Method and system for detecting tensile strain mark limit

Abstract

The invention belongs to the field of mechanical property testing of metal materials, and relates to a method and a system for detecting tensile strain mark limit, the system applies tensile load to a metal plate sample through a test module, an illumination projection module projects a structured light pattern to the surface of the sample, and an image acquisition module continuously acquires surface images of the sample; and the data processing module is used for carrying out wrapped phase calculation, differential phase calculation, distortion parameter extraction and tensile strain mark initiation judgment on the image sequence, so that accurate positioning at the moment of tensile strain mark initiation and objective and quantitative measurement of the critical strain limit are realized. The method can effectively improve the detection sensitivity and accuracy of the material surface instability characteristics, realizes high-precision judgment at the moment of tensile strain mark initiation, and provides a reliable basis for material performance evaluation and quality control.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of mechanical property testing of metal materials, in particular to a method and system for detecting tensile strain mark limit. BACKGROUND

[0002] Tensile strain mark is a kind of surface defect that seriously affects the appearance quality of products during the stamping forming process of low carbon steel and other metal sheets due to uneven plastic deformation. In the prior art, there are mainly traditional tensile test method, manual visual observation method and other physical methods. The traditional tensile test method indirectly evaluates by measuring the yield point elongation on the stress-strain curve, which can only evaluate the risk size and cannot determine the accurate instant of defect initiation and the corresponding critical strain value. The manual visual observation method is observed by the inspector during the tensile process. This method completely depends on the subjective judgment of the person and has poor repeatability, and cannot realize standardization and automation. Other physical methods, such as infrared thermal imaging method, are easily disturbed by various noise signals, have low signal-to-noise ratio and face challenges in reliability.

[0003] Therefore, the invention patent with publication number CN115186459B discloses a strain adaptive calculation method for optical coherence elastography, which reconstructs the strain field distribution inside the composite material with high precision through the adaptive rotation model of differential phase combined with the light vector method. The adaptive rotation model combined with the vector method algorithm used in the present application does not have the problem of improving the strain calculation signal-to-noise ratio under multiplicative noise when using the least squares method. In addition, by constructing the adaptive rotation model of differential phase, the optimal rotation angle is found, and then combined with the light vector method, the inherent transverse non-uniformity is reduced to some extent, and the problem that the light vector method cannot construct the strain field distribution inside the composite material with low signal-to-noise ratio with high precision under strong noise and complex deformation conditions, especially the abnormal transverse non-uniformity, is solved.

[0004] Although the above technical solution can characterize the mechanical properties or strain distribution of the material to some extent, there are still deficiencies in the detection of strain marks during the stretching process of metal sheets. Firstly, the traditional method cannot accurately capture the initiation instant of strain mark; secondly, there is no judgment mechanism synchronized with the mechanical data, so the critical strain limit corresponding to the strain mark cannot be accurately obtained.

[0005] Therefore, it is necessary to provide a method and system for detecting tensile strain mark limit to solve the above-mentioned defects in the prior art. SUMMARY

[0006] The purpose of the present application is to solve the problem of inaccurate positioning of defect initiation instant, and to provide a method and system for detecting tensile strain mark limit to solve the above-mentioned technical problems in view of the technical defects of the prior art.

[0007] To achieve the above object, the present application provides the following technical solutions: In a first aspect, the present application provides a method for detecting the limit of tensile strain marks, comprising the following steps: Step S1: a step of test preparation, in which a tensile load is applied to a metal sheet sample during a material test, and observation data of surface changes of the sample are formed by structured light projection and image acquisition; Step S2: a step of phase processing, in which at least two consecutive images in the acquired image sequence are subjected to wrapped phase processing to obtain a phase distribution map reflecting surface micro-geometric mutations; Step S3: a step of distortion quantification, in which the difference between the two consecutive phase maps is calculated, and distortion parameters are extracted from the difference result for quantifying surface instability features; Step S4: a step of limit determination, in which the tensile strain mark initiation event is determined based on the comparison between the distortion parameters and a preset threshold, and the critical strain limit corresponding to the event is determined from the synchronous mechanical data.

[0008] In a second aspect, the present application further provides a system for detecting the limit of tensile strain marks, comprising: a test module, which is used to apply a tensile load to a metal sheet sample to form a tensile strain environment; an illumination projection module, which is used to project a stable structured light pattern onto the sample surface to realize surface topography information coding; an image acquisition module, which is used to continuously acquire an image sequence of the sample surface to record surface micro-changes during the tensile process; a data processing module, which is used to perform wrapped phase calculation, differential phase calculation, distortion parameter extraction, and tensile strain mark initiation determination on the acquired image sequence, and determine the critical strain limit.

[0009] The modules work cooperatively to realize accurate positioning of the tensile strain mark initiation moment and objective and quantitative detection of the critical strain limit.

