Integrated detection platform for mechanical property and microstructure of welding test piece

Abstract

The invention relates to the technical field of welding quality evaluation, in particular to a welding test piece mechanical property and microstructure integrated detection platform which comprises six steps of three-dimensional shape data acquisition, detection path planning, in-situ mechanical property testing, zero displacement mode switching and same-point microstructure acquisition and data fusion output. A three-dimensional model of the surface of a test piece is constructed through a laser scanner, a detection path coordinate set containing a fusion line and a heat affected zone is generated, and a nanoindentor is used for applying a preset load to a selected coordinate point to obtain mechanical response. And then the confocal microscope module is switched in through zero displacement switching, and a microstructure image corresponding to a mechanical test point is acquired. And finally, data of the same coordinate point is subjected to space matching, a performance-structure correlation map is constructed, and high-precision and multi-scale integrated detection of the welding area is achieved. The platform improves the detection precision and consistency, and can be widely applied to welding process verification, material service performance analysis, microdefect evaluation and other scenes.

Description

Technical Field

[0001] This invention relates to the field of welding quality assessment technology, and in particular to an integrated testing platform for the mechanical properties and microstructure of welded specimens. Background Technology

[0002] In the field of welded structure quality evaluation, mechanical property testing and microstructure analysis are crucial means to ensure joint strength and service reliability. Traditional testing procedures typically treat nanoindentation testing and metallographic image observation as two separate steps, used to obtain the mechanical response and microstructure characteristics of the material at the microscale, respectively. However, with the development of advanced manufacturing technologies, welded joint areas exhibit significant microstructural inhomogeneity and heat-affected zone refinement effects, making it difficult for single physical quantity tests to comprehensively reflect local performance variation trends. Therefore, establishing an integrated testing method capable of simultaneously acquiring mechanical response parameters and microstructure images at the same spatial location has become an important development direction for high-end welded quality analysis and quantitative microstructure assessment.

[0003] Current testing technologies often employ manual positioning or image comparison to match regions across different testing devices, resulting in problems such as large spatial positioning errors, unclear tissue correspondences, and poor test repeatability. Furthermore, detection path planning relies on manual point selection, lacking adaptive optimization capabilities based on morphological data, making it difficult to balance detection efficiency with regional representativeness. In addition, the analysis results of microstructure and mechanical response are often output separately, lacking a systematic data fusion mechanism, and thus unable to support quantitative analysis of the impact of weld micro-defects on performance. Summary of the Invention

[0004] To achieve the above objectives, the present invention provides an integrated testing platform for the mechanical properties and microstructure of welded specimens.

[0005] An integrated testing platform for the mechanical properties and microstructure of welded specimens includes the following steps: S1, Acquisition of three-dimensional morphology data: Acquire three-dimensional morphology data of the surface of the welded specimen using a laser scanner; S2, Detection path planning: Based on the three-dimensional topography data, identify the weld area and generate a detection path coordinate set including the fusion line and heat-affected zone; S3, In-situ mechanical property test: The nanoindenter is driven to apply a preset load to the target coordinate point according to the detection path coordinate set, and mechanical response data is collected simultaneously. S4, Zero Displacement Mode Switching: Keep the specimen position unchanged, move the indenter out of the observation optical path, and switch to the confocal microscope observation module; S5, Microstructure acquisition at the same point: Based on the detection path coordinate set, locate the mechanical test point and obtain the microstructure image of the indentation area; S6, Data Fusion Output: Spatially match the mechanical response data at the same coordinate point with the microstructure image to generate a mechanical property-microstructure correlation map.

[0006] Optionally, S1 includes: S11: Start the laser scanner, set the scanning resolution parameters and focal length calibration value to ensure full coverage of the surface of the welding specimen; S12: Perform the scanning task to acquire three-dimensional point cloud data of the surface of the welding specimen; S13: Denoise and reconstruct the three-dimensional point cloud data to generate a complete three-dimensional morphological model of the welding specimen; S14: Construct the weld geometric feature extraction region based on the three-dimensional morphology model, and output the morphology feature database.

