Quality monitoring system for deep penetration keyhole non-metallic inert gas welding

Abstract

The present invention provides a deep penetration keyhole non-metallic inert gas (NIG) shielded welding quality monitoring system. This system uses a ring laser to perform three-dimensional scanning of weld gaps, misalignment, and other conditions before welding, as well as weld morphology during and after welding. Furthermore, it collects welding current, voltage signal data, arc sound signal data, arc morphology, and weld pool image data in real time during the welding process. This data is then comprehensively analyzed to enable real-time monitoring of welding quality. This system monitors the quality of deep penetration keyhole NIGG shielded welding through multi-dimensional data collection, significantly improving the efficiency and accuracy of quality testing for deep penetration keyhole NIGG shielded welding.

Description

Technical Field

[0001] The invention relates to the technical field of welding, in particular to a quality monitoring system for deep penetration keyhole non-melting inert gas shielded welding. Background Art

[0002] As an efficient welding technology, deep penetration keyhole non-melting inert gas shielded welding (K-TIG) uses the arc pressure generated by high current to form a small hole in the molten pool. It can weld thicker plates without opening a groove, achieve butt welding, single-sided welding and double-sided forming, and one-time penetration. There is no need to remove the back root and repair welding, which greatly simplifies the welding process. At the same time, since there is no need to filler wire and open a welding groove, compared with traditional tungsten inert gas shielded welding (TIG), it has the characteristics of high efficiency and low cost, and has extremely high development potential and application space.

[0003] Since deep-penetration K-TIG welding is primarily used for single-pass double-sided forming of thick workpieces, ensuring welding quality is particularly important. Currently, research on K-TIG welding automation is primarily focused on controlling the trajectory of the welding gun. The usual method for testing welding quality is to cut the workpiece after welding and analyze the degree of penetration of the weld cross-section to determine the quality, thereby adjusting the welding parameters. This method involves complex steps and significantly reduces welding efficiency. Therefore, achieving online testing of welding quality is of great significance. Compared to simple flat workpieces, cylindrical workpieces are more widely used in actual engineering, necessitating the development of welding monitoring devices specifically for these workpieces. Summary of the Invention

[0004] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a quality monitoring system for deep penetration keyhole non-melting inert gas welding, so as to solve the above technical problems arising in the prior art.

[0005] In order to achieve the above-mentioned purpose and other related purposes, the present invention provides a quality monitoring system for deep-penetration keyhole non-melting inert gas shielded welding, including: a weld morphology annular laser three-dimensional scanning module, which is used to perform three-dimensional scanning of the splicing gap and misalignment of the test piece before deep-penetration keyhole non-melting inert gas shielded welding, and the target weld morphology of the welded part during welding and after welding, so as to collect corresponding weld scanning data before welding, weld scanning data during welding and weld morphology data after welding; a welding electrical signal acquisition module, which is used to collect the welding current signal and the welding voltage signal data between the tungsten electrode of the welding gun and the welding material in real time during the welding process; a welding arc sound signal acquisition module, which is used to collect the arc sound signal data generated by the welding gun in real time during the welding process ; A welding arc morphology and molten pool image acquisition module, which is used to collect the molten pool image data of the front of the weldment and the arc morphology image data of the welding process in real time during the welding process; A welding quality monitoring system, which is connected to the welding morphology annular laser scanning module, the welding electrical signal acquisition module, the welding arc sound signal acquisition module and the welding arc morphology and molten pool image acquisition module, is used to perform a comprehensive evaluation of the welding quality based on the collected weld scanning data before welding, the weld scanning data during welding, the weld morphology data after welding, the current and voltage signal data, the arc sound signal data, the molten pool image data of the front of the weldment and the arc morphology image data during the welding process, so as to obtain the deep penetration small hole non-melting inert gas shielded welding quality corresponding to the target weld.

[0006] In one embodiment of the present invention, the weld morphology annular laser scanning module includes: a forward and backward moving linear guide rail installed on a heavy tripod, a drive motor, and a weld morphology annular laser three-dimensional scanning assembly installed on the linear guide rail; the weld morphology annular laser three-dimensional scanning assembly includes: a conical mirror arranged along the same optical axis and integrated in a transparent glass tube, a laser collimating and beam expanding lens group, a laser and a CCD camera; wherein, the conical mirror is used to convert the laser emitted by the laser and expanded by the laser collimating and beam expanding lens group into a ring laser, and the CCD camera collects the pre-welding specimen splicing condition scanning data, the weld scanning data during welding, and the weld contour data after welding of the target weld scanned forward and backward.

