Method and system for detecting air hole defect of welding seam
Through automated and intelligent weld detection methods and combined with multiple detection technologies, the problem that visual detection methods cannot detect internal defects of welds are solved, the welding quality and safety are improved, and the comprehensive evaluation and processing of welding structures are achieved.
Patent Information
- Application Number
- CN202411507952.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-28
- Publication Date
- 2025-01-07
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the quality evaluation of existing welded workpieces, visual inspection methods cannot effectively detect internal defects of the weld, resulting in inaccurate detection results and the safety and reliability of the welded structure cannot be ensured.
Using automated and intelligent detection methods, we can obtain target pictures of welds for processing, determine appropriate detection methods, and combine penetration detection, magnetic powder detection, ultrasonic detection and ray detection technologies to achieve comprehensive inspection of the surface and interior of the welds. And take targeted measures based on the test results.
Improve the accuracy of weld inspection and welding quality, ensure the safety and reliability of the welded structure, avoid blind or over-processing, and promptly identify and solve the problem of missing welding during welding.
Smart Images
Figure CN119269509A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of weld porosity detection, and in particular to a method and system for detecting weld porosity defects. Background Art
[0002] With the rapid progress of the manufacturing industry, welding technology has become an indispensable means of metal connection in industrial fields such as energy, transportation, construction, machinery and aviation. During the welding process, its quality is regulated by multiple complex factors, including the inherent properties of the material, the precise setting of process parameters, the stability of equipment performance and the skill level of the operator, all of which may induce the formation of defects such as pores in the weld. The presence of pores in the weld will significantly weaken the overall strength of the welded structure, aggravate its tendency to crack initiation and expansion under external loads, and may eventually cause structural failure, posing a serious threat to the safety and reliability of the product.
[0003] In addition, the implementation of effective weld porosity detection is of vital importance to ensure welding quality and prevent structural failure. At present, the quality assessment of welded workpieces generally adopts visual inspection method, which relies on manual or magnifying glass tools to directly observe the weld surface to identify and locate defects such as pores. However, the visual inspection method has significant limitations, that is, it can only detect the surface of the weld and cannot detect defects inside the weld, resulting in inaccurate test results.
[0004] Therefore, there is an urgent need for a method and system for detecting weld porosity defects that can solve the above-mentioned technical problems. Summary of the invention
[0005] The present application provides a method and system for detecting porosity defects in welds. The method detects the surface and interior of a target weld to obtain corresponding detection results. The entire detection process is automated and intelligent. It is determined whether a weld has porosity defects based on the detection results, and corresponding treatment measures are taken, which effectively solves the limitations of visual inspection methods and improves the accuracy of weld detection.
[0006] In the first aspect, the present application provides a method for detecting porosity defects in welds, which is applied to a server, and the method includes: obtaining a detection request sent by a target user, and determining a target weld according to the detection request, where the target weld is a joint formed when any two metal parts are connected together; obtaining a target image corresponding to the target weld; processing the target image to obtain target information, and determining a first detection method according to the target information; using the first detection method to detect the surface of the target weld to obtain a first detection result; obtaining a target value corresponding to the target weld, and determining a second detection method according to the target value; using the second detection method to detect the inside of the target weld to obtain a second detection result; if any one of the first detection result and the second detection result is abnormal, it is confirmed that there is a porosity defect area in the target weld, and treatment measures need to be taken according to the porosity defect area.
[0007] By adopting the above technical solution, according to the detection request sent by the target user, it is determined that the target weld needs to be inspected, the target image corresponding to the target weld is obtained, the target image is processed to determine the first detection method, and the first detection method is used to detect the surface of the target weld, so that defects on the weld surface can be found in time, and then the target value corresponding to the target weld is obtained, and the second detection method is determined according to the target value, and the inside of the target weld is detected using the second detection method. The second detection method can go deep into the weld and find porosity defects that cannot be reached by visual inspection methods. The entire inspection process is automated, and the first inspection results and the second inspection results are comprehensively evaluated to judge the overall quality of the target weld. When it is confirmed that the target weld is in an abnormal state and that there are porosity defect areas in the target weld, corresponding treatment measures need to be taken, which effectively solves the limitations of the visual inspection method and improves the accuracy of weld inspection.
[0008] Optionally, the target image is processed to obtain target information, and the first detection method is determined according to the target information; specifically including: identifying the target image to obtain material information, the target information includes material information; calculating the target image and a preset image to obtain a target cleaning value; judging whether the material information is in a preset material table; when the material information is not in the preset material table, judging whether the target cleaning value is greater than the preset cleaning value; if the target cleaning value is greater than the preset cleaning value, confirming that a penetration detection method is used, the first detection method includes a penetration detection method.
[0009] By adopting the above technical solution, the target image is identified and the material information used for the weld is obtained. Then, the target cleaning value is obtained by calculating the target image with the preset image. The corresponding detection method is selected according to the material information and the target cleaning value. When the material information is in the preset material table and the target cleaning value is greater than the preset cleaning value, it is confirmed to adopt the penetration detection method. The appropriate detection method can be flexibly selected according to the specific situation of the target weld, which can improve the accuracy of the detection.