[0010] The present application has the following advantages: The present application forms physical signals by structured light projection and image acquisition, and performs wrapped phase calculation, differential phase calculation, and distortion parameter extraction on the image sequence by combining with a data processing unit, thereby realizing objective and quantitative determination of the tensile strain mark initiation moment, eliminating human subjective factors, and improving detection accuracy and standardization level.

[0011] This invention utilizes the differential phase method to amplify micron-level surface geometric abrupt changes into significant signals, exhibiting high sensitivity and a high signal-to-noise ratio. It accurately captures the instantaneous abrupt changes during tensile strain mark initiation and can simultaneously acquire surface deformation information in two orthogonal directions, making the measurement results more robust. It is particularly suitable for the analysis of complex non-uniform deformation fields. The method and system can automatically complete the entire analysis process, improving detection efficiency and making it suitable for rapid screening and quality control of large batches of materials. By calculating distortion parameters, it can identify diffuse surface defects such as orange peel texture, solving the problem that traditional methods struggle to identify.

[0012] Therefore, it is evident that the present invention has outstanding substantive features and significant progress compared with the prior art, and the beneficial effects of its implementation are also obvious. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present 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 embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0014] Figure 1 This is a flowchart of a method for detecting the tensile strain mark limit; Figure 2 This is a structural diagram of a method for detecting the limit of tensile strain marks. Figure 3 This is a flowchart illustrating the logical judgment of a method for detecting the limit of tensile strain marks. Figure 4 This is a block diagram illustrating the principle of a system for detecting the limit of tensile strain marks.

[0015] The above figures include the following reference numerals: 1-Universal testing machine; 2-Standard tensile specimen; 3-Digital stripe projector; 4-High-speed industrial camera; 5-Data processing module; 6-Synchronization controller; 7-Test module; 8-Illumination projection module; 9-Image acquisition module. Detailed Implementation

[0016] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. The following embodiments are explanations of the present invention, but the present invention is not limited to the following implementation methods.

[0017] Example 1: like Figure 1 As shown, this embodiment provides a method for detecting the tensile strain mark limit, which includes the following steps: Step S1: The test preparation step involves applying a tensile load to the metal sheet specimen during the material test, and simultaneously generating observation data on the surface changes of the specimen through structured light projection and image acquisition. Step S2: The phase processing step involves performing wrapping phase processing on at least two consecutive frames of the acquired image sequence to obtain a phase distribution map that reflects minute geometric changes on the surface. Step S3: The distortion quantification step involves calculating the difference between two consecutive phase images and extracting distortion parameters from the difference results to quantify surface instability characteristics. Step S4: The limit determination step, based on the comparison between the distortion parameters and the preset threshold, determines the tensile strain mark initiation event, and determines the critical strain limit corresponding to the event from the synchronous mechanical data.

[0018] Example 2: like Figure 1 As shown, this embodiment provides a method for detecting the tensile strain mark limit, which includes the following steps: Step S1: The test preparation step involves applying a tensile load to the metal sheet specimen during the material test, and simultaneously generating observation data on the surface changes of the specimen through structured light projection and image acquisition. Step S2: The phase processing step involves performing wrapping phase processing on at least two consecutive frames of the acquired image sequence to obtain a phase distribution map that reflects minute geometric changes on the surface. Step S3: The distortion quantification step involves calculating the difference between two consecutive phase images and extracting distortion parameters from the difference results to quantify surface instability characteristics. Step S4: The limit determination step, based on the comparison between the distortion parameters and the preset threshold, determines the tensile strain mark initiation event, and determines the critical strain limit corresponding to the event from the synchronous mechanical data.

[0019] In step S1: During the material testing process, the thin steel plate to be tested is processed into a standard tensile specimen 2 and installed in the fixture of a universal testing machine. A tensile load is applied to the specimen. The universal testing machine 1 can be used to apply a constant-rate unidirectional tensile load to the specimen, or a planar biaxial tensile testing machine can be used to apply a biaxial tensile load to the cross-shaped specimen, thereby obtaining the strain response under different stress paths. Simultaneously, the synchronous controller 6 commands the digital stripe projector 3 to project a stable structured light pattern onto the specimen surface. This pattern can be parallel stripes distributed along the width of the specimen, or a cross-shaped grid pattern. The advantage of using a grid pattern is that it can simultaneously capture deformation information in two orthogonal directions (X and Y), providing more comprehensive data for analyzing complex, non-uniform deformation fields, resulting in more stable measurement results.

[0020] In terms of image acquisition, a high-speed industrial camera 4 is used to continuously acquire image sequences containing structured light patterns on the sample surface at a high frame rate, forming observation data reflecting the entire deformation process of the sample. The entire acquisition process is coordinated by a synchronous controller 6 to ensure a one-to-one correspondence between the applied mechanical signal and the image sequence on the time axis, thereby providing reliable synchronous data for subsequent phase calculation and differential analysis.