[0007] Optionally, S2 includes: S21: Based on the three-dimensional topography model constructed in S1, the topography gradient analysis algorithm is used to identify the weld contour region. The topography gradient analysis algorithm is expressed as: ; in, Indicates the welding test piece at point The three-dimensional topographic gradient value at that location, Represents the two-dimensional coordinates of the surface of the welded specimen. The height function below, , They are respectively in , The rate of change of height in the direction, i.e. the degree of local surface tilt.

[0008] gradient value With preset threshold The comparison is used to determine whether the current point belongs to the weld contour area; S22: Divide the identified weld contour area into zones, distinguishing between the fusion line area and the heat-affected zone; S23: Construct a gridded set of coordinate points within each region to generate a detection path coordinate set containing 3D coordinates and corresponding region labels; S24: Sort and optimize the detection path coordinate set, eliminate possible interference areas, and output the final detection path coordinate set.

[0009] Optionally, S3 includes: S31: Read the detection path coordinate set and drive the nanoindenter to position itself to each coordinate point in sequence; S32: Apply a preset load at each coordinate point and collect load-displacement data throughout the loading-unloading process; S33: Perform nonlinear fitting on the original load-displacement curve to extract representative mechanical response parameters, including elastic modulus and hardness.

[0010] S34: Associate and store the extracted mechanical response parameters with the corresponding coordinate points to form an in-situ mechanical performance test result set.

[0011] Optionally, S4 includes: S41: Lock the spatial position of the welding specimen to prevent micro-displacement deviation caused by switching operations; S42: Move the nanoindenter out of the observation optical path along the slide rail; S43: Synchronously start the confocal microscope observation module and focus on the current indentation test area; S44: Complete the switching of observation channels between the indenter and the microscope.

[0012] Optionally, S5 includes: S51: Call the detection path coordinate set and drive the confocal microscope to locate the corresponding indentation point; S52: Adjust the light intensity and depth of focus parameters to focus on the center area of ​​the indentation; S53: Obtain multi-scale microstructure images in the indentation area, including metallographic features, grain boundaries, pores or crack information; S54: Label each image with its coordinate points, region attributes, and image sharpness score to construct a microscopic tissue image database.

[0013] Optionally, S6 includes: S61: Call the in-situ mechanical property test result set and microstructure image database; S62: Spatial matching based on coordinate labels, pairing mechanical response parameters at the same coordinate point with microstructure images; S63: Construct a two-dimensional correlation map, where the horizontal axis represents the tissue image and the vertical axis represents the corresponding mechanical parameters such as elastic modulus and hardness. S64: Outputs a visual mechanical property-microstructure correlation map to evaluate the performance consistency of welds and the impact of micro-defects on performance.

[0014] The beneficial effects of this invention are: This invention utilizes a laser scanner to construct a high-resolution three-dimensional morphology model and automatically plans the detection path based on morphological features, achieving accurate identification and gridded coordinate point division of the weld fusion line and heat-affected zone. Furthermore, by using a unified detection path coordinate set, it drives a nanoindenter and a confocal microscope to perform mechanical testing and microscopic image acquisition at identical spatial points, avoiding spatial offset problems caused by displacement errors in traditional detection methods, and significantly improving data consistency and repeatability.

[0015] This invention utilizes a platform that integrates and coordinates indentation testing and microscopic imaging via steps S3 to S5. This allows for device channel switching while keeping the specimen stationary, avoiding error accumulation caused by manual mold changing or secondary positioning. By applying a standard load to the same coordinate point and acquiring high-precision microscopic images, it enables direct comparison and quantitative coupling between local elastic modulus, hardness, and other indicators with microstructures such as grain size and crack distribution. This breaks through the traditional "point measurement-image observation" separation mode, achieving simultaneous analysis of performance and structure.