[0010] Optionally, after determining whether the material information is in the preset material table, the method also includes: when the material information is in the preset material table, determining whether the target cleaning value is less than or equal to the preset cleaning value; if the target cleaning value is less than or equal to the preset cleaning value, confirming the use of the magnetic particle detection method, the first detection method also includes the magnetic particle detection method.
[0011] By adopting the above technical solution, when the material information is in the preset material table and the target cleaning value is less than or equal to the preset cleaning value, the magnetic particle detection method is selected. The magnetic particle detection method is suitable for detecting defects such as cracks on the surface of ferromagnetic materials. It automatically judges and selects the appropriate detection method, optimizes the detection process, and reduces the possibility of manual intervention and misjudgment.
[0012] Optionally, a target value corresponding to the target weld is obtained, and a second detection method is determined based on the target value; specifically including: detecting the thickness of the target weld to obtain the target value; determining whether the target value is greater than a preset value; when the target value is greater than the preset value, confirming that an ultrasonic detection method is used, the second detection method includes an ultrasonic detection method.
[0013] By adopting the above technical solution, accurate detection of the thickness of the target weld is an important basis for selecting an appropriate detection method. Welds of different thicknesses may require different detection methods to detect their internal defects. When the target array of the target weld is greater than the preset value, the ultrasonic detection method is selected. Ultrasonic detection is suitable for detecting internal defects of thicker materials. The use of ultrasonic detection can significantly improve detection efficiency and reduce detection time.
[0014] Optionally, after determining whether the target value is greater than a preset value, the method further includes: when the target value is less than or equal to the preset value, confirming to adopt the ray detection method, the second detection method also includes the ray detection method.
[0015] By adopting the above technical solution, when the target value is less than or equal to the preset value, the X-ray detection method is selected. The X-ray detection method has high-resolution imaging capabilities and can clearly display tiny defects inside the weld, thereby providing more accurate detection results.
[0016] Optionally, the processing measures include a first processing measure and a second processing measure. If any one of the first detection result and the second detection result is in an abnormal state, it is confirmed that there is a porosity defect area in the target weld, and processing measures need to be taken according to the porosity defect area, specifically including: if the first detection result is in an abnormal state, it is confirmed that the first processing measure is taken, and the first processing measure is grinding measures and cleaning measures; if the second detection result is in an abnormal state, it is confirmed that the second processing measure is adopted, and the second processing measure is repair welding measures, filling welding wire measures and increasing welding material measures.
[0017] By adopting the above technical solution, the surface and interior of the target weld are detected respectively, and targeted treatment measures are taken according to the detection results, so that the problems existing in the weld can be solved more accurately. Such targeted treatment measures avoid blind treatment or excessive treatment and improve treatment efficiency. These treatment measures act together on the weld to effectively ensure the overall quality of the welding.
[0018] Optionally, if the second detection result is abnormal, the method also includes: obtaining a target area value, the target area value is the area value corresponding to the pore defect area; judging whether the target area value is greater than a preset area value; when the target area value is greater than the preset area value, it is confirmed that the target welding is in a leaking weld state, and the target component needs to be re-welded according to the leaking weld state, and the target component is a component obtained by combining any two metal components.
[0019] By adopting the above technical solution, the area of the pore defect region is measured to obtain a target area value, and the target area value is compared with the preset area value, so as to accurately identify whether a weld leak occurs during the welding process. Once it is confirmed that the target weld is in a weld leak state, the target component is immediately re-welded. This timely remedial measure can prevent the weld leak problem from further expanding and affecting the safety and stability of the welded structure.
[0020] In a second aspect of the present application, a detection system for weld porosity defects is provided, the system comprising an acquisition unit, a processing unit and a confirmation unit, the acquisition unit, acquiring a detection request sent by a target user, determining a target weld according to the detection request, the target weld being a joint formed when any two metal parts are connected together; acquiring a target image corresponding to the target weld; acquiring a target value corresponding to the target weld, and determining a second detection method according to the target value; a processing unit, processing the target image to obtain target information, and determining a first detection method according to the target information; using the first detection method to detect the surface of the target weld to obtain a first detection result; using the second detection method to detect the inside of the target weld to obtain a second detection result; and a confirmation unit, if any one of the first detection result and the second detection result is abnormal, confirming that there is a porosity defect area in the target weld, and treatment measures need to be taken according to the porosity defect area.
[0021] Optionally, the processing unit is used to identify the target image and obtain material information, the target information including material information; calculate the target image and the preset image to obtain a target cleaning value; determine whether the material information is in the preset material table; when the material information is not in the preset material table, determine whether the target cleaning value is greater than the preset cleaning value; the confirmation unit is used to confirm the use of a penetration detection method if the target cleaning value is greater than the preset cleaning value, and the first detection method includes a penetration detection method.
[0022] Optionally, the processing unit is used to determine whether the target cleaning value is less than or equal to the preset cleaning value when the material information is in the preset material table; the confirmation unit is used to confirm the use of the magnetic particle detection method if the target cleaning value is less than or equal to the preset cleaning value, and the first detection method also includes the magnetic particle detection method.