[0021] It should be noted that this invention uses digital projectors such as DLP to project structured light patterns, which is a geometric imaging process using incoherent light. This is fundamentally different from techniques that use coherent light sources such as lasers to generate interference fringes. Therefore, even when projecting complex grid-like patterns, no harmful optical interference or diffraction effects will occur to interfere with the measurement. The inherent diffraction effect of the method will only cause slight blurring at the edges of the projected fringes, and this effect has no impact on the measurement algorithm.

[0022] Step S1 enables the simultaneous recording of the tensile state and surface morphology changes of the sample, providing a reliable data basis for subsequent phase calculation and differential analysis, and achieving objectivity and quantifiability of the detection.

[0023] Example 3: like Figure 1 As shown, this embodiment provides a method for detecting the tensile strain mark limit, which includes the following steps: Step S1: The test preparation step involves applying a tensile load to the metal sheet specimen during the material test, and simultaneously generating observation data on the surface changes of the specimen through structured light projection and image acquisition. Step S2: The phase processing step involves performing wrapping phase processing on at least two consecutive frames of the acquired image sequence to obtain a phase distribution map that reflects minute geometric changes on the surface. Step S3: The distortion quantification step involves calculating the difference between two consecutive phase images and extracting distortion parameters from the difference results to quantify surface instability characteristics. Step S4: The limit determination step, based on the comparison between the distortion parameters and the preset threshold, determines the tensile strain mark initiation event, and determines the critical strain limit corresponding to the event from the synchronous mechanical data.

[0024] In step S1: During the material testing process, the thin steel plate to be tested is processed into a standard tensile specimen 2 and installed in the fixture of a universal testing machine. A tensile load is applied to the specimen. The universal testing machine 1 can be used to apply a constant-rate unidirectional tensile load to the specimen, or a planar biaxial tensile testing machine can be used to apply a biaxial tensile load to the cross-shaped specimen, thereby obtaining the strain response under different stress paths. Simultaneously, the synchronous controller 6 commands the digital stripe projector 3 to project a stable structured light pattern onto the specimen surface. This pattern can be parallel stripes distributed along the width of the specimen, or a cross-shaped grid pattern. The advantage of using a grid pattern is that it can simultaneously capture deformation information in two orthogonal directions (X and Y), providing more comprehensive data for analyzing complex, non-uniform deformation fields, resulting in more stable measurement results.

[0025] In terms of image acquisition, a high-speed industrial camera 4 is used to continuously acquire image sequences containing structured light patterns on the sample surface at a high frame rate, forming observation data reflecting the entire deformation process of the sample. The entire acquisition process is coordinated by a synchronous controller 6 to ensure a one-to-one correspondence between the applied mechanical signal and the image sequence on the time axis, thereby providing reliable synchronous data for subsequent phase calculation and differential analysis.

[0026] It should be noted that this invention uses digital projectors such as DLP to project structured light patterns, which is a geometric imaging process using incoherent light. This is fundamentally different from techniques that use coherent light sources such as lasers to generate interference fringes. Therefore, even when projecting complex grid-like patterns, no harmful optical interference or diffraction effects will occur to interfere with the measurement. The inherent diffraction effect of the method will only cause slight blurring at the edges of the projected fringes, and this effect has no impact on the measurement algorithm.

[0027] Step S1 enables the simultaneous recording of the tensile state and surface morphology changes of the sample, providing a reliable data basis for subsequent phase calculation and differential analysis, and achieving objectivity and quantifiability of the detection.

[0028] In step S2: For at least two consecutive frames in the acquired image sequence, the corresponding wrap-around phase distribution map is calculated using Fourier Transform Profilometry (FTP). This Fourier Transform Profilometry includes performing a two-dimensional Fourier transform on the image, extracting the fundamental frequency component in the spectral domain, filtering the fundamental frequency component, and performing an inverse Fourier transform on the filtered spectrum.

[0029] When the projected structured light pattern is a grid, its two-dimensional Fourier spectrum contains fundamental frequency components in both the horizontal and vertical axes. The algorithm can filter and solve these fundamental frequency components in these two directions separately, thereby obtaining mutually orthogonal X-axis and Y-axis phase maps. The X-axis phase map reflects surface deformation in the X direction, and the Y-axis phase map reflects surface deformation in the Y direction. In this way, phase changes in two orthogonal directions can be captured simultaneously, enabling a comprehensive characterization of complex deformation fields such as local inhomogeneities and orange peel texture.

[0030] Step S2 can convert micron-level surface morphology changes into analyzable phase information to achieve high-sensitivity detection, ensuring accurate capture of abrupt changes in tensile strain mark initiation, while providing more comprehensive surface morphology information.

[0031] Example 4: like Figure 1 As shown, this embodiment provides a method for detecting the tensile strain mark limit, which includes the following steps: Step S1: The test preparation step involves applying a tensile load to the metal sheet specimen during the material test, and simultaneously generating observation data on the surface changes of the specimen through structured light projection and image acquisition. Step S2: The phase processing step involves performing wrapping phase processing on at least two consecutive frames of the acquired image sequence to obtain a phase distribution map that reflects minute geometric changes on the surface. Step S3: The distortion quantification step involves calculating the difference between two consecutive phase images and extracting distortion parameters from the difference results to quantify surface instability characteristics. Step S4: The limit determination step, based on the comparison between the distortion parameters and the preset threshold, determines the tensile strain mark initiation event, and determines the critical strain limit corresponding to the event from the synchronous mechanical data.