[0007] In one embodiment of the present invention, the quality monitoring device includes: a weld morphology annular laser three-dimensional scanning detection module, which is used to construct a corresponding weld morphology three-dimensional model based on the weld scanning data before welding, the weld scanning data during welding and the weld three-dimensional contour data after welding, to obtain weld morphology data before welding, during welding and after welding, so as to obtain annular laser scanning detection results; a welding current and voltage detection module, which is used to perform FFT analysis based on the collected current signal and the welding voltage signal data between the tungsten electrode of the welding gun and the welding material, and obtain the welding current and the welding voltage signal spectrum detection results between the tungsten electrode of the welding gun and the welding material based on the signal strength of a specific frequency band; a welding arc sound signal detection module, which obtains the arc sound signal detection result by filtering and spectrum analysis the collected arc sound signal data through the signal strength of a specific frequency band; a welding pool and welding arc morphology image detection module, which is used Based on the collected molten pool image data on the front of the welded part, the size and shape parameters of the molten pool and its position relative to the center of the weld are obtained, and the front image detection result of the molten pool is obtained; the collected arc morphology image data of the welding process is extracted, the abnormalities of the arc morphology image characteristics are analyzed, and the quality problems generated during the welding process are predicted to obtain the welding arc morphology image detection result; the welding quality analysis module is connected to the weld morphology annular laser three-dimensional scanning detection module, the welding current and voltage detection module, the arc sound signal detection module, the welding molten pool and the arc morphology image detection module, and is used to integrate the annular laser scanning detection results, the welding current and the welding voltage signal spectrum detection results between the welding gun tungsten electrode and the welding material, the arc sound signal detection results, the molten pool front image detection results and the welding arc morphology image detection results, and comprehensively analyze and evaluate the welding quality to obtain the deep penetration small hole non-melting inert gas shielded welding quality detection result.

[0008] In one embodiment of the present invention, the weld seam morphology ring laser 3D scanning detection module includes: a weld seam detection unit before welding, which is used to construct a 3D model of the current target weld seam based on the weld seam scanning data before welding, so as to obtain the seam width, misalignment and center trajectory of the target weld seam before welding; a weld seam detection unit during welding, which is used to construct a 3D model of the current target weld seam based on the weld seam scanning data collected in real time, so as to obtain the seam width, misalignment, deformation and change of the center trajectory, back weld width and weld height of the target weld seam during welding; and a weld seam detection unit after welding. A measurement unit is used to construct a three-dimensional model of the current target weld according to the collected double-side profile data of the weld, so as to obtain weld morphology parameters such as weld width and weld height of the target weld after welding; a weld morphology change detection unit is connected to the weld detection unit before welding, the weld detection unit during welding and the weld detection unit after welding, and is used to judge the weld morphology change of the weld width, misalignment and center trajectory of the target weld before welding, the weld width, misalignment, center trajectory, weld width and weld height during welding, and the weld width and weld height of the target weld after welding.

[0009] In one embodiment of the present invention, when the welded part is a cylindrical hollow structure, a ring-shaped laser 3D scanning module, via a motion mechanism mounted on a heavy-duty tripod, enters the cylindrical hollow structure to perform a 3D scan of the weld. The heavy-duty tripod and motion mechanism comprise a linear motion guide mounted on the tripod, a drive motor, and a ring-shaped laser 3D scanning module mounted on the motion guide. The linear motion guide is equipped with a high-precision grating displacement sensor. The ring-shaped laser 3D scanning module comprises a conical mirror arranged along the same optical axis and integrated within a transparent glass tube, a laser collimating and beam-expanding lens assembly, a laser, and a camera. The ring-shaped laser profiler can image the inner contour of the cylindrical hollow structure. Driven by the heavy-duty tripod, the ring-shaped laser 3D scanning module scans the weld of the specimen and, combined with data collected by the high-precision grating displacement sensor, constructs 3D data of the weld topography.

[0010] In one embodiment of the present invention, the welding arc morphology and molten pool image acquisition module includes: a high-speed camera device arranged on the front side of the target weld of the weldment, which is used to collect the molten pool and arc morphology image data on the front side of the weldment in real time during the welding process.

[0011] In one embodiment of the present invention, the welding arc sound signal acquisition module uses a Hall sensor to convert the large current signal of welding into current signal data that can be collected by a data acquisition card, and at the same time collects the welding voltage signal between the tungsten electrode of the welding gun and the welding material.

[0012] In one embodiment of the present invention, a microphone is used to collect the arc sound signal and analyze abnormalities in the sound signal during the welding process.