[0023] Optionally, the processing unit is used to detect the thickness of the target weld to obtain a target value; determine whether the target value is greater than a preset value; the confirmation unit is used to confirm the use of ultrasonic detection when the target value is greater than the preset value, and the second detection method includes an ultrasonic detection method.
[0024] Optionally, the confirmation unit is used to confirm the use of the ray detection method when the target value is less than or equal to a preset value, and the second detection method also includes the ray detection method.
[0025] Optionally, the confirmation unit is used to confirm the adoption of a first treatment measure if an abnormal state is found in the first detection result, and the first treatment measure is a grinding measure and a cleaning measure; the confirmation unit is used to confirm the adoption of a second treatment measure if an abnormal state is found in the second detection result, and the second treatment measure is a repair welding measure, a filling welding wire measure, and a measure of increasing welding materials.
[0026] Optionally, the acquisition unit is used to obtain a target area value, which is an area value corresponding to the pore defect area; the processing unit is used to determine whether the target area value is greater than a preset area value; the confirmation unit is used to confirm that the target welding is in a leaking state when the target area value is greater than the preset area value, and the target component needs to be re-welded according to the leaking state, and the target component is a component obtained by combining any two metal components.
[0027] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.
[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.
[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. According to the detection request sent by the target user, it is determined that the target weld needs to be inspected, the target image corresponding to the target weld is obtained, and the target image is processed to determine the first detection method. The first detection method is used to detect the surface of the target weld, and defects on the weld surface can be found in time. Then, by obtaining the target value corresponding to the target weld, the second detection method is determined according to the target value, and the second detection method is used to detect the inside of the target weld. The second detection method can go deep into the weld and find porosity defects that cannot be reached by visual inspection. The entire inspection process is automated, and the first and second inspection results are comprehensively evaluated to judge the overall quality of the target weld. When it is confirmed that the target weld is in an abnormal state and that there is a porosity defect area in the target weld, corresponding treatment measures need to be taken, which effectively solves the limitations of the visual inspection method and improves the accuracy of weld inspection.
[0030] 2. Separately inspect the surface and interior of the target weld and adopt targeted treatment measures based on the inspection results, which can more accurately solve the problems existing in the weld. This targeted treatment measure avoids blind treatment or excessive treatment and improves treatment efficiency. These treatment measures work together on the weld to effectively ensure the overall quality of the welding.
[0031] 3. Measure the area of the pore defect area to obtain the target area value, and compare the target area value with the preset area value. This can accurately identify whether a leak occurs during the welding process. Once it is confirmed that the target weld is in a leak state, immediately re-weld the target component. This timely remedial measure can prevent the leak problem from further expanding and affecting the safety and stability of the welded structure. BRIEF DESCRIPTION OF THE DRAWINGS
[0032] Figure 1 It is a flow chart of a method for detecting weld porosity defects provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a detection system for weld porosity defects provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.
[0033] Explanation of the reference numerals: 201, acquisition unit; 202, processing unit; 203, confirmation unit; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION
[0034] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.
[0035] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.
[0036] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.
[0037] With the rapid progress of the manufacturing industry, welding technology has become an indispensable means of metal connection in industrial fields such as energy, transportation, construction, machinery and aviation. During the welding process, its quality is regulated by multiple complex factors, including the inherent properties of the material, the precise setting of process parameters, the stability of equipment performance and the skill level of the operator, all of which may induce the formation of defects such as pores in the weld. The presence of pores in the weld will significantly weaken the overall strength of the welded structure, aggravate its tendency to crack initiation and expansion under external loads, and may eventually cause structural failure, posing a serious threat to the safety and reliability of the product.
[0038] In addition, the implementation of effective weld porosity detection is of vital importance to ensure welding quality and prevent structural failure. At present, the quality assessment of welded workpieces generally adopts visual inspection method, which relies on manual or magnifying glass tools to directly observe the weld surface to identify and locate defects such as pores. However, the visual inspection method has significant limitations, that is, it can only detect the surface of the weld and cannot detect defects inside the weld, resulting in inaccurate test results.
[0039] Therefore, how to change the limitations of the existing visual inspection method to improve the accuracy of weld inspection This is a problem that needs to be solved urgently. The present application provides a method for detecting weld porosity defects, which is applied to a server. The server of the present application can be a platform for performing weld porosity defect detection services. Figure 1 is a flow chart of a method for detecting weld porosity defects provided in an embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S107.
[0040] S101: Obtain a detection request sent by a target user, and determine a target weld according to the detection request, where the target weld is a joint formed when any two metal parts are connected together.
[0041] In the above S101, the server receives a detection request sent by a target user, and the target user refers to a worker or a quality control personnel on the production line. The detection request contains basic information of the target weld, such as location, part number, etc. This application takes the porosity detection of any weld between two metal parts as an example to illustrate that the corresponding target weld is searched on the current product according to the detection request, and after the target weld is determined, the porosity of the target weld is detected.
[0042] S102: Obtain a target image corresponding to the target weld.