[0032] In step S1: During the material testing process, the thin steel plate to be tested is processed into a standard tensile specimen 2 and installed in the fixture of a universal testing machine. A tensile load is applied to the specimen. The universal testing machine 1 can be used to apply a constant-rate unidirectional tensile load to the specimen, or a planar biaxial tensile testing machine can be used to apply a biaxial tensile load to the cross-shaped specimen, thereby obtaining the strain response under different stress paths. Simultaneously, the synchronous controller 6 commands the digital stripe projector 3 to project a stable structured light pattern onto the specimen surface. This pattern can be parallel stripes distributed along the width of the specimen, or a cross-shaped grid pattern. The advantage of using a grid pattern is that it can simultaneously capture deformation information in two orthogonal directions (X and Y), providing more comprehensive data for analyzing complex, non-uniform deformation fields, resulting in more stable measurement results.

[0033] In terms of image acquisition, a high-speed industrial camera 4 is used to continuously acquire image sequences containing structured light patterns on the sample surface at a high frame rate, forming observation data reflecting the entire deformation process of the sample. The entire acquisition process is coordinated by a synchronous controller 6 to ensure a one-to-one correspondence between the applied mechanical signal and the image sequence on the time axis, thereby providing reliable synchronous data for subsequent phase calculation and differential analysis.

[0034] It should be noted that this invention uses digital projectors such as DLP to project structured light patterns, which is a geometric imaging process using incoherent light. This is fundamentally different from techniques that use coherent light sources such as lasers to generate interference fringes. Therefore, even when projecting complex grid-like patterns, no harmful optical interference or diffraction effects will occur to interfere with the measurement. The inherent diffraction effect of the method will only cause slight blurring at the edges of the projected fringes, and this effect has no impact on the measurement algorithm.

[0035] Step S1 enables the simultaneous recording of the tensile state and surface morphology changes of the sample, providing a reliable data basis for subsequent phase calculation and differential analysis, and achieving objectivity and quantifiability of the detection.

[0036] In step S2: For at least two consecutive frames in the acquired image sequence, the corresponding wrap-around phase distribution map is calculated using Fourier Transform Profilometry (FTP). This Fourier Transform Profilometry includes performing a two-dimensional Fourier transform on the image, extracting the fundamental frequency component in the spectral domain, filtering the fundamental frequency component, and performing an inverse Fourier transform on the filtered spectrum.

[0037] When the projected structured light pattern is a grid, its two-dimensional Fourier spectrum contains fundamental frequency components in both the horizontal and vertical axes. The algorithm can filter and solve these fundamental frequency components in these two directions separately, thereby obtaining mutually orthogonal X-axis and Y-axis phase maps. The X-axis phase map reflects surface deformation in the X direction, and the Y-axis phase map reflects surface deformation in the Y direction. In this way, phase changes in two orthogonal directions can be captured simultaneously, enabling a comprehensive characterization of complex deformation fields such as local inhomogeneities and orange peel texture.

[0038] Step S2 can convert micron-level surface morphology changes into analyzable phase information to achieve high-sensitivity detection, ensuring accurate capture of abrupt changes in tensile strain mark initiation, while providing more comprehensive surface morphology information.

[0039] In step S3, point-by-point differencing is performed on two consecutive phase images to obtain a differential phase image Δφ(x, y, t). The differential phase image can effectively highlight the instantaneous abrupt changes caused by surface instability. To detect various surface instability morphologies, a universally applicable distortion parameter is used to measure the overall non-uniformity of the differential phase image. The distortion parameter can be the sum of the squares of the moduli of all points in the spatial gradient field of the differential phase image, i.e., the gradient energy integral, or it can be the standard deviation of all pixel values. The gradient energy integral S_energy(t) is used as the distortion parameter. When a tensile strain mark is initiated, the value of S_energy(t) will undergo a sharp, pulse-like jump, thus forming a significant abrupt change characteristic signal.

[0040] The distortion parameters characterizing the degree of inhomogeneity are calculated based on this difference map. The distortion parameters can be the sum of squares of the moduli of all points in the spatial gradient field of the difference phase map, i.e., the gradient energy integral, or the standard deviation of all pixel values, used to quantify the local instability characteristics of the sample surface. Data processing module 5 can calculate the distortion parameters in real time, capture local abrupt change times, and simultaneously lock the mechanical signal to establish the correspondence between surface morphology and stress-strain.

[0041] By calculating distortion parameters, local minute mutations are amplified into significant signals, enhancing the ability to detect tensile strain mark initiation. At the same time, it can identify complex surface morphology defects such as orange peel texture, improving the stability and robustness of measurement results.