[0016] This invention utilizes a platform that constructs a structure-performance correlation map by spatially matching the mechanical response data obtained from testing with the acquired microscopic images. This map supports the fusion display of two-dimensional images and mechanical parameters, providing intuitive data support for the strength distribution, abnormal microstructure identification, and failure prediction of welded joint areas. Furthermore, the map can be exported and integrated into external data analysis platforms, facilitating the formation of standardized evaluation models and enabling intelligent welding quality inspection and traceability analysis. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the detection platform process according to an embodiment of the present invention. Detailed Implementation

[0019] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should also be noted that, to make the embodiments more comprehensive, the following embodiments are the best and preferred embodiments, and those skilled in the art can use other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0020] It should be noted that the use of terms such as "an embodiment," "an embodiment," "an exemplary embodiment," and "some embodiments" in the specification indicates that the described embodiment may include a specific feature, structure, or characteristic, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Furthermore, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such a feature, structure, or characteristic in conjunction with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the art.

[0021] Generally, terms can be understood at least partly from their use in context. For example, depending at least partly on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in a singular sense, or a combination of features, structures, or characteristics in a plural sense. Additionally, the term "based on" can be understood not necessarily to convey an exclusive set of factors, but rather, alternatively, depending at least partly on the context, to allow for the presence of other factors that are not necessarily explicitly described.

[0022] like Figure 1 As shown, an integrated testing platform for the mechanical properties and microstructure of welded specimens includes the following steps: S1, Acquisition of three-dimensional morphology data: Acquire three-dimensional morphology data of the surface of the welded specimen using a laser scanner; S2, Inspection Path Planning: Based on three-dimensional topography data, identify the weld area and generate a set of inspection path coordinates including fusion line and heat-affected zone; S3, In-situ Mechanical Performance Testing: Based on the detection path coordinate set, the nanoindenter is driven to apply a preset load to the target coordinate point and mechanical response data is collected simultaneously. S4, Zero Displacement Mode Switching: Keep the specimen position unchanged, move the indenter out of the observation optical path, and switch to the confocal microscope observation module; S5, Same-point microstructure acquisition: Based on the detection path coordinate set, locate the mechanical test point and obtain the microstructure image of the indentation area; S6, Data Fusion Output: Spatially match the mechanical response data at the same coordinate point with the microstructure image to generate a mechanical property-microstructure correlation map.

[0023] S1 includes: S11: Start the laser scanner, set the scanning resolution parameters and focal length calibration value to ensure full coverage of the surface of the welding specimen; S12: Perform the scanning task to acquire three-dimensional point cloud data of the surface of the welding specimen; S13: Denoise and reconstruct the three-dimensional point cloud data to generate a complete three-dimensional morphological model of the welding specimen; S14: Construct the weld geometric feature extraction region based on the three-dimensional morphology model and output the morphology feature database; The laser scanner acquires three-dimensional point cloud data of the welded specimen and constructs a complete three-dimensional morphology model, providing high-precision input for the accurate planning of subsequent inspection paths.

[0024] S2 includes: S21: Based on the three-dimensional topography model constructed in S1, the topography gradient analysis algorithm is used to identify the weld contour region. The topography gradient analysis algorithm is expressed as: ; in, Indicates the welding test piece at point The three-dimensional topographic gradient value at that location, Represents the two-dimensional coordinates of the surface of the welded specimen. The height function below, , They are respectively in , The rate of change of height in the direction, i.e. the degree of local surface tilt.

[0025] gradient value With preset threshold The comparison is used to determine whether the current point belongs to the weld contour area; S22: Divide the identified weld contour area into zones, distinguishing between the fusion line area and the heat-affected zone; S23: Construct a gridded set of coordinate points within each region to generate a detection path coordinate set containing 3D coordinates and corresponding region labels; S24: Sort and optimize the detection path coordinate set, remove possible interference areas, and output the final detection path coordinate set; By identifying weld areas and constructing gridded inspection paths, precise planning of fusion lines and heat-affected zones can be achieved, ensuring spatial consistency and comprehensive coverage of subsequent mechanical testing and tissue sampling.