[0043] In the above S102, a high-definition camera or machine vision equipment may be used to take a picture of the target weld. The target picture should clearly show the appearance of the weld, including surface conditions, welding marks, etc. When taking pictures, it is also necessary to ensure that the lighting, angle, focal length and other parameters of the shooting environment are appropriate to obtain a high-quality image.
[0044] S103: Process the target image to obtain target information, and determine a first detection method according to the target information.
[0045] In the above S103, after obtaining the target image, the target image needs to be processed to determine the appropriate method to detect the target weld. The target image is processed to obtain target information, and the first detection method is determined according to the target information; specifically including: identifying the target image to obtain material information, the target information includes material information; calculating the target image and the preset image to obtain the target cleaning value; judging whether the material information is in the preset material table; when the material information is not in the preset material table, judging whether the target cleaning value is greater than the preset cleaning value; if the target cleaning value is greater than the preset cleaning value, it is confirmed that the penetration detection method is adopted, and the first detection method includes the penetration detection method. Specifically, the target image is analyzed using image recognition technology (deep learning, machine learning algorithm), the weld and its surrounding area in the image are identified, and the material type is inferred by color, texture, shape and other features. Extract material information, such as metal type (stainless steel, aluminum alloy, etc.), surface treatment method (galvanizing, spray painting, etc.). An image recognition model can also be trained to accurately identify the surfaces corresponding to different types of materials, and the material information is determined by identifying the image of the captured surface. Since the target image is processed to obtain the target information, the target information includes material information. The preset image is determined according to the material information. The preset image is a set of standard images representing clean welding. One material corresponds to one preset image, so the preset image needs to be determined according to the identified material information. Then use image processing technology (image contrast, edge detection, color analysis, etc.) to compare the target image with the preset image. Calculate the difference or similarity between the two to obtain the target cleanliness value. The target cleanliness value can be a percentage, score or other quantitative index used to indicate the cleanliness of the target weld. Determine whether the material information is in the preset material table. The preset material represents a database of ferromagnetic material information. The preset processing table contains information such as the name, type and characteristics of each material. Compare the material information identified from the target image with each material in the preset material table. If the material information is not in the preset material table, it is confirmed that the material information is non-ferromagnetic material, which includes aluminum alloy, magnesium alloy, ceramic and other materials. The cleanliness of the weld needs to be further evaluated. Compare the target cleanliness value with the preset cleanliness value. The preset cleanliness value can be set based on actual inspection experience and industry standards. When the target cleaning value is greater than the preset cleaning value, the penetration test method is selected as the first test method. The penetration test method is a non-destructive test method suitable for detecting tiny defects (such as cracks, pores, etc.) on the weld surface. The penetration test method uses the capillary phenomenon to apply a liquid penetrant with good permeability to the weld surface. After the penetrant enters the surface opening defect, it will be cleaned and developed, and the defect will show the penetrant, thereby detecting the defect. The penetration test method has high requirements for surface cleanliness, but has high sensitivity for detecting tiny surface opening defects.
[0046] In addition, when the material information is in the preset material table, it is determined whether the target cleaning value is less than or equal to the preset cleaning value; if the target cleaning value is less than or equal to the preset cleaning value, it is confirmed that the magnetic particle detection method is used, and the first detection method also includes the magnetic particle detection method. Specifically, since the preset material table represents a database of ferromagnetic material information, the material information identified from the target image is compared with the entries in the preset material table. The comparison process may involve technical means such as string matching and pattern recognition. After confirming that the material information is in the preset material table, the target cleaning value (obtained by calculating the target image and the preset image) is compared with the preset cleaning value. When the target cleaning value is less than or equal to the preset cleaning value, it is considered that the cleanliness of the weld is average, and it can be confirmed that the magnetic particle detection method is used. The magnetic particle detection method is a commonly used non-destructive detection method, which is particularly suitable for detecting defects such as cracks and pores in metal welds. The principle is to use the leakage magnetic field generated by the magnetic field at the defect to adsorb magnetic powder, thereby showing the location and shape of the defect. That is, magnetic particle detection uses the ferromagnetic material under the action of the magnetic field, the defect will cause magnetic field distortion, and the magnetic powder will gather at the defect, thereby showing the location and shape of the defect. Since magnetic particle testing can only be used for ferromagnetic materials and cannot be used for non-ferromagnetic materials, magnetic particle testing is selected. Then use magnetizing equipment to magnetize the weld so that the defects in the weld generate leakage magnetic fields. Apply an appropriate amount of magnetic powder to the magnetized weld surface, and the magnetic powder will be adsorbed by the leakage magnetic field at the defect, thereby displaying the location and shape of the defect. Use an observation device (such as a magnifying glass, microscope, etc.) to observe the display of magnetic traces and record information such as the location, shape, and size of the defect.
[0047] S104: Using a first detection method to detect the surface of the target weld to obtain a first detection result.
[0048] In the above S104, the corresponding first detection method is selected according to the material information and the target cleaning value. Since the first detection method includes a penetration detection method and a magnetic particle detection method, corresponding detection equipment and tools are prepared according to the first detection method. The surface of the target weld is inspected in detail, and the detection results are recorded, and then the first detection result is output.