[0013] In one embodiment of the present invention, the weld seam morphology annular laser three-dimensional scanning module drives the corresponding forward and backward movement through a forward and backward movement driving device; the forward and backward movement driving device is a linear motion guide rail, a drive motor, and a high-precision grating displacement sensor.

[0014] As described above, the quality monitoring system for deep penetration keyhole non-melting inert gas shielded welding of the present invention has the following beneficial effects: The present invention realizes online monitoring of welding quality by integrating and performing comprehensive analysis of annular laser three-dimensional scanning data of the weld morphology before, during, and after welding, as well as real-time data collection during the welding process of the welding gun current, the voltage signal data between the tungsten electrode and the welding material, arc sound signal data, and image data of the weld pool front and arc morphology during the welding process. This data is then integrated into the system to perform comprehensive analysis. The present invention realizes online detection of welding quality through multi-dimensional data collection, thereby improving the efficiency and accuracy of welding quality detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Shown is a structural schematic diagram of a quality monitoring system for deep penetration keyhole non-metallic inert gas welding in one embodiment of the present invention.

[0016] Figure 2 Shown is a schematic structural diagram of a ring laser three-dimensional scanning device for weld morphology in one embodiment of the present invention.

[0017] Figure 3 Shown is a schematic diagram of the molten pool arc image monitoring results in one embodiment of the present invention.

[0018] Figure 4 Shown is a structural schematic diagram of a quality monitoring system for deep penetration keyhole non-metallic inert gas welding in one embodiment of the present invention.

[0019] Figure 5 Shown is a schematic diagram of a welding quality monitoring process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0021] It should be noted that in the following description, reference is made to the accompanying drawings, which describe several embodiments of the present invention. It should be understood that other embodiments may be used and that mechanical, structural, electrical and operational changes may be made without departing from the spirit and scope of the present invention. The following detailed description should not be considered restrictive, and the scope of the embodiments of the present invention is limited only by the claims of the published patents. The terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. Spatially related terms, such as "upper", "lower", "left", "right", "below", "below", "lower", "above", "upper", etc., may be used in the text to facilitate the description of the relationship between one element or feature shown in the figure and another element or feature.

[0022] Throughout this specification, when a part is said to be "connected" to another part, this includes not only "direct connection" but also "indirect connection" with other elements interposed therebetween. Furthermore, when a part is said to "include" a certain component, unless otherwise stated, this does not exclude the inclusion of such other components but rather implies that the part may include such other components.

[0023] The terms "first," "second," and "third" are used to describe various parts, components, regions, layers, and / or segments, but are not intended to be limiting. These terms are used solely to distinguish one part, component, region, layer, or segment from another. Therefore, a reference to a first part, component, region, layer, or segment below may also refer to a second part, component, region, layer, or segment without departing from the scope of the present invention.

[0024] Furthermore, as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It should be further understood that the terms "comprise", "include" indicate the presence of the described features, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Thus, "A, B, or C" or "A, B, and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B, and C". Exceptions to this definition occur only when the combination of elements, functions, or operations is inherently mutually exclusive in some way.

[0025] In one embodiment of the present invention, a quality monitoring system for deep penetration keyhole non-metallic inert gas (NiGM) shielded welding is provided. This system uses a ring laser to perform online three-dimensional scanning of the weld morphology before, during, and after welding. Furthermore, during the welding process, the system collects real-time data on the welding gun's current and voltage signals, arc sound signals, and images of the weld pool's front surface and the arc morphology during the welding process. This data is then integrated and analyzed to achieve online monitoring of welding quality. This system achieves online detection of welding quality through multi-dimensional data collection, significantly improving the efficiency and accuracy of welding quality testing.

[0026] The following is a detailed description of the embodiments of the present invention with reference to the accompanying drawings so that those skilled in the art can easily implement the present invention. The present invention can be embodied in many different forms and is not limited to the embodiments described herein.

[0027] like Figure 1 , which shows a structural schematic diagram of a quality monitoring system for deep penetration keyhole non-melting inert gas shielded welding in an embodiment of the present invention.