[0026] S3 includes: S31: Read the detection path coordinate set and drive the nanoindenter to position itself to each coordinate point in sequence; S32: Apply a preset load at each coordinate point and collect load-displacement data throughout the loading-unloading process; S33: Perform nonlinear fitting on the original load-displacement curve to extract representative mechanical response parameters, including elastic modulus and hardness. Among these, the elastic modulus... The calculation is as follows: ; in, Indicates the indentation modulus, used to characterize the elastic response of a localized material. This represents the initial slope, or contact stiffness, during the unloading phase of the nanoindenter. The indentation contact area is typically determined by the indentation depth and the indenter geometry. In nanoindentation testing, It can be converted into the intrinsic elastic modulus of the material by setting the instrument. This is used to further analyze the differences in the mechanical properties of the weld.

[0027] S34: Associate and store the extracted mechanical response parameters with the corresponding coordinate points to form an in-situ mechanical performance test result set; By applying precise loads at the coordinate points of the detection path and extracting mechanical response parameters, in-situ quantitative characterization of the mechanical properties of welded specimens at multiple points was achieved.

[0028] S4 includes: S41: Lock the spatial position of the welding specimen to prevent micro-displacement deviation caused by switching operations; S42: Move the nanoindenter out of the observation optical path along the slide rail; S43: Synchronously start the confocal microscope observation module and focus on the current indentation test area; S44: Complete the switching of the observation channel between the indenter and the microscope; The observation mode was switched while keeping the original position of the specimen unchanged, ensuring spatial consistency between the microstructure image acquisition and the mechanical testing area.

[0029] S5 includes: S51: Call the detection path coordinate set and drive the confocal microscope to locate the corresponding indentation point; S52: Adjust the light intensity and depth of focus parameters to focus on the center area of ​​the indentation; S53: Obtain multi-scale microstructure images in the indentation area, including metallographic features, grain boundaries, pores or crack information; S54: Label each image with its coordinate points, region attributes, and image sharpness score to construct a microscopic tissue image database; High-resolution microstructure images are acquired at in-situ indentation points to achieve visualized recording of the tissue structure at mechanical test points.

[0030] S6 includes: S61: Call the in-situ mechanical property test result set and microstructure image database; S62: Spatial matching based on coordinate labels, pairing mechanical response parameters at the same coordinate point with microstructure images; S63: Construct a two-dimensional correlation map, where the horizontal axis represents the tissue image and the vertical axis represents the corresponding mechanical parameters such as elastic modulus and hardness. S64: Outputs a visual mechanical property-microstructure correlation map to evaluate the performance consistency of welds and the impact of micro-defects on performance; The above steps achieve a precise fusion of mechanical response and microstructure based on spatial coordinates, generating an integrated performance-structure analysis map of the welded area.

[0031] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0032] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An integrated testing platform for the mechanical properties and microstructure of welded specimens, characterized in that, Includes the following steps: S1, Acquisition of three-dimensional morphology data: Acquire three-dimensional morphology data of the surface of the welded specimen using a laser scanner; S2, Detection path planning: Based on the three-dimensional topography data, identify the weld area and generate a detection path coordinate set including the fusion line and heat-affected zone; S3, In-situ mechanical property test: The nanoindenter is driven to apply a preset load to the target coordinate point according to the detection path coordinate set, and mechanical response data is collected simultaneously. S4, Zero Displacement Mode Switching: Keep the specimen position unchanged, move the indenter out of the observation optical path, and switch to the confocal microscope observation module; S5, Microstructure acquisition at the same point: Based on the detection path coordinate set, locate the mechanical test point and obtain the microstructure image of the indentation area; S6, Data Fusion Output: Spatially match the mechanical response data at the same coordinate point with the microstructure image to generate a mechanical property-microstructure correlation map.