[0049] S105: Obtain a target value corresponding to the target weld, and determine a second detection method according to the target value.
[0050] In the above S105, the target value is obtained by the measuring tool, the target value corresponding to the target weld is obtained, and the second detection method is determined according to the target value; specifically including: detecting the thickness of the target weld to obtain the target value; judging whether the target value is greater than the preset value; when the target value is greater than the preset value, it is confirmed that the ultrasonic detection method is adopted, and the second detection method includes the ultrasonic detection method. Specifically, select an appropriate measuring tool, such as an ultrasonic thickness gauge, a vernier caliper or a laser rangefinder, etc., and select a suitable tool according to the material, shape and position of the weld. Place the measuring tool at the appropriate position of the weld to ensure that the measuring point is representative and can accurately reflect the overall thickness of the weld. For an ultrasonic thickness gauge, an appropriate amount of coupling agent needs to be applied to ensure that the ultrasonic wave can be transmitted smoothly. According to the indication of the measuring tool or the reading on the display screen, accurately record the thickness value of the weld, that is, the target value. Then judge whether the target value is greater than the preset value. The preset value is a threshold set according to industry standards, engineering requirements or empirical data, which is used to judge whether the weld thickness exceeds a certain range, so as to determine whether a more accurate or in-depth detection method is needed. Compare the target value obtained by the detection with the preset value. If the target value is greater than the preset value, it means that the weld is thicker and a more sensitive or deeper detection method may be needed. When the target value is greater than the preset value, confirm that ultrasonic detection is used. Ultrasonic detection has the advantages of strong penetration, wide detection range, and fast detection speed, and is particularly suitable for detecting thicker welds. It can effectively detect defects inside the weld, such as cracks, inclusions, and lack of fusion, providing a reliable basis for the evaluation of welding quality. Ultrasonic detection steps: First, select an appropriate ultrasonic flaw detector and probe, and select the appropriate frequency and probe type according to the material and thickness of the weld. Secondly, apply an appropriate amount of coupling agent on the weld surface, place the probe on the weld, and scan along the weld direction. Pay attention to keeping the probe stable and the pressure moderate to ensure that the ultrasonic wave can propagate smoothly and receive clear reflected signals. According to the received reflected signals, analyze the structure and defects inside the weld. Modern ultrasonic flaw detectors are usually equipped with display screens and data analysis software, which can display the test results in real time and provide information such as the location, size, and nature of the defects. As an efficient and accurate non-destructive testing method, ultrasonic testing plays an important role in weld quality inspection. During the implementation process, it is necessary to pay attention to operating specifications and safety matters to ensure the accuracy and reliability of the test results.
[0051] In addition, when the target value is less than or equal to the preset value, it is confirmed that the ray detection method is adopted, and the second detection method also includes the ray detection method. Specifically, when the target value is less than or equal to the preset value, it is confirmed that the ray detection method is adopted, and according to the material, thickness and detection requirements of the weld, a suitable ray detection equipment, such as an X-ray machine or a gamma ray machine, is selected. Ray detection is radioactive, and it is necessary to ensure the safe isolation of the detection area and equip the detection personnel with necessary protective equipment, such as lead clothing, protective glasses, etc. The ray detection steps are as follows: first, calibrate the ray detection equipment before detection to ensure the accuracy of the detection results. Place the weld within the irradiation range of the ray detection equipment, and ensure that there are no other sensitive objects or personnel around to reduce the impact of radiation. Move the ray detection equipment to irradiate the weld. According to the thickness and material of the weld, adjust the parameters such as the intensity, irradiation time and distance of the ray source to ensure that the ray can penetrate the weld and produce a clear image. Use the imaging system supporting the ray detection equipment to collect the ray image of the weld. Check the quality of the collected ray image to ensure that the image is clear and has no defects such as blur or ghosting. Carefully analyze the radiographic images to identify possible defects in the weld, such as cracks, lack of fusion, slag inclusions, etc. These defects usually appear as dark or bright areas in the radiographic images. Use measurement tools to measure the size of the defects in the radiographic images to assess their severity and whether they meet the engineering requirements. Ensure that when the target weld thickness is less than or equal to the preset value, effective and accurate detection is performed using radiographic detection methods, providing strong support for the quality assurance of the project.
[0052] S106: Use the second detection method to detect the interior of the target weld to obtain a second detection result.
[0053] In the above S106, since the second detection method includes an ultrasonic detection method and a radiographic detection method, an appropriate second detection method is selected according to the target value of the target weld, and a radiographic detection method is prepared according to the second detection method. The inside of the target weld is scanned or detected, the internal structure and possible defects are recorded, and the scanning result is output as the second detection result.
[0054] S107: If any one of the first detection result and the second detection result is abnormal, it is confirmed that there is a porosity defect area in the target weld, and treatment measures need to be taken according to the porosity defect area.
[0055] In the above S107, after the surface and the interior of the target weld are inspected, the first inspection result and the second inspection result are obtained, and then it is determined whether any one of the first inspection result and the second inspection result is in an abnormal state, and the abnormal state indicates the presence of a porosity defect. When the target weld has a porosity defect area, it is necessary to determine whether the porosity defect area exists on the surface of the target weld or inside the target weld, and formulate corresponding treatment measures according to the porosity defect areas existing in different positions.