[0028] The welding object of the present application is a weldment, which can be of any structure, such as a plate structure or a cylindrical structure; and a welding gun is used to perform deep penetration keyhole non-melting inert gas shielded welding on the target weld of the weldment;

[0029] The system comprises:

[0030] The weld morphology annular laser three-dimensional scanning module 1 is provided near the target weld and needs to ensure that it can scan the target weld; the annular laser scanning module is used to perform three-dimensional scanning of the target weld morphology of the welded part before deep penetration keyhole non-melting inert gas shielded welding is performed on the target weld of the welded part using a welding gun, and to collect corresponding weld scanning data before welding, weld scanning data during welding, and weld morphology data after welding;

[0031] The welding electrical signal acquisition module 2 is located near the welding gun and is used to collect the current signal of the welding gun connected to it and the welding voltage signal data between the tungsten electrode of the welding gun and the welding material in real time during the welding process;

[0032] The welding arc sound signal acquisition module 3 is located near the welding gun and is used to collect the arc sound signal data generated by the welding gun in real time during the welding process;

[0033] The molten pool front and welding process arc morphology image monitoring module 4 is used to obtain the front molten pool image of the target weld seam of the welded part and the arc morphology image output by the welding gun, and collects the molten pool image data of the front molten pool image of the welded part and the arc morphology image data of the welding gun in real time during the welding process;

[0034] The welding quality monitoring system 5 is connected to the weld morphology ring laser three-dimensional scanning module 1, the welding electrical signal acquisition module 2, the welding arc sound signal acquisition module 3, and the welding arc morphology and molten pool image acquisition module 4, and is used to fuse the collected weld scanning data before welding, the weld scanning data during welding, the weld contour data after welding, the current and voltage signal data, the arc sound signal data, the molten pool image on the front of the weldment, and the arc morphology image data output by the welding gun to perform welding quality detection, so as to obtain the deep penetration keyhole non-melting inert gas shielded welding quality detection result corresponding to the target weld.

[0035] In one embodiment, the weld morphology annular laser three-dimensional scanning device includes: Figure 2 As shown, a heavy-loaded tripod bracket 108, a forward and backward moving linear guide rail 102, a drive motor 101, and a weld seam profile ring laser 3D scanning module 100 installed on the moving guide rail 102, and a high-precision grating displacement sensor is installed on the linear motion guide rail; the weld seam profile ring laser 3D scanning module includes: a conical mirror 103 arranged along the same optical axis and integrated in a transparent glass tube 107, a laser collimating and expanding lens group 104, a laser 105 and a CCD camera 106; the ring laser profile can image the inner contour of the cylindrical hollow structure.

[0036] Among them, the conical mirror 103 is used to convert the laser emitted by the laser 105 and expanded by the laser collimating and expanding lens group 104 into a ring laser, and the CCD imaging device 106 collects the pre-weld weld scanning data, the weld scanning data during welding, and the weld contour data after welding of the target weld corresponding to the front and back scans.

[0037] In a preferred embodiment, the weld morphology annular laser three-dimensional scanning module drives the corresponding forward and backward movement through a forward and backward movement driving device; wherein the forward and backward movement driving device includes a linear motion guide rail, a drive motor and a high-precision grating displacement sensor, etc.

[0038] In one embodiment, to solve the problem of scanning cylindrical workpieces, a heavy-duty tripod is used to install a motion platform and a weld seam morphology ring laser three-dimensional scanning device, which facilitates entry into the cylindrical workpiece and cooperates with the generated ring laser to perform weld scanning.

[0039] In one embodiment, the quality monitoring device includes:

[0040] The weld morphology annular laser three-dimensional scanning detection module is used to construct a corresponding three-dimensional model of the weld based on the splicing weld scanning data before welding, the weld scanning data during welding, and the weld three-dimensional contour data after welding, to obtain the weld morphology data before, during and after welding, so as to obtain the annular laser scanning detection result; specifically, the three-dimensional model of the weld is constructed through the point cloud data obtained by the annular laser scanning, thereby obtaining the weld morphology data before, during and after welding, so as to obtain the annular laser scanning detection result.

[0041] The welding current and voltage detection module is used to perform FFT analysis on the collected current signal, welding voltage signal data between the welding gun tungsten electrode and the welding material, and obtain the welding current and welding voltage signal spectrum detection results between the welding gun tungsten electrode and the welding material based on the signal strength of a specific frequency band; specifically, the collected welding current and voltage signals are subjected to fast Fourier spectrum analysis, and by monitoring the signal strength of certain specific frequency bands, when it changes, it can be judged that defects such as lack of penetration or welding through occur during the welding process, so as to facilitate compensation and improve welding quality.

[0042] The welding arc sound signal detection module filters and performs spectrum analysis on the collected arc sound signal data, and obtains the arc sound signal detection results through the signal strength of a specific frequency band. Specifically, the collected signal is filtered to eliminate the noise interference generated by the factory itself, and then the filtered signal is subjected to spectrum analysis. The change in signal strength in a certain frequency band is used to determine defects such as lack of penetration or welding during the welding process, and the welding defects are determined in conjunction with the collected current and voltage signals.