2. The integrated testing platform for mechanical properties and microstructure of welded specimens according to claim 1, characterized in that, S1 includes: S11: Start the laser scanner, set the scanning resolution parameters and focal length calibration value to ensure full coverage of the surface of the welding specimen; S12: Perform the scanning task to acquire three-dimensional point cloud data of the surface of the welding specimen; S13: Denoise and reconstruct the three-dimensional point cloud data to generate a complete three-dimensional morphological model of the welding specimen; S14: Construct the weld geometric feature extraction region based on the three-dimensional morphology model, and output the morphology feature database.

3. The integrated testing platform for mechanical properties and microstructure of welded specimens according to claim 2, characterized in that, S2 includes: S21: Based on the three-dimensional topography model constructed in S1, the topography gradient analysis algorithm is used to identify the weld contour region. The topography gradient analysis algorithm is expressed as: ； in, Indicates the welding test piece at point The three-dimensional topographic gradient value at that location, Represents the two-dimensional coordinates of the surface of the welded specimen. The height function below, , They are respectively in , The rate of change of height in the direction, i.e. the degree of local surface tilt; gradient value With preset threshold The comparison is used to determine whether the current point belongs to the weld contour area; S22: Divide the identified weld contour area into zones, distinguishing between the fusion line area and the heat-affected zone; S23: Construct a gridded set of coordinate points within each region to generate a detection path coordinate set containing 3D coordinates and corresponding region labels; S24: Sort and optimize the detection path coordinate set, eliminate possible interference areas, and output the final detection path coordinate set.

4. The integrated testing platform for mechanical properties and microstructure of welded specimens according to claim 3, characterized in that, S3 includes: S31: Read the detection path coordinate set and drive the nanoindenter to position itself to each coordinate point in sequence; S32: Apply a preset load at each coordinate point and collect load-displacement data throughout the loading-unloading process; S33: Perform nonlinear fitting on the original load-displacement curve to extract representative mechanical response parameters, including elastic modulus and hardness; S34: Associate and store the extracted mechanical response parameters with the corresponding coordinate points to form an in-situ mechanical performance test result set.

5. The integrated testing platform for mechanical properties and microstructure of welded specimens according to claim 4, characterized in that, S4 includes: S41: Lock the spatial position of the welding specimen to prevent micro-displacement deviation caused by switching operations; S42: Move the nanoindenter out of the observation optical path along the slide rail; S43: Synchronously start the confocal microscope observation module and focus on the current indentation test area; S44: Complete the switching of observation channels between the indenter and the microscope.

6. The integrated testing platform for mechanical properties and microstructure of welded specimens according to claim 5, characterized in that, S5 includes: S51: Call the detection path coordinate set and drive the confocal microscope to locate the corresponding indentation point; S52: Adjust the light intensity and depth of focus parameters to focus on the center area of ​​the indentation; S53: Obtain multi-scale microstructure images in the indentation area, including metallographic features, grain boundaries, pores or crack information; S54: Label each image with its coordinate points, region attributes, and image sharpness score to construct a microscopic tissue image database.

7. The integrated testing platform for mechanical properties and microstructure of welded specimens according to claim 6, characterized in that, S6 includes: S61: Call the in-situ mechanical property test result set and microstructure image database; S62: Spatial matching based on coordinate labels, pairing mechanical response parameters at the same coordinate point with microstructure images; S63: Construct a two-dimensional correlation map, where the horizontal axis represents the tissue image and the vertical axis represents the corresponding mechanical parameters such as elastic modulus and hardness. S64: Outputs a visual mechanical property-microstructure correlation map to evaluate the performance consistency of welds and the impact of micro-defects on performance.

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