image information of the cutting target in real time and identify obstacles on the cutting path. This function not only reduces the need for manual intervention, but also greatly improves the cutting accuracy and avoids cutting deviations caused by human judgment errors. At the same time, automatic obstacle identification also significantly improves the efficiency of the cutting operation and shortens the production cycle. Through the application of the present invention in the field of robot plasma cutting of automotive die castings, it is possible to achieve efficient, fast, accurate and stable detection of obstacles within the cutting trajectory and dimensional offsets after cutting is completed, which is convenient, safe and reliable to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0026] Figure 1 It is a schematic block diagram of a system provided by an embodiment of the present invention.

[0027] Figure 2 is a schematic flow chart of a method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] like Figure 1 As shown, an embodiment of the present invention provides a plasma cutting system, including a robot cutting device, on which a cutting gun is provided; and also including a mounting frame, on which the robot cutting device is fixedly provided on a lower surface of the mounting frame, a visual sensor module is provided on one side of the robot cutting device, and the visual sensor module is fixedly connected to the mounting frame, and the robot cutting device is in communication connection with the visual sensor module; The visual sensor module is used to capture the image information of the cutting path of the cutting target in real time, identify obstacles on the cutting trajectory and input the identification results to the robotic cutting device, and the robotic cutting device controls its own cutting action according to the identification results; the visual sensor module also detects the workpiece after cutting and outputs a prompt message when it detects that the workpiece is unqualified.

[0030] By integrating the visual sensor module, the system can capture accurate image information of the cutting target in real time. The visual sensor module can continuously monitor the surrounding environment during the cutting process, promptly detect and identify obstacles that may affect cutting safety, thereby effectively avoiding collisions between the cutting gun and obstacles, reducing the risk of equipment damage and accidents, and improving the safety of the work site. Combining the visual sensor module with the robot cutting equipment realizes the automation and intelligent upgrade of the cutting operation. This not only reduces the labor intensity of workers, but also makes the cutting process more flexible and efficient through the application of intelligent algorithms, providing strong support for the development of industrial automation and intelligent manufacturing.

[0031] The visual sensor module uses a 3D visual sensor to capture and process the three-dimensional spatial information of the cutting target in real time. Using a 3D visual sensor as an auxiliary tool can significantly improve the accuracy and efficiency of plasma cutting. By acquiring the three-dimensional data of the cutting target in real time, the system can automatically identify obstacles, reduce material waste, and improve the overall processing quality.

[0032] In some embodiments, a PLC controller is provided in the robot cutting device, and the PLC controller is communicatively connected with the visual sensor module via the PROFINET communication protocol, and the visual sensor module inputs the detection result to the PLC controller.

[0033] The visual sensor module is installed directly above the workpiece to be inspected. The visual sensor module is about 1.8m away from the surface of the workpiece to be inspected. The mounting plate of the visual sensor module is a long hole with adjustable thread installation. A lens protective cover is designed at the lens of the visual sensor module to prevent cutting dust from contaminating the lens of the visual sensor module and causing misjudgment. By designing the PROFINET communication between the PLC controller of the robot plasma cutting equipment and the visual sensor module, the signal interaction between the PLC controller and the visual sensor module is established to ensure that the output judgment result of the visual sensor module can be effectively fed back to the PLC controller for further processing. For the detection of obstacles on the cutting track of die-casting parts, the foreign body detection function of the visual sensor module can be used. Before the robot plasma cutting, after the die-casting machine produces qualified die-casting parts with no oil stains and water stains on the surface, the upper computer feeds back to the PLC controller of the robot plasma cutting equipment. The robot plasma cutting equipment then uses the standard qualified workpiece produced by the die-casting machine as a calibration object to collect and store the image information of the standard workpiece. The image of the standard workpiece here and the image collected later need to have the same pixels to facilitate the unified use of pixel size for later size detection. In the embodiment of the present invention, when inspecting the workpiece after cutting, in addition to inspecting the size, the workpiece can also be inspected for oil stains, water stains, foreign matter, etc. on the surface of the workpiece through an image recognition method, and the oil stains, water stains, and foreign matter contained are judged as unqualified parts. At the same time, the visual sensor module judges and identifies the unqualified parts and feeds back to the PLC controller for processing. After the PLC controller receives the NG signal of the visual sensor module, it pauses the operation of the robot and feeds back to the host computer. After the host computer receives the alarm information, it manually removes the obstacles and then cuts, effectively avoiding the collision between the cutting gun and the obstacles. The PLC controller of the robot plasma equipment can set the detection threshold range for the calibration size of the calibration object. All subsequent die-castings after cutting are compared and analyzed with the calibration object. If the size offset of the die-casting after cutting exceeds the detection threshold setting range, the visual sensor module identifies, judges, and feeds back the robot unqualified signal. After receiving the unqualified signal, the PLC controller of the robot plasma equipment feeds back to the host computer to determine that the workpiece is unqualified for cutting.