[0043] The weld pool and arc profile image detection module is used to obtain the weld pool's size, shape, and position relative to the weld center based on the weld pool image data collected from the front of the welded part, generating weld pool front-view image detection results. The module also extracts arc profile image features from the weld pool data collected during welding, analyzes any anomalies in these features, and predicts quality issues that may arise during welding to obtain weld arc profile image detection results. Specifically, the module processes the weld pool image to detect its boundaries and then measures its size, various shape parameters, and position relative to the weld center. After separating the weld pool from the rest of the image, it uses block analysis tools to calculate and measure various parameters, such as its centroid, area, perimeter, boundary, and roundness. This information is combined to reveal the weld pool's formation process, the presence of burn-through defects, whether the welding gun is aligned with the weld center, and other desired information. Furthermore, the module analyzes the arc profile image output by the tungsten electrode during welding and processes it through image segmentation and other methods to correlate this information with weld quality, enabling real-time assessment of weld quality.

[0044] The welding quality analysis module is connected to the weld morphology annular laser three-dimensional scanning detection module, the weld morphology annular laser three-dimensional scanning module, the welding current and voltage detection module, the arc sound signal detection module, the welding molten pool and arc morphology image detection module, and is used to integrate the annular laser scanning detection results, the annular laser weld three-dimensional scanning detection results, the welding current and the welding current and voltage signal spectrum detection results between the welding gun tungsten electrode and the welding material, the arc sound signal detection results, the molten pool front image detection results, the welding front molten pool and the welding arc morphology image detection results, and the welding process arc morphology image detection results to comprehensively analyze and evaluate the welding quality to obtain the deep penetration keyhole non-melting inert gas shielded welding quality detection results. Specifically, welding quality analysis is performed based on the annular laser scanning detection results, welding current and voltage detection results, arc sound signal detection results, front molten pool image, and arc morphology image detection results output by the welding gun. Different weights and judgment rules can also be set for the annular laser scanning detection results, welding current and voltage detection results, arc sound signal detection results, front molten pool image, and arc morphology image output by the welding gun for comprehensive analysis to obtain the final quality inspection result.

[0045] like Figure 5 As shown, a preliminary display of the acquisition results of the front molten pool image and the arc morphology image output by the welding gun in an embodiment of the present invention is shown. Figure 5 It consists of four pictures in total: the upper left picture represents a picture when the floor drain is melted through during welding; the upper right picture represents a picture when the back height is too high during welding; the lower left picture represents a picture when the welding forming quality is good during welding; the lower right picture represents a picture when the welding is not fully penetrated during welding.

[0046] In one embodiment, the weld morphology ring laser three-dimensional scanning detection module includes:

[0047] The pre-weld weld inspection unit constructs a 3D model of the target weld based on pre-weld weld scan data to determine the weld width, misalignment, and center trajectory. Specifically, before welding begins, a conical mirror converts collimated laser light into annular light, scanning the weld from front to back. The point cloud data generated by the annular laser scan is used to construct a 3D weld model, providing data such as the weld width, misalignment, and center trajectory. This data is fed back to the welding gun control system, enabling offline generation of the welding trajectory to guide automated welding.

[0048] The weld detection unit during welding is used to construct a three-dimensional model of the current target weld based on the real-time weld scanning data collected during welding, in order to obtain the weld width, misalignment, center trajectory, weld weld width, and weld height of the target weld during the welding process. Specifically, during the welding process, a portion of the weld is exposed, so the data is divided into two parts: one part is the weld width, misalignment, and center trajectory during welding; the other part is the weld weld width and weld height. The multi-segment linear fitting image can quickly and accurately determine whether the welding gun is correctly aligned with the weld center. In addition, the obtained weld width and weld height of the back weld are matched with the welding current and speed, combined with the material and thickness of the welded plate, and the weld width and misalignment obtained based on the previous weld, and a comprehensive analysis is performed to judge the quality of the weld based on the morphology.

[0049] The post-weld weld detection unit is used to construct a three-dimensional model of the current target weld based on the collected weld contour data to obtain the weld width and weld height of the target weld after welding; specifically, after welding is completed, the collimated laser is converted into annular light by a conical mirror, and the weld is scanned front and back. The three-dimensional model of the weld is constructed using the point cloud data obtained by the annular laser scanning. At the same time, by performing multi-segment linear fitting on the collected laser point cloud, the weld width and weld height of the front and back welds can be calculated separately through different fitting calculations. The weld width and weld height of the collected back weld are matched with the welding current and speed, and then combined with the material and thickness of the welded plate and the weld width and misalignment of the weld obtained before welding for a comprehensive analysis, so that the quality of the welding can be judged in terms of morphology.