[0056] In addition, if the first detection result is abnormal, it is confirmed that the first treatment measure is taken, and the first treatment measure is grinding and cleaning. Specifically, the first detection result is obtained by detecting the surface of the target weld. When there is a porosity defect area on the surface of the target weld, the first treatment measure can be taken, and the first treatment measure includes grinding and cleaning. The grinding measure is to remove defects such as unevenness, scale, rust, etc. on the weld surface to improve the surface quality of the weld. Grinding steps: Select suitable grinding tools, such as angle grinders, grinding wheels, sandpaper, etc., and select suitable grinding materials and particle sizes according to the material and surface state of the weld. Wear personal protective equipment, such as protective glasses, masks, gloves, etc., to ensure that the working area is well ventilated. Use grinding tools to evenly grind the weld surface, pay attention to controlling the grinding force and speed, and avoid excessive grinding to damage the weld matrix. The surface quality of the weld needs to be checked regularly during the grinding process until the required finish and flatness are achieved. Cleaning measures are to thoroughly remove dirt, grease, welding slag and other impurities on and around the weld to prepare for subsequent welding or testing work. Cleaning steps First check the cleanliness of the weld and its surroundings to determine the specific areas that need to be cleaned. Select the appropriate cleaning agent based on the degree of contamination on the weld surface and the material characteristics. For welds with heavy oil pollution, use chemical cleaning agents; for general dirt, use water or neutral cleaning agents. Use a soft cloth, sponge or brush to dip an appropriate amount of cleaning agent to wipe or scrub the weld and its surroundings. Pay attention to controlling the amount of cleaning agent and the cleaning force to avoid damaging the weld matrix. After cleaning, use clean water or compressed air to rinse and dry the weld to ensure that there is no residual cleaning agent or moisture on the weld surface.
[0057] Further, if the second detection result is in an abnormal state, the second treatment measure is confirmed to be adopted, and the second treatment measure is a repair welding measure, a filling welding wire measure, and a measure to increase welding materials. Specifically, the second detection result is obtained by detecting the inside of the target weld. When there is a pore defect area inside the target weld, the second treatment measure can be taken, and the second treatment measure includes a repair welding measure, a filling welding wire measure, and a measure to increase welding materials. The repair welding measure is to repair the defects in the weld and restore the integrity and performance of the weld. The repair step is to determine the appropriate repair plan according to the type, location and severity of the weld defect. The repair plan should specify the repair method (such as manual welding, automatic welding, etc.), repair materials, repair process parameters, etc. Prepare corresponding welding materials and equipment according to the repair plan, such as welding rods, welding wires, welding machines, shielding gases, etc. Clean the weld thoroughly before repairing to remove impurities such as oxides and oil stains around the defects. Perform welding operations according to the repair plan, pay attention to controlling parameters such as welding current, voltage, and welding speed to ensure the quality of the repaired weld. After the repair welding is completed, the repaired weld is quality inspected and performance evaluated to ensure that it meets the engineering requirements. Filling wire measures are to supplement the weld metal by filling wire during welding to improve the strength and density of the weld. Filling wire steps Select appropriate welding wire according to welding requirements and ensure that the quality of the welding wire meets the standards. During welding, adjust the wire feeding speed according to the welding speed and the state of the molten pool to ensure that the welding wire can be fed into the molten pool evenly and stably. Pay attention to the formation of the weld, adjust the welding parameters and wire feeding speed in time to ensure that the weld is well formed and defect-free. Adding welding materials measures When the weld thickness is insufficient or the weld strength needs to be enhanced, the load-bearing capacity and performance of the weld are improved by adding welding materials. Adding welding steps, first evaluate the load-bearing demand and performance requirements of the weld to determine whether additional welding materials are needed. Select appropriate welding materials, such as welding rods, welding wires or welding plates, according to the material, thickness and performance requirements of the weld. Add welding materials to the weld during or before welding to ensure that the welding materials can be fully melted and fused with the base metal. In the process of adding welding materials, pay attention to controlling welding parameters such as current, voltage and welding speed to ensure welding quality. After adding welding materials, the weld should be inspected for quality and evaluated for performance to ensure that it meets the engineering requirements.