[0034] In some embodiments, the visual sensor module includes an image acquisition unit, a first processing unit, and a second processing unit; An image acquisition unit is used to capture the image information of the cutting path of the cutting target in real time and mark the captured image information of the cutting path as an identification image and transmit it to the first processing unit; it is also used to collect the image information of the workpiece after cutting, mark the image information of the workpiece after cutting as a size verification image and transmit it to the second processing unit; The first processing unit is used to compare the image information marked as the recognition image with the pre-stored image with the obstacle marked, and perform obstacle recognition and positioning processing on the compared image information with the obstacle, and input the processing result to the PLC controller; The second processing unit is used to compare the image information marked as the size verification image with the stored standard size workpiece image, and output a size qualified reminder message when the comparison is consistent, and output a size unqualified reminder message when the comparison is inconsistent.

[0035] The image acquisition unit is responsible for capturing the cutting path and workpiece images in real time and accurately, providing a high-quality data source for subsequent processing. The first processing unit and the second processing unit focus on obstacle identification and size verification respectively, and significantly improve the efficiency and accuracy of image processing through parallel processing. The first processing unit compares the captured cutting path image with the pre-stored obstacle image, and can quickly identify and locate potential obstacles. This real-time and accurate obstacle recognition capability provides timely and effective obstacle avoidance guidance for the robot cutting equipment, ensuring the safety and continuity of the cutting operation. The second processing unit can automatically verify whether the size of the workpiece meets the requirements by comparing the image of the workpiece after cutting with the image of the workpiece of standard size. This function not only reduces the burden of manual inspection, but also improves the accuracy and efficiency of size verification, ensuring the stability and consistency of product quality. The detailed design of the visual sensor module makes the entire cutting system have a higher level of intelligence. By integrating advanced image processing technology and intelligent algorithms, the system can independently complete multiple links such as obstacle identification, path planning, cutting operations and size verification, realizing full intelligent control from raw materials to finished products. Since the visual sensor module adopts a modular design, it can be flexibly configured and expanded according to actual needs. For example, the parameter settings of the image acquisition unit can be adjusted according to different cutting targets and workpiece requirements, or new processing units can be added to expand the system's functions. This flexibility and scalability enables the system to adapt to diverse production needs and continue to upgrade and optimize with the continuous advancement of technology.

[0036] In some embodiments, the first processing unit performs contrast enhancement processing on the acquired image, adopts a grayscale difference method based on edge image pixels to extract the contour of the image, and extracts the edge features of obstacles in the image by clearing the pixels wrapped by the edge of the image and retaining the contour of the image; uses a Gabor wavelet filter to extract obstacle features, completes the positioning of the obstacle shape and position, and inputs the processing results into the PLC controller.

[0037] The first processing unit first performs contrast enhancement processing on the acquired image, and then uses the grayscale difference method based on the edge image pixels to extract the image contour, and clears the internal pixels of the image edge, retaining only the contour information. The obstacle feature extraction is further performed using the Gabor wavelet filter, which can accurately capture the shape and position information of the obstacle, thereby significantly improving the accuracy of obstacle recognition. In practical applications, the cutting environment may be affected by various factors such as illumination changes and shadow interference, resulting in a decrease in image quality and affecting the effect of obstacle recognition. By introducing contrast enhancement processing and edge contour extraction technology, the first processing unit can effectively cope with these complex environments and ensure that obstacles can be accurately identified under various conditions. This greatly enhances the system's adaptability to complex environments and improves the system's stability and reliability. By accurately identifying the shape and position of obstacles, the first processing unit provides reliable obstacle avoidance guidance for the robotic cutting equipment. The robotic cutting equipment can adjust the cutting path based on this information to avoid collisions with obstacles, thereby optimizing the overall efficiency and quality of the cutting operation. This path planning strategy based on real-time obstacle recognition makes the cutting operation more flexible and efficient.