[0050] The weld seam morphology change detection unit is connected to the weld seam detection unit before welding, the weld seam detection unit during welding and the weld seam detection unit after welding, and is used to judge the weld seam morphology change of the target weld seam before welding, the seam width, misalignment, center trajectory, weld seam molten width and molten height during welding, and the molten width and molten height of the target weld after welding, and obtain the annular laser scanning detection result; based on the above obtained data, after corresponding to the welding current and speed, combined with the material, thickness of the welding plate and the obtained weld seam width and misalignment before welding, a comprehensive analysis is performed to judge the quality of the welding in terms of morphology.

[0051] In one embodiment, the welding arc profile and molten pool image acquisition module 3 includes a high-speed camera device positioned on the front face of the target weld seam of the welded component, configured to capture real-time molten pool image data and arc profile image data from both front faces of the welded component during the welding process. Specifically, during the welding process, a high-speed camera equipped with a filter is mounted to simultaneously capture and store images of the molten pool and arc profile from the front face of the welded plate.

[0052] In one embodiment, the welding electrical signal acquisition module 2 uses a Hall effect sensor to convert the welding gun's current signal into current signal data, which can be collected by a data acquisition card, as well as the welding voltage signal between the welding gun's tungsten electrode and the weld material. Specifically, the Hall effect sensor converts the high current (>300A) during K-TIG welding into a small, collectible current signal, while also collecting the welding voltage signal between the welding gun's tungsten electrode and the weld material.

[0053] In one embodiment, the arc sound signal acquisition device includes: a microphone welding sound signal acquisition device.

[0054] In order to better illustrate the quality monitoring system for deep penetration keyhole non-metallic inert gas shielded welding, the present invention provides the following specific embodiments.

[0055] Example 1: A quality monitoring system for deep penetration keyhole non-metallic inert gas shielded welding. Figure 4 The figure shows the structure diagram of the quality monitoring system of deep penetration keyhole non-melting inert gas shielded welding.

[0056] The system comprises:

[0057] Welding electrical signal acquisition device, welding pool and arc profile acquisition device (CCD), welding sound signal acquisition microphone, weld seam profile ring laser 3D scanning device (not shown), and a computer connecting the various devices;

[0058] The specific detection process is as follows Figure 4 As shown, the following steps are included:

[0059] Pre-weld weld width inspection: Before welding begins, the conical mirror of the annular laser scanner converts the collimated laser light into an annular beam, which is then scanned back and forth across the weld using a motion mechanism. The point cloud data generated by the annular laser scanning is used to construct a 3D weld model, providing data such as the weld width, misalignment, and center trajectory. This data is fed back to the welding gun control system, which generates an offline weld trajectory to guide automated welding.

[0060] Welding current and voltage monitoring during welding: A Hall effect sensor converts the high current (>300A) during K-TIG welding into a small current signal that can be acquired by a data acquisition card. The voltage signal from the welding torch tungsten electrode to the weld material is simultaneously collected. Fast Fourier transform spectrum analysis is performed on the collected current and voltage signals. By monitoring the signal strength in specific frequency bands, fluctuations in these frequencies can be used to identify defects such as incomplete penetration or weld penetration during welding, allowing for compensation and improved welding quality.

[0061] Arc sound signal monitoring during welding: A microphone is installed near the welding torch, and an acquisition card collects the acoustic signals generated by the arc during welding. The collected signals are filtered to eliminate noise interference generated by the factory itself, and the filtered signals are then subjected to spectrum analysis. Changes in signal intensity within a certain frequency band are used to identify defects such as incomplete penetration or weld penetration during welding. This information is then combined with the welding electrical signal to determine welding quality.

[0062] Monitoring the frontal weld pool image and the arc profile output from the welding torch during welding: During welding, a high-speed camera equipped with a filter simultaneously captures and stores images of the weld pool and arc profile from the front of the weld plate. These images are then processed to detect the weld pool boundary and measure its dimensions, various shape parameters, position relative to the weld center, and arc profile and contour. After separating the weld pool from the rest of the image, block analysis tools are used to calculate and measure various parameters, such as centroid, area, perimeter, boundary, and roundness. This information is combined to reveal the weld pool formation process, the presence of burn-through defects, whether the welding torch is aligned with the weld center, and other desired information. Combined with the arc profile, a comprehensive assessment of weld quality is made.