[0042] Example 5: like Figure 1 As shown, this embodiment provides a method for detecting the tensile strain mark limit, which includes the following steps: Step S1: The test preparation step involves applying a tensile load to the metal sheet specimen during the material test, and simultaneously generating observation data on the surface changes of the specimen through structured light projection and image acquisition. Step S2: The phase processing step involves performing wrapping phase processing on at least two consecutive frames of the acquired image sequence to obtain a phase distribution map that reflects minute geometric changes on the surface. Step S3: The distortion quantification step involves calculating the difference between two consecutive phase images and extracting distortion parameters from the difference results to quantify surface instability characteristics. Step S4: The limit determination step, based on the comparison between the distortion parameters and the preset threshold, determines the tensile strain mark initiation event, and determines the critical strain limit corresponding to the event from the synchronous mechanical data.

[0043] In step S1: During the material testing process, the thin steel plate to be tested is processed into a standard tensile specimen 2 and installed in the fixture of a universal testing machine. A tensile load is applied to the specimen. The universal testing machine 1 can be used to apply a constant-rate unidirectional tensile load to the specimen, or a planar biaxial tensile testing machine can be used to apply a biaxial tensile load to the cross-shaped specimen, thereby obtaining the strain response under different stress paths. Simultaneously, the synchronous controller 6 commands the digital stripe projector 3 to project a stable structured light pattern onto the specimen surface. This pattern can be parallel stripes distributed along the width of the specimen, or a cross-shaped grid pattern. The advantage of using a grid pattern is that it can simultaneously capture deformation information in two orthogonal directions (X and Y), providing more comprehensive data for analyzing complex, non-uniform deformation fields, resulting in more stable measurement results.

[0044] In terms of image acquisition, a high-speed industrial camera 4 is used to continuously acquire image sequences containing structured light patterns on the sample surface at a high frame rate, forming observation data reflecting the entire deformation process of the sample. The entire acquisition process is coordinated by a synchronous controller 6 to ensure a one-to-one correspondence between the applied mechanical signal and the image sequence on the time axis, thereby providing reliable synchronous data for subsequent phase calculation and differential analysis.

[0045] It should be noted that this invention uses digital projectors such as DLP to project structured light patterns, which is a geometric imaging process using incoherent light. This is fundamentally different from techniques that use coherent light sources such as lasers to generate interference fringes. Therefore, even when projecting complex grid-like patterns, no harmful optical interference or diffraction effects will occur to interfere with the measurement. The inherent diffraction effect of the method will only cause slight blurring at the edges of the projected fringes, and this effect has no impact on the measurement algorithm.

[0046] Step S1 enables the simultaneous recording of the tensile state and surface morphology changes of the sample, providing a reliable data basis for subsequent phase calculation and differential analysis, and achieving objectivity and quantifiability of the detection.

[0047] In step S2: For at least two consecutive frames in the acquired image sequence, the corresponding wrap-around phase distribution map is calculated using Fourier Transform Profilometry (FTP). This Fourier Transform Profilometry includes performing a two-dimensional Fourier transform on the image, extracting the fundamental frequency component in the spectral domain, filtering the fundamental frequency component, and performing an inverse Fourier transform on the filtered spectrum.

[0048] When the projected structured light pattern is a grid, its two-dimensional Fourier spectrum contains fundamental frequency components in both the horizontal and vertical axes. The algorithm can filter and solve these fundamental frequency components in these two directions separately, thereby obtaining mutually orthogonal X-axis and Y-axis phase maps. The X-axis phase map reflects surface deformation in the X direction, and the Y-axis phase map reflects surface deformation in the Y direction. In this way, phase changes in two orthogonal directions can be captured simultaneously, enabling a comprehensive characterization of complex deformation fields such as local inhomogeneities and orange peel texture.

[0049] Step S2 can convert micron-level surface morphology changes into analyzable phase information to achieve high-sensitivity detection, ensuring accurate capture of abrupt changes in tensile strain mark initiation, while providing more comprehensive surface morphology information.

[0050] In step S3, point-by-point differencing is performed on two consecutive phase images to obtain a differential phase image Δφ(x, y, t). The differential phase image can effectively highlight the instantaneous abrupt changes caused by surface instability. To detect various surface instability morphologies, a universally applicable distortion parameter is used to measure the overall non-uniformity of the differential phase image. The distortion parameter can be the sum of the squares of the moduli of all points in the spatial gradient field of the differential phase image, i.e., the gradient energy integral, or it can be the standard deviation of all pixel values. The gradient energy integral S_energy(t) is used as the distortion parameter. When a tensile strain mark is initiated, the value of S_energy(t) will undergo a sharp, pulse-like jump, thus forming a significant abrupt change characteristic signal.