[0058] In a possible implementation, the area value of the pore defect area can also be obtained, and the welding quality can be judged accordingly. For the target component in the leaking state, timely re-welding is performed to ensure the reliability of the welding quality, specifically including: obtaining the target area value, the target area value is the area value corresponding to the pore defect area; judging whether the target area value is greater than the preset area value; when the target area value is greater than the preset area value, it is confirmed that the target welding is in the leaking state, and the target component needs to be re-welded according to the leaking state, and the target component is a component obtained by combining any two metal components. Specifically, after determining that the target weld has a pore defect area, a high-resolution industrial camera or a dedicated image acquisition device can be used to shoot the welded target component to ensure that the image is clear and can accurately reflect the welding quality. The collected image is imported into professional image processing software or pre-processed using an algorithm, including denoising, contrast enhancement, etc., to improve the image quality. The collected image is imported into professional image processing software or pre-processed using an algorithm, including denoising, contrast enhancement, etc., to improve the image quality. Accurately marking the boundaries of the pore defects in the image can be achieved by manual annotation or using an automatic algorithm (such as an algorithm based on shape analysis). According to the marked boundaries, calculate the number of pixels in the pore defect area. Note that if the scale of the image is known, the number of pixels can be converted into actual area units (such as square millimeters, square centimeters, etc.), that is, the target area value. Then determine whether the target area value is greater than the preset area value. The preset area value is based on industry standards, engineering requirements or empirical data. A reasonable preset area value is set as the threshold for judging whether the welding quality is qualified. Compare the calculated target area value with the preset threshold. When the pore defect area is greater than the preset threshold, it is considered that there is a quality problem with the welding and further processing is required. Confirm that the target welding is in a leaking state. Leaking is usually caused by failure to fully melt or penetrate the welding material during the welding process. Analyze the causes of leaking, which may include improper welding parameter settings (such as current, voltage, welding speed, etc.), welding material quality problems, poor welding environment (such as temperature, humidity, wind speed, etc.) or improper welding operation. Adjust welding parameters, replace welding materials or improve welding environment according to the analysis results. Re-weld the target parts to ensure that the welding quality meets the engineering requirements. During the re-welding process, pay attention to monitoring the welding process to ensure stable and reliable welding quality. After re-welding is completed, the welding quality is inspected, including appearance inspection, non-destructive testing (such as X-ray testing, ultrasonic testing, etc.) and mechanical property testing. In addition, when the target area value is less than or equal to the preset area value, it is necessary to check the location of the target weld where the porosity defect exists, that is, whether it is inside or on the surface, and then adopt corresponding treatment measures according to the specific location.
[0059] In a possible implementation, in addition to using the first detection method and the second detection method mentioned above, a helium mass spectrometer leak detector can also be used to detect porosity defects in the target weld. The helium mass spectrometer leak detector is a high-precision, high-sensitivity gas leak detection device, and its principle is based on the low permeability and high sensitivity of helium. In weld detection, since weld porosity can cause gas leakage, a helium mass spectrometer leak detector can be used for detection. You can choose the helium spray method or the helium absorption method. For some large or complex weld structures, the helium absorption method can be used. The specific method to be selected for detecting the target weld can be determined based on the structure of the target weld, and no excessive restrictions are made here. The helium mass spectrometer leak detector can detect extremely small leaks, so it also has a good detection effect on tiny weld pores.
[0060] The present application also provides a detection system for weld porosity defects. Figure 2 is a schematic diagram of a detection system for weld porosity defects provided in an embodiment of the present application, with reference to Figure 2 The system includes an acquisition unit 201, a processing unit 202 and a confirmation unit 203.
[0061] The acquisition unit 201 acquires a detection request sent by a target user, determines a target weld according to the detection request, and the target weld is a joint formed when any two metal parts are connected together; acquires a target image corresponding to the target weld; acquires a target value corresponding to the target weld, and determines a second detection method according to the target value.
[0062] The processing unit 202 processes the target image to obtain target information, and determines a first detection method according to the target information; uses the first detection method to detect the surface of the target weld to obtain a first detection result; and uses the second detection method to detect the inside of the target weld to obtain a second detection result.
[0063] The confirmation unit 203 confirms that there is a porosity defect area in the target weld if any one of the first detection result and the second detection result is in an abnormal state, and treatment measures need to be taken according to the porosity defect area.
[0064] In one possible implementation, the processing unit 202 is used to identify the target image to obtain material information, the target information including material information; calculate the target image and the preset image to obtain a target cleaning value; determine whether the material information is in the preset material table; when the material information is not in the preset material table, determine whether the target cleaning value is greater than the preset cleaning value; the confirmation unit 203 is used to confirm the use of a penetration detection method if the target cleaning value is greater than the preset cleaning value, and the first detection method includes a penetration detection method.
[0065] In one possible embodiment, the processing unit 202 is used to determine whether the target cleaning value is less than or equal to the preset cleaning value when the material information is in the preset material table; the confirmation unit 203 is used to confirm the use of the magnetic particle detection method if the target cleaning value is less than or equal to the preset cleaning value, and the first detection method also includes the magnetic particle detection method.
[0066] In one possible implementation, the processing unit 202 is used to detect the thickness of the target weld to obtain a target value; determine whether the target value is greater than a preset value; and the confirmation unit 203 is used to confirm that an ultrasonic detection method is used when the target value is greater than a preset value, and the second detection method includes an ultrasonic detection method.
[0067] In a possible implementation, the confirmation unit 203 is used to confirm that the ray detection method is adopted when the target value is less than or equal to a preset value, and the second detection method also includes a ray detection method.
[0068] In one possible implementation, the confirmation unit 203 is used to confirm the adoption of a first treatment measure if an abnormal state is present in the first detection result, and the first treatment measure is a grinding measure and a cleaning measure; the confirmation unit is used to confirm the adoption of a second treatment measure if an abnormal state is present in the second detection result, and the second treatment measure is a repair welding measure, a filling welding wire measure, and a measure of increasing welding materials.