[0038] By identifying and avoiding obstacles in a timely manner, robotic cutting equipment can avoid unnecessary collisions and friction with the surrounding environment, thereby reducing equipment wear and failure rates. This helps extend the service life of the equipment and reduces the cost of repairs and replacements due to equipment damage. At the same time, reducing noise and vibration caused by collisions also helps improve the working environment and increase the comfort and work efficiency of workers.

[0039] In some embodiments, the first processing unit filters the texture of the collected image through a Gabor wavelet filter to perform digital signal conversion to improve the accuracy of obstacle recognition. The Gabor wavelet filter digital signal conversion method:

[0040] In the formula, Represents a digital signal; They represent the conversion factor and expansion factor respectively; represents the basic wavelet.

[0041] The transformed digital signal is decomposed into a set of wavelet functions, and the resolution of the image is improved in the time-space domain and frequency domain through conversion factors and expansion factors; the two-dimensional function of the Gabor wavelet filter is:

[0042] In the formula, Represents a Gaussian distribution in Axis and Axis direction variants, represents the frequency of the sine curve, It indicates the direction of the sine curve.

[0043] When filtering, the output of the Gabor wavelet filter is the output adjustment of the average convolution of the real and virtual filter masks of all convolution pixels in the image, and its calculation formula is:

[0044] In the formula, Indicates the size of the filter output adjustment; represents the result of convolving the image region with the Gabor wavelet filter mask; It is the result of convolving the image region with a Gabor wavelet filter virtual mask.

[0045] In some embodiments, the second processing unit determines the image edge based on the grayscale changes on both sides of the image edge, connects the edges, and performs distance measurement based on the position coordinates of the pixel points to determine the image size of the cut workpiece and compare it with the standard workpiece image size; wherein the pixels of the standard workpiece image and the cut workpiece image are the same.

[0046] Traditional dimension verification often relies on manual measurement or the use of complex measuring equipment, which is not only time-consuming and labor-intensive, but also prone to human errors. The second processing unit completes dimension verification in an automated and digital way, greatly simplifying the verification process. The operator only needs to input the image of the cut workpiece into the system, and the system can automatically complete the dimension measurement and comparison, significantly improving work efficiency.

[0047] The second processing unit integrates advanced image processing technology and algorithms, and can independently complete tasks such as image edge recognition, size measurement and comparison. This intelligent processing method not only reduces the manual burden, but also improves the automation and intelligence level of the system, making the cutting system more adaptable to the modern manufacturing industry's demand for efficiency, precision and intelligence.

[0048] The second processing unit records detailed image data and measurement results during the measurement and comparison process, which can be saved and traced as production records. When product quality issues need to be investigated or analyzed, these data can be easily retrieved for review and verification, thereby improving the traceability and transparency of the production process.

[0049] In some embodiments, the system also includes a host computer, which is connected to the robot cutting equipment and the visual sensor module via a wireless network to achieve the functions of remotely monitoring the cutting process, adjusting cutting parameters and receiving real-time feedback data.

[0050] By introducing a host computer and establishing a wireless network connection with the robot cutting equipment and visual sensor module, the host computer allows operators to quickly adjust cutting parameters such as cutting speed, power, angle, etc. according to actual needs while remotely monitoring. This instant adjustment capability makes the cutting process more flexible and can quickly adapt to workpieces of different materials, shapes and sizes, improving production efficiency and product quality.

[0051] The host computer can receive real-time feedback data from the robot cutting equipment and visual sensor module, including cutting progress, obstacle recognition results, workpiece size verification information, etc. These real-time data provide operators with comprehensive production information, helping them to identify problems in a timely manner, analyze problems and take measures to solve them, thereby ensuring the smooth progress of the production process.

[0052] While receiving real-time feedback data, the host computer can also record and save this data. These production records not only help with subsequent production analysis and optimization, but also provide strong support for the tracing of product quality issues. When it is necessary to trace the quality of a batch of products, relevant data can be easily retrieved for review and verification.

[0053] It should be noted that, in the embodiment of the present invention, a lens protective cover is provided at the lens of the image acquisition unit of the visual sensor module to prevent the cutting dust from contaminating the lens of the visual sensor module and causing misjudgment.

[0054] In some embodiments, the mounting frame is further provided with an automatic calibration device for periodically or as needed to calibrate the position of the visual sensor module to ensure continuous stability of the cutting accuracy.

[0055] The addition of an automatic calibration device can automatically compensate for the position offset of the visual sensor module caused by long-term use or environmental changes, ensuring that it can maintain high-precision measurement and positioning capabilities throughout the entire working cycle, further improving the reliability and stability of the cutting operation.