[0051] The distortion parameters characterizing the degree of inhomogeneity are calculated based on this difference map. The distortion parameters can be the sum of squares of the moduli of all points in the spatial gradient field of the difference phase map, i.e., the gradient energy integral, or the standard deviation of all pixel values, used to quantify the local instability characteristics of the sample surface. Data processing module 5 can calculate the distortion parameters in real time, capture local abrupt change times, and simultaneously lock the mechanical signal to establish the correspondence between surface morphology and stress-strain.

[0052] By calculating distortion parameters, local minute mutations are amplified into significant signals, enhancing the ability to detect tensile strain mark initiation. At the same time, it can identify complex surface morphology defects such as orange peel texture, improving the stability and robustness of measurement results.

[0053] In step S4: the obtained distortion parameter is compared with a preset threshold. When the distortion parameter exceeds the threshold for the first time, a tensile strain mark initiation event is determined to have occurred. When S_energy(t) first exceeds a preset threshold, the moment t_crit is immediately marked as the critical moment. Based on the synchronization information, the strain value ε_crit corresponding to the critical moment t_crit is found from the recorded mechanical data. This ε_crit is the objectively quantitative critical strain limit of the tensile strain mark measured by the method of this invention. The data processing module 5 can combine the real-time communication between the testing machine and the image acquisition unit to complete the distortion abrupt change detection and mechanical signal locking, and can output the critical moment and strain value.

[0054] Step S4 enables precise location of the moment tensile strain mark initiation and objective, quantitative determination of the critical strain limit, providing a reliable technical basis for material performance evaluation and quality control.

[0055] like Figure 3 As shown, the detection method provided in this embodiment includes the following steps: First, Fourier transform profilometry is used to process the image data of the current frame I(t) and the previous frame I(t-1) to obtain the corresponding wrapping phase distribution map φ(x, y, t). Then, the point-by-point difference between the phase distributions of adjacent frames is calculated to obtain the differential phase map Δφ(t) = φ(t) - φ(t-1). Subsequently, based on this difference result, the distortion parameter S(t), which characterizes the surface inhomogeneity, is calculated. The distortion parameter is preferably the gradient energy integral of the differential phase map. Next, the distortion parameter is compared with a preset threshold S_th. When S(t) exceeds the threshold for the first time, it is determined that a tensile strain mark initiation event has occurred, and this moment is recorded as the critical moment t_crit. Finally, the strain value ε_crit corresponding to t_crit is extracted from the synchronously recorded mechanical data as the critical strain limit of the tensile strain mark. When the distortion parameter does not exceed the threshold, the system continues to acquire the next frame image I(t+1), let t=t+1; and repeats the process of phase solution, difference calculation and distortion parameter extraction until the distortion parameter exceeds the threshold for the first time.

[0056] Therefore, it can be seen that the process fully embodies the processing logic of steps S2 to S4, and can achieve accurate positioning of the moment of tensile strain mark initiation and objective and quantitative determination of the critical strain limit.

[0057] Example 6: like Figure 4 As shown, this embodiment provides a system for detecting the tensile strain mark limit, comprising: Test module 7 is used to apply tensile loads to metal sheet specimens. It can use a universal testing machine 1 to apply a uniaxial tensile load to a standard tensile specimen 2 at a constant rate; or it can use a planar biaxial tensile testing machine to apply a biaxial tensile load to a cruciform specimen, thereby obtaining the strain response under different stress paths. This module can provide controllable and stable mechanical loading conditions, enabling precise tensile testing of specimens under different stress states, and providing a reliable synchronous mechanical basis for subsequent surface morphology change detection.

[0058] The illumination projection module 8 projects a preset structured light pattern onto the sample surface. This pattern can be parallel stripes distributed along the width of the sample or a cross-shaped grid pattern. The digital stripe projector 3 uses a monochromatic LED light source, and a bandpass filter matching its wavelength is installed in front of the image acquisition unit to suppress ambient light interference and improve the signal-to-noise ratio. This module uses incoherent optical geometric projection methods such as digital light processing (DLP) to avoid stripe ghosting and diffraction effects that may be introduced by laser interferometry imaging, ensuring pattern stability and imaging clarity. By optically encoding the sample surface morphology, this module can convert micron-level geometric abrupt changes into observable stripe distortion signals, providing highly sensitive optical input for subsequent phase extraction and differential analysis, ensuring comprehensive and stable acquisition of surface morphology information.

[0059] Image acquisition module 9 is used to continuously acquire image sequences of the specimen surface, recording minute morphological changes during tensile testing. A high-speed industrial camera 4 is employed, and its acquisition timing is coordinated by a synchronization controller 6, ensuring a strict correspondence between image data and the mechanical loading process. This achieves time synchronization between mechanical signals and surface morphology information, ensuring that subsequent phase calculations and distortion analysis accurately match the loading state. This module enables data acquisition synchronized with the tensile load, ensuring temporal consistency between surface morphology information and mechanical data, providing complete and continuous observation data for differential phase calculations and distortion parameter extraction.