[0069] In a possible implementation, the acquisition unit 201 is used to obtain a target area value, which is an area value corresponding to the pore defect area; the processing unit 202 is used to determine whether the target area value is greater than a preset area value; the confirmation unit 203 is used to confirm that the target welding is in a leaking state when the target area value is greater than the preset area value, and the target component needs to be re-welded according to the leaking state, and the target component is a component obtained by combining any two metal components.
[0070] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.
[0071] The present application also discloses an electronic device. Figure 3 , Figure 3The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .
[0072] The communication bus 302 is used to realize the connection and communication between these components.
[0073] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.
[0074] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).
[0075] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.
[0076] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 305 can also be optionally at least one storage device located away from the aforementioned processor 301.
[0077] like Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for detecting weld porosity defects.
[0078] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application for detecting weld porosity defects stored in the memory 305. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.
[0079] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.
[0080] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0081] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.
[0082] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0083] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0084] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.
[0085] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure.
Claims
1. A method for detecting weld porosity defects, characterized in that: The method comprises: Obtaining a detection request sent by a target user, and determining a target weld according to the detection request, wherein the target weld is a seam formed when any two metal parts are connected together; Obtaining a target image corresponding to the target weld; Processing the target image to obtain target information, and determining a first detection method according to the target information; Using the first detection method to detect the surface of the target weld to obtain a first detection result; Obtaining a target value corresponding to a target weld, and determining a second detection method according to the target value; Using the second detection method to detect the interior of the target weld to obtain a second detection result; If any one of the first detection result and the second detection result is in an abnormal state, it is confirmed that the target weld has a porosity defect area, and treatment measures need to be taken according to the porosity defect area.
2. The method according to claim 1, characterized in that The processing of the target image to obtain target information and determining the first detection method according to the target information specifically includes: Identify the target image to obtain material information, where the target information includes the material information; Calculating the target image and the preset image to obtain a target cleaning value; Determine whether the material information is in the preset material table; When the material information is not in the preset material table, determining whether the target cleaning value is greater than a preset cleaning value; If the target cleaning value is greater than the preset cleaning value, it is confirmed that a penetration detection method is adopted, and the first detection method includes the penetration detection method.
3. The method according to claim 2, characterized in that After determining whether the material information is in the preset material table, the method further includes: When the material information is in the preset material table, determining whether the target cleaning value is less than or equal to the preset cleaning value; If the target cleaning value is less than or equal to the preset cleaning value, it is confirmed that the magnetic particle detection method is adopted, and the first detection method also includes the magnetic particle detection method.
4. The method according to claim 1, characterized in that The step of obtaining a target value corresponding to the target weld and determining a second detection method according to the target value specifically includes: Detecting the thickness of the target weld to obtain the target value; Determining whether the target value is greater than a preset value; When the target value is greater than the preset value, it is confirmed that the ultrasonic detection method is adopted, and the second detection method includes the ultrasonic detection method.
5. The method according to claim 4, characterized in that After determining whether the target value is greater than a preset value, the method further includes: When the target value is less than or equal to the preset value, it is confirmed that the ray detection method is adopted, and the second detection method also includes the ray detection method.
6. The method according to claim 1, characterized in that The treatment measures include a first treatment measure and a second treatment measure. If any one of the first detection result and the second detection result is in an abnormal state, it is confirmed that there is a porosity defect area in the target weld, and treatment measures need to be taken according to the porosity defect area, specifically including: If the first detection result shows the abnormal state, confirming to take the first treatment measure, wherein the first treatment measure is a grinding measure and a cleaning measure; If the second detection result shows the abnormal state, the second treatment measure is confirmed to be adopted, and the second treatment measure is a repair welding measure, a filling welding wire measure, and a measure of adding welding materials.
7. The method according to claim 6, characterized in that After the second detection result shows the abnormal state, the method further includes: Obtaining a target area value, wherein the target area value is an area value corresponding to the pore defect region; Determine whether the target area value is greater than a preset area value; When the target area value is greater than the preset area value, it is confirmed that the target welding is in a leaky state, and the target component needs to be re-welded according to the leaky state. The target component is a component obtained by combining any two metal components.
8. A detection system for weld porosity defects, characterized in that: The system comprises an acquisition unit (201), a processing unit (202) and a confirmation unit (203). The acquisition unit (201) acquires a detection request sent by a target user, and determines a target weld according to the detection request, wherein the target weld is a seam formed when any two metal parts are connected together; Obtaining a target image corresponding to the target weld; Obtaining a target value corresponding to a target weld, and determining a second detection method according to the target value; The processing unit (202) processes the target image to obtain target information, and determines a first detection method according to the target information; uses the first detection method to detect the surface of the target weld to obtain a first detection result; and uses the second detection method to detect the interior of the target weld to obtain a second detection result; The confirmation unit (203) confirms that a porosity defect area exists in the target weld if any one of the first detection result and the second detection result is in an abnormal state, and takes treatment measures according to the porosity defect area.
9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.