[0056] It should be further explained here that the automatic calibration device includes a displacement sensor, a fine adjustment mechanism and a control unit; The displacement sensor is installed between the mounting frame and the visual sensor module to accurately measure the tiny position changes of the visual sensor module during the actual working process, including the horizontal offset and the vertical height change. The fine-tuning mechanism is directly connected to the visual sensor module and consists of a precision motor, a transmission mechanism and a guide element. It can automatically adjust the position of the visual sensor module according to the feedback signal of the displacement sensor to achieve precise calibration. The fine-tuning mechanism should have sufficient adjustment range and accuracy to meet the calibration requirements in different scenarios. As the core of the automatic calibration device, the control unit is responsible for receiving the data input from the displacement sensor, processing and analyzing it, and issuing control instructions to the fine-tuning mechanism. The control unit should also have a self-diagnosis function, which can monitor the working status of the calibration device in real time and give an alarm in time when an abnormality occurs.

[0057] The control unit has a built-in calibration program, which includes preset calibration processes and parameter settings. Users can select the appropriate calibration mode (such as regular calibration, on-demand calibration, etc.) according to actual needs, and set the calibration cycle and accuracy requirements. Specific workflow: The user starts the automatic calibration program through the host computer or control panel. After receiving the command, the control unit activates the displacement sensor and fine-tuning mechanism to enter the standby state. The displacement sensor starts working, collects the current position information of the visual sensor module in real time, and transmits the data to the control unit. The control unit processes and analyzes the received data to determine whether there is a position offset in the visual sensor module. If a position offset is detected, the control unit sends a control command to the fine-tuning mechanism according to the preset calibration parameters and process. After receiving the command, the fine-tuning mechanism drives the visual sensor module to adjust to the correct position until the predetermined calibration accuracy is achieved. After the calibration is completed, the control unit feeds back the calibration results to the host computer or control panel, and automatically saves the calibration records and parameter settings. At the same time, the control unit will also perform self-diagnosis on the calibration device to ensure that all components are working properly.

[0058] The automatic calibration device can ensure that the visual sensor module can maintain high-precision measurement and positioning capabilities throughout the entire working cycle, thereby improving the accuracy and reliability of the cutting operation. The automatic calibration device can automatically complete the calibration process without human intervention, reducing labor intensity and human errors. Regular or on-demand automatic calibration can promptly detect and correct position offsets, avoid cutting errors and downtime caused by position offsets, and improve production efficiency and equipment utilization. The automatic calibration device can adapt to changes in different working environments and cutting requirements, and achieve more flexible and accurate calibration effects by adjusting calibration parameters and processes.

[0059] like Figure 2 As shown, the embodiment of the present invention provides a cutting control method based on the plasma cutting system described in the first aspect, comprising the following steps: Step 1: Establish signal interaction between the robot cutting device and the visual sensor module through the PROFINET communication protocol; Step 2: During the cutting process, the visual sensor module captures the image information of the cutting path of the cutting target in real time, identifies obstacles on the cutting track and inputs the identification results to the robotic cutting device; the robotic cutting device controls its own cutting action according to the identification results; Step 3: After cutting is completed, the visual sensor module inspects the cut workpiece and outputs a prompt message if it detects that the workpiece is unqualified.

[0060] Through the precise detection of the visual sensor module and the intelligent processing of the PLC controller, timely identification of cutting size deviations can be achieved, ensuring the quality and consistency of the cut workpiece, and further improving production efficiency and product qualification rate.

[0061] In some embodiments, during the cutting process, the visual sensor module captures image information of the cutting path of the cutting target in real time, identifies obstacles on the cutting track and inputs the identification results to the robot cutting device, including: The image acquisition unit captures the image information of the cutting path of the cutting target in real time and marks the captured image information of the cutting path as an identification image and transmits it to the first processing unit; The first processing unit compares the image information marked as the recognition image with the pre-stored image with the obstacle marked, performs obstacle recognition and positioning processing on the compared image information with the obstacle, and inputs the processing result to the PLC controller.

[0062] Through the precise detection of the visual sensor module and the intelligent processing of the PLC controller, timely identification of cutting size deviations can be achieved, ensuring the quality and consistency of the cut workpiece, and further improving production efficiency and product qualification rate.