[0063] Detection of weld contour after welding: After welding begins, the collimated laser is converted into annular light by a conical mirror, and the weld is scanned forward and backward by a motion mechanism. A three-dimensional model of the weld is constructed using the point cloud data obtained through the annular laser scanning. At the same time, by performing multi-segment linear fitting on the collected laser point cloud, the weld width and weld height of the front and back welds can be calculated separately through different fitting calculations. The image of the multi-segment linear fitting can quickly and accurately determine whether the welding gun is correctly aligned with the center of the weld. In addition, the obtained weld width and weld height of the back weld are matched with the welding current and speed, and then combined with the material and thickness of the welded plate and the weld width and misalignment amount before welding obtained in step one for comprehensive analysis, so that the quality of the welding can be judged based on the morphology.

[0064] Finally, the above test results are integrated and analyzed to obtain the final deep penetration keyhole non-melting inert gas shielded welding quality test results.

[0065] Compared with the existing K-TIG weld quality inspection technology, this embodiment differs in that: (1) a conical mirror is used to generate a ring laser to scan the weld instead of the traditional line laser, which not only expands the laser detection width but also makes it more convenient to detect the back weld morphology of cylindrical workpieces. (2) A high-speed camera is integrated to monitor the molten pool and arc morphology in real time during the welding process, and the welding current signal, the voltage signal between the tungsten electrode of the welding gun and the welding material, and the arc sound signal are collected in real time to comprehensively evaluate the welding quality.

[0066] In summary, the quality monitoring system for deep penetration keyhole non-melting inert gas shielded welding of the present invention achieves online monitoring of welding quality by using a ring laser to perform three-dimensional scanning of the weld before, during, and after welding. It also collects welding current, voltage signal data, arc sound signal data, front molten pool data, and arc morphology image data output by the welding gun in real time during the welding process, and performs comprehensive analysis of the above data. The present invention uses the collected data from multiple dimensions to detect and comprehensively evaluate welding quality, greatly improving the efficiency and accuracy of welding quality detection. This invention effectively overcomes the shortcomings of the existing technology and has excellent application value.

[0067] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, any equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A quality monitoring system for deep penetration keyhole non-metallic inert gas shielded welding, characterized in that: The system comprises: The weld seam morphology ring laser 3D scanning module is used to perform 3D scanning of the weld seam morphology before deep penetration keyhole non-melting inert gas shielded welding, the weld seam gap and misalignment before welding, and the weld seam morphology during and after welding, so as to collect the corresponding weld seam scanning data before welding, during welding, and after welding. Welding electrical signal acquisition module, used to collect welding current signal and welding voltage signal data between the welding gun tungsten electrode and welding material in real time during the welding process; Welding arc sound signal acquisition module, used to collect arc sound signal data generated by the welding gun in real time during the welding process; The welding arc profile and molten pool image acquisition module is used to collect the molten pool image data of the front of the weldment and the arc profile image data of the welding process in real time during the welding process; The welding quality monitoring system is connected to the weld morphology ring laser three-dimensional scanning module, the welding electrical signal acquisition module, the welding arc sound signal acquisition module, and the welding arc morphology and molten pool image acquisition module, and is used to comprehensively evaluate the welding quality based on the collected weld scanning data before welding, the weld scanning data during welding, the weld morphology data after welding, the current and voltage signal data, the arc sound signal data, the molten pool image data on the front of the weldment, and the arc morphology image data during the welding process, so as to obtain the deep penetration keyhole non-melting inert gas shielded welding quality corresponding to the target weld.

2. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: The weld seam profile annular laser 3D scanning module comprises: a linear guide rail mounted on a heavy tripod for forward and backward motion, a drive motor, and a weld seam profile annular laser 3D scanning assembly mounted on the linear guide rail; the weld seam profile annular laser 3D scanning assembly comprises: a conical mirror arranged along the same optical axis and integrated into a transparent glass tube, a laser collimating and beam expanding lens group, a laser, and a CCD camera; Among them, the conical mirror is used to convert the laser emitted by the laser and expanded by the laser collimating and expanding lens group into a ring laser, and the CCD camera collects the pre-welding specimen splicing condition scanning data, the weld scanning data during welding, and the weld contour data after welding of the target weld scanned before and after.

3. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: The quality monitoring system includes: The weld seam morphology annular laser 3D scanning detection module is used to construct a 3D model of the corresponding weld seam based on the scanning data of the spliced ​​weld seam before welding, the scanning data of the weld seam during welding, and the 3D contour data of the weld seam after welding, to obtain the weld seam morphology data before, during, and after welding, so as to obtain the annular laser scanning detection results; The welding current and voltage detection module is used to perform FFT analysis based on the collected current signal and the welding voltage signal data between the welding gun tungsten electrode and the welding material, and obtain the welding current and welding voltage signal spectrum detection results between the welding gun tungsten electrode and the welding material based on the signal strength of a specific frequency band; The welding arc sound signal detection module filters and performs spectrum analysis on the collected arc sound signal data, and obtains the arc sound signal detection results based on the signal strength in a specific frequency band; The welding pool and welding arc profile image detection module is used to obtain the size and shape parameters of the molten pool and its position relative to the center of the weld based on the collected molten pool image data of the front of the weldment, and obtain the molten pool front image detection result; extract the collected arc profile image data of the welding process, analyze the abnormalities of the arc profile image features, predict the quality problems generated during the welding process, and obtain the welding arc profile image detection result; The welding quality analysis module is connected to the weld morphology annular laser three-dimensional scanning detection module, the welding current and voltage detection module, the arc sound signal detection module, the welding molten pool and arc morphology image detection module, and is used to integrate the annular laser scanning detection results, the welding current and the welding voltage signal spectrum detection results between the welding gun tungsten electrode and the welding material, the arc sound signal detection results, the molten pool front image detection results and the welding arc morphology image detection results to comprehensively analyze and evaluate the welding quality, so as to obtain the deep penetration keyhole non-melting inert gas shielded welding quality detection results.

4. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 3, characterized in that: The weld seam morphology ring laser three-dimensional scanning detection module includes: The pre-weld weld detection unit is used to construct a three-dimensional model of the current target weld based on the pre-weld weld scanning data to obtain the weld width, misalignment and center trajectory of the target weld before welding; The welding seam detection unit is used to build a three-dimensional model of the current target weld according to the real-time collected welding seam scanning data, so as to obtain the seam width, misalignment, deformation and change of the center trajectory, back weld width and weld height of the target weld during the welding process; The post-weld weld detection unit is used to construct a three-dimensional model of the current target weld based on the collected double-side profile data of the weld to obtain the weld width and weld height weld morphology parameters of the target weld after welding; The weld seam profile change detection unit is connected to the weld seam detection unit before welding, the weld seam detection unit during welding and the weld seam detection unit after welding, and is used to judge the weld seam profile change based on the seam width, misalignment amount and center trajectory of the target weld before welding, the seam width, misalignment amount, center trajectory, weld width and weld height during welding, and the weld width and weld height of the target weld after welding.

5. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: When the welded part is a cylindrical hollow structure, the annular laser 3D scanning module enters the cylindrical hollow structure through a motion mechanism mounted on a heavy-duty tripod to perform 3D scanning of the weld. Wherein, the heavy-duty tripod and motion mechanism include: A linear motion guide rail, a drive motor, and a ring laser 3D scanning module mounted on a heavy-duty tripod. A high-precision grating displacement sensor is mounted on the linear motion guide rail. The annular laser three-dimensional scanning module includes: A conical mirror, a laser collimating and beam expanding lens set, a laser, and a camera are arranged along the same optical axis and integrated into a transparent glass tube. The annular laser profile can image the inner contour of a cylindrical hollow structure. Driven by a heavy-duty tripod, the ring laser 3D scanning module scans the weld of the specimen and constructs 3D data of the weld morphology by combining the data collected by the high-precision grating displacement sensor.

6. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: The welding arc profile and molten pool image acquisition module includes: a high-speed camera device arranged on the front side of the target weld of the weldment, which is used to collect the molten pool and arc profile image data on the front side of the weldment in real time during the welding process.

7. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: The welding arc sound signal acquisition module is used to convert the large current signal of welding into current signal data that can be collected by the data acquisition card through the Hall sensor, and at the same time collect the welding voltage signal between the tungsten electrode of the welding gun and the welding material.

8. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: The arc sound signal is collected by using a microphone, and abnormalities of the sound signal during the welding process are analyzed.

9. The quality monitoring system for deep penetration keyhole non-metallic inert gas welding according to claim 1, characterized in that: The weld seam profile annular laser three-dimensional scanning module drives the corresponding forward and backward movement through a forward and backward movement driving device; the forward and backward movement driving device is a driving motor, a linear guide rail and a high-precision grating displacement sensor.

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