[0060] Data processing module 5 is used to process the acquired image sequence in real time. First, Fourier transform profilometry (FTP) is used to perform a two-dimensional Fourier transform on a single frame image, filtering the fundamental frequency component in the spectral domain and performing an inverse Fourier transform to obtain the wrapping phase distribution map. When the illumination projection module 8 projects a grid-like structured light pattern, the system can simultaneously obtain phase maps in the X and Y orthogonal directions, realizing a two-way characterization of complex deformation fields. Subsequently, the phase distribution maps of two consecutive frames are differentially analyzed point by point to obtain a differential phase map, and distortion parameters characterizing the surface inhomogeneity are calculated. Data processing module 5 can calculate distortion parameters in real time, capture local abrupt change times, and synchronously lock mechanical signals to establish the correspondence between surface morphology and stress-strain. For example, the sum of squares of the spatial gradient field of the differential phase map is the gradient energy integral or the standard deviation of pixel values. When a tensile strain mark initiates, the gradient energy integral will undergo a sharp, pulse-like jump, and the system determines that the initiation event has occurred based on this. The data processing module 5 can synchronously compare the critical moment with the mechanical data recorded by the testing machine, lock the corresponding mechanical signal, and extract the strain value ε_crit corresponding to that moment as the critical strain limit. The data processing module 5 can combine the real-time communication between the testing machine and the image acquisition unit to complete the distortion abrupt change detection and mechanical signal locking, and can output the critical moment and strain value.

[0061] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The methods disclosed in the embodiments are described simply because they correspond to the systems disclosed in the embodiments; relevant details can be found in the method section.

[0062] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0063] In the embodiments provided by this invention, it should be understood that the disclosed systems, methods, and approaches can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0064] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0065] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit.

[0066] Similarly, in the various embodiments of the present invention, each processing unit can be integrated into a functional module, or each processing unit can exist physically, or two or more processing units can be integrated into a functional module.

[0067] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0068] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0069] The above-disclosed embodiments are merely preferred embodiments of the present invention, but the present invention is not limited thereto. Any non-creative variations that can be conceived by those skilled in the art, as well as any improvements and modifications made without departing from the principles of the present invention, should fall within the protection scope of the present invention.

Claims

1. A method for detecting the tensile strain mark limit, characterized in that, Includes the following steps: Step S1: The test preparation step involves applying a tensile load to the metal sheet specimen during the material test, and simultaneously generating observation data on the surface changes of the specimen through structured light projection and image acquisition. Step S2: The phase processing step involves performing wrapping phase processing on at least two consecutive frames of the acquired image sequence to obtain a phase distribution map that reflects minute geometric changes on the surface. Step S3: The distortion quantification step involves calculating the difference between two consecutive phase images and extracting distortion parameters from the difference results to quantify surface instability characteristics. Step S4: The limit determination step, based on the comparison between the distortion parameters and the preset threshold, determines the tensile strain mark initiation event, and determines the critical strain limit corresponding to the event from the synchronous mechanical data.

2. The method for detecting the tensile strain mark limit according to claim 1, characterized in that, In step S1: During the material test, the thin steel plate to be tested is processed into a standard tensile specimen (2) and installed in the fixture of the universal testing machine; a tensile load is applied to the specimen, and the universal testing machine (1) is used to unidirectionally tensile the specimen at a constant rate or a planar bidirectional tensile testing machine is used to apply a bidirectional tensile load to the cross-shaped specimen. At the same time, the digital stripe projector (3) is commanded by the synchronous controller (6) to project a set of stable structured light patterns onto the specimen surface. The pattern can be parallel stripes distributed along the width direction of the specimen or a cross-shaped grid pattern; the high-speed industrial camera (4) is used to continuously acquire image sequences containing structured light patterns on the specimen surface at a high frame rate to form observation data reflecting the entire deformation process of the specimen. The entire acquisition process is coordinated by the synchronous controller (6).

3. A method for detecting the tensile strain mark limit according to claim 1 or 2, characterized in that, Structured light patterns are projected using a DLP digital projector.

4. The method for detecting the tensile strain mark limit according to claim 3, characterized in that, In step S2: For at least two consecutive frames of images in the acquired image sequence, the corresponding wrapping phase distribution map is calculated using Fourier transform profilometry; the Fourier transform profilometry includes performing a two-dimensional Fourier transform on the image, extracting the fundamental frequency component in the spectral domain, filtering the fundamental frequency component, and performing an inverse Fourier transform on the filtered spectrum.

5. The method for detecting the tensile strain mark limit according to claim 4, characterized in that, When the projected structured light pattern is grid-like, its two-dimensional Fourier spectrum has fundamental frequency components in both the horizontal and vertical axes. By filtering and solving the fundamental frequency components in these two directions, mutually orthogonal X-axis phase diagrams and Y-axis phase diagrams are obtained. The X-axis phase diagram reflects the surface deformation in the X direction, and the Y-axis phase diagram reflects the surface deformation in the Y direction.