[0063] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0064] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A plasma cutting system, comprising a robot cutting device, wherein the robot cutting device is provided with a cutting gun; characterized in that: It also includes a mounting frame, the robot cutting device is fixedly mounted on the lower surface of the mounting frame, a visual sensor module is disposed on one side of the robot cutting device, and the visual sensor module is fixedly connected to the mounting frame, and the robot cutting device is in communication connection with the visual sensor module; The visual sensor module is used to capture the image information of the cutting path of the cutting target in real time, identify obstacles on the cutting track and input the identification results to the robotic cutting device, and the robotic cutting device controls its own cutting action according to the identification results; The visual sensor module also inspects the workpiece after cutting and outputs a prompt message when it detects that the workpiece is unqualified.

2. The plasma cutting system according to claim 1, characterized in that: The robot cutting device is provided with a PLC controller, and the PLC controller is connected to the visual sensor module through the PROFINET communication protocol, and the visual sensor module inputs the detection result to the PLC controller.

3. The plasma cutting system according to claim 2, characterized in that: The visual sensor module includes an image acquisition unit, a first processing unit and a second processing unit; An image acquisition unit is used to capture the image information of the cutting path of the cutting target in real time and mark the captured image information of the cutting path as an identification image and transmit it to the first processing unit; it is also used to collect the image information of the workpiece after cutting, mark the image information of the workpiece after cutting as a size verification image and transmit it to the second processing unit; The first processing unit is used to compare the image information marked as the recognition image with the pre-stored image with the obstacle marked, and perform obstacle recognition and positioning processing on the compared image information with the obstacle, and input the processing result to the PLC controller; The second processing unit is used to compare the image information marked as the size verification image with the stored standard size workpiece image, and output a size qualified reminder message when the comparison is consistent, and output a size unqualified reminder message when the comparison is inconsistent.

4. The plasma cutting system according to claim 3, characterized in that: The first processing unit performs contrast enhancement processing on the acquired image, and adopts a grayscale difference method based on edge image pixels to extract the image contour. By clearing the pixels wrapped by the image edge and retaining the image contour, the edge features of the obstacles in the image are extracted; the Gabor wavelet filter is used to extract the obstacle features, the shape and position of the obstacle are located, and the processing results are input into the PLC controller.

5. The plasma cutting system according to claim 4, characterized in that: The first processing unit filters the texture of the collected image through a Gabor wavelet filter to perform digital signal conversion; decomposes the transformed digital signal into a set of wavelet functions, and improves the resolution of the image in the time-space domain and the frequency domain through a conversion factor and an expansion factor; when filtering, the output of the Gabor wavelet filter is an output adjustment of the average convolution of the real and virtual filter masks of all convolution pixels in the image.

6. The plasma cutting system according to claim 5, characterized in that: The second processing unit determines the image edge according to the grayscale change on both sides of the image edge, connects the edges, measures the distance according to the position coordinates of the pixel points, and compares the image size of the cut workpiece with the standard workpiece image size; wherein the pixels of the standard workpiece image and the cut workpiece image are the same.

7. The plasma cutting system according to claim 6, characterized in that: The system also includes a host computer, which is connected to the robot cutting equipment and the visual sensor module through a wireless network to realize the functions of remotely monitoring the cutting process, adjusting cutting parameters and receiving real-time feedback data.

8. The plasma cutting system according to claim 7, characterized in that: A lens protective cover is provided at the lens of the image acquisition unit of the visual sensor module.

9. A cutting control method based on the plasma cutting system according to any one of claims 1 to 8, characterized in that: The steps include: Establish signal interaction between the robot cutting equipment and the visual sensor module through the PROFINET communication protocol; During the cutting process, the visual sensor module captures the image information of the cutting path of the cutting target in real time, identifies obstacles on the cutting track and inputs the identification results to the robot cutting device; The robotic cutting device controls its own cutting action according to the recognition result; After cutting is completed, the visual sensor module inspects the cut workpiece and outputs a prompt message if it detects that the workpiece is unqualified.

10. The cutting control method of the plasma cutting system according to claim 9, characterized in that: During the cutting process, the visual sensor module captures the image information of the cutting path of the cutting target in real time, identifies obstacles on the cutting track and inputs the identification results to the robot cutting device. The steps include: The image acquisition unit captures the image information of the cutting path of the cutting target in real time and marks the captured image information of the cutting path as an identification image and transmits it to the first processing unit; The first processing unit compares the image information marked as the recognition image with the pre-stored image with the obstacle marked, performs obstacle recognition and positioning processing on the compared image information with the obstacle, and inputs the processing result to the PLC controller.

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