6. The method for detecting the tensile strain mark limit according to claim 5, characterized in that, In step S3: point-by-point difference is performed on two consecutive phase maps to obtain a differential phase map. A universal distortion parameter is used to measure the overall non-uniformity of the differential phase map. The distortion parameter can be the sum of squares of the moduli of all points in the spatial gradient field of the differential phase map, i.e., the gradient energy integral, or the standard deviation of all pixel values. The gradient energy integral S_energy(t) is used as the distortion parameter. When a tensile strain mark is generated, the value of S_energy(t) will change sharply and impulsively, thus forming a significant abrupt change characteristic signal.

7. The method for detecting the tensile strain mark limit according to claim 6, characterized in that, In step S4, the obtained distortion parameter is compared with a preset threshold. When the distortion parameter exceeds the threshold for the first time, it is determined that a tensile strain mark initiation event has occurred. When S_energy(t) first exceeds a preset threshold, the moment t_crit is immediately marked as the critical moment. Based on the synchronization information, the strain value ε_crit corresponding to the critical moment t_crit is found from the recorded mechanical data. ε_crit is the objectively quantitative critical strain limit of the tensile strain mark.

8. The method for detecting the tensile strain mark limit according to claim 7, characterized in that, For the image data of the current frame I(t) and the previous frame I(t-1), Fourier transform contouring is used to process the data and obtain the corresponding wrapper phase distribution map φ(x, y, t). Then, the point-by-point difference between the phase distributions of adjacent frames is calculated to obtain the differential phase map Δφ(t) = φ(t) - φ(t-1). Subsequently, based on this difference result, the distortion parameter S(t) characterizing the surface non-uniformity is calculated. The distortion parameter is preferably the gradient energy integral of the differential phase map. Then, the distortion parameter is compared with a preset threshold S_ The system compares t and th. When S(t) exceeds the threshold for the first time, it determines that a tensile strain mark initiation event has occurred and records this moment as the critical moment t_crit. Finally, it extracts the strain value ε_crit corresponding to t_crit from the synchronously recorded mechanical data as the critical strain limit of the tensile strain mark. When the distortion parameter does not exceed the threshold, the system continues to acquire the next frame image I(t+1), sets t=t+1, and repeats the process of phase solution, difference calculation, and distortion parameter extraction until the distortion parameter exceeds the threshold for the first time.

9. A system for detecting the tensile strain mark limit, characterized in that, include: Experimental module (7), illumination projection module (8), image acquisition module (9), data processing module (5); The test module (7) is used to apply tensile load to the metal sheet specimen to form a tensile strain environment; The illumination projection module (8) is used to project a stable structured light pattern onto the sample surface to encode surface morphology information; The image acquisition module (9) is used to continuously acquire image sequences of the sample surface and record minute changes in the surface during the stretching process; The data processing module (5) is used to perform wrapping phase calculation, differential phase calculation, distortion parameter extraction and tensile strain mark initiation determination on the acquired image sequence, and to determine the critical strain limit.

10. A system for detecting the tensile strain mark limit according to claim 9, characterized in that, The test module (7) uses a universal testing machine (1) to apply a uniaxial tensile load to a standard tensile specimen (2) at a constant rate or uses a planar biaxial tensile testing machine to apply a biaxial tensile load to a cross-shaped specimen to obtain strain responses under different stress paths. The illumination projection module (8) is used to project a preset structured light pattern onto the sample surface. The pattern is a parallel stripe or a cross-shaped grid pattern distributed along the width of the sample. The projection light source of the digital stripe projector (3) is a monochrome LED light source, and a bandpass filter matching its wavelength is installed in front of the image acquisition unit. The non-coherent light geometric projection method such as digital light processing (DLP) is used to optically encode the surface morphology of the sample and convert the micron-level geometric mutation into an observable stripe distortion signal. The image acquisition module (9) uses a high-speed industrial camera (4) and its acquisition timing is coordinated by a synchronous controller (6) so that the image data strictly corresponds to the mechanical loading process; The data processing module (5) is used to process the acquired image sequence in real time. First, it uses Fourier transform contouring to perform two-dimensional Fourier transform on a single frame image, filters the fundamental frequency component in the spectral domain, and performs inverse Fourier transform to obtain the wrapping phase distribution map. When the illumination projection module (8) projects a grid-like structured light pattern, the system can simultaneously obtain phase maps in two orthogonal directions, X and Y. Subsequently, the phase distribution maps of two consecutive frames are differentially analyzed point by point to obtain differential phase maps, and the distortion parameters characterizing the surface non-uniformity are calculated. Local abrupt change times are captured, and mechanical signals are locked synchronously to establish the correspondence between surface morphology and stress-strain. When tensile strain marks are generated, the gradient energy integral will undergo a sharp, pulse-like jump. The system determines that the generation event has occurred based on this. The data processing module can synchronously compare the critical moment with the mechanical data recorded by the testing machine, lock the corresponding mechanical signal, and extract the strain value ε_crit corresponding to that moment as the critical strain limit.

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