CN111386449B - Stress analysis system for curved surface material inspection - Google Patents
Stress analysis system for curved surface material inspection Download PDFInfo
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- CN111386449B CN111386449B CN201980005547.1A CN201980005547A CN111386449B CN 111386449 B CN111386449 B CN 111386449B CN 201980005547 A CN201980005547 A CN 201980005547A CN 111386449 B CN111386449 B CN 111386449B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L1/00—Measuring force or stress, in general
- G01L1/24—Measuring force or stress, in general by measuring variations of optical properties of material when it is stressed, e.g. by photoelastic stress analysis using infrared, visible light, ultraviolet
Abstract
A stress analysis system for curved surface material inspection comprises: a light source (10) for emitting an illumination beam; the polarizer (20), the first wavefront modulation lens (30), the curved surface detection material, the second wavefront modulation lens (40), the analyzer (50) and the image sensor (60) are sequentially arranged on the light path of the illumination light beam; the thickness distribution of the first wavefront modulation lens (30) and the distance from the curved test material satisfy the condition: the wavefront of the illumination beam reaching the incident surface of the curved surface material to be detected is consistent with the incident surface of the curved surface material to be detected; the image sensor (60) is used for acquiring interference imaging of the illumination light beam; the device also comprises a processor (70) which is used for acquiring the interference imaging collected by the image sensor (60) and detecting the stress distribution of the curved surface material to be tested according to the interference imaging. The stress analysis system of the curved surface material checking is more accurate.
Description
Technical Field
The invention relates to the technical field of industrial detection, in particular to a stress analysis system for curved surface material detection.
Background
With the rapid development of the mobile internet industry, manufacturers and products of the intelligent mobile terminals are in a large number, and the materials of the appearance shell of the intelligent mobile terminal are also continuously improved. At present, mainstream mobile phone manufacturers have provided terminal products based on 3D curved glass, and the terminal products are popular among many mobile phone manufacturers and consumers due to the advantages of being transparent, clean, anti-fingerprint, anti-glare, easy to match with a flexible OLED screen, and more in line with human engineering.
However, the processing process of 3D curved glass requires a "hot bending" process of the glass. The glass produced by the process has residual stress in different degrees, and the usability of the glass is influenced. In addition, due to poor quality or non-uniform composition of the glass (for example, defects such as cracks, stones, bubbles, etc. exist in the glass), the thermal expansion coefficients of the respective components are different, and when the glass is cooled to room temperature, stress jump occurs, and the jump point becomes a stress singular point, which may cause explosion of the glass in a serious case. Therefore, in the production process of the 3D curved glass, the glass stress needs to be measured, so as to ensure the yield and the safety performance of the 3D curved glass.
However, the current glass stress detection method is mostly directed to plane glass. When the method for detecting the stress distribution of the planar glass is adopted to detect the stress distribution of the 3D curved glass, the accuracy is not high. For example, when the method for detecting the stress of the coherent light plane glass is used for detecting the 3D curved glass, because the optical elements such as the lens and the like cannot be attached to the optical surface of the 3D curved glass, the illumination light beam is difficult to propagate on the portion which cannot be attached as required, and thus the stress distribution of the 3D curved glass detected by interference imaging is inaccurate.
Disclosure of Invention
Based on this, in order to solve the technical problem that the stress distribution of the 3D curved glass detected through interference imaging in the prior art is inaccurate, a curved surface material detection stress analysis system is specially provided.
A stress analysis system for curved surface material inspection comprises:
a light source for emitting an illumination beam;
the polarizer, the first wavefront modulation lens, the curved surface detection material, the second wavefront modulation lens, the analyzer and the image sensor are sequentially arranged on the light path of the illumination light beam;
the polarizer is used for polarizing the illumination light beam in a preset target polarization direction;
the thickness distribution of the first wavefront modulation lens and the distance from the curved surface material to be inspected satisfy the condition: the wavefront of the illumination beam reaching the incident surface of the curved inspection material is consistent with the incident surface of the curved inspection material;
the thickness distribution of the second wavefront modulation lens and the distance from the curved surface material to be inspected satisfy the condition: the second wavefront modulation lens and the first wavefront modulation lens form a conjugate system;
the analyzer is used for combining components of the illumination light beams with different polarization directions to generate interference;
the image sensor is used for acquiring interference imaging of the illumination light beam;
the device also comprises a processor, which is used for acquiring the interference image acquired by the image sensor and detecting the stress distribution of the curved surface material to be detected according to the interference image.
In one embodiment, the light source is a monochromatic coherent light source and the illumination beam is a monochromatic coherent beam.
In one embodiment, the processor is configured to detect an interference position and an interference fringe interval of the interference imaging, determine a stress point of the curved surface material to be inspected according to the interference position, and determine a stress distribution of the stress point according to the interference fringe interval.
In one embodiment, the thickness distribution of the first wavefront modulation lens and the distance from the curved material to be inspected satisfy the following conditions:
n is the refractive index of the first wavefront modulation lens, and two beams i and j of the illumination light beam enter the incident surface of the first wavefront modulation lens through the positions Ai and Aj, exit through the positions Bi and Bj on the exit surface of the first wavefront modulation lens, and enter through the positions Ci and Cj on the incident surface of the curved inspection material.
In one embodiment, the system further comprises:
a phase adjuster disposed in an optical path of the illumination beam, the phase adjuster being positioned between the light source and the polarizer for adjusting a phase of the illumination beam;
the image sensor is also used for acquiring interference imaging under a plurality of phases adjusted by the phase adjuster.
In one embodiment, the phase adjuster adjusts the phase difference between adjacent phases to be pi/2.
In one embodiment, the processor is further configured to acquire at least 4 interference images acquired by the image sensor, and phase differences of the illumination beams corresponding to the 4 interference images are pi/2, pi, 3 pi/2, respectively;
the processor is further configured to obtain light intensity information of the same position in the 4 interference images, calculate an interference fringe phase of the position according to the light intensity information, perform wrapping processing to obtain phase distribution of the interference fringe, and obtain stress distribution of the curved surface inspection material according to the phase distribution and the photoelastic coefficient of the curved surface inspection material.
In one embodiment, the processor is further configured to perform the operations according to:
calculating the phase of the corresponding illumination beam at the (x, y) position on the interference image
Said I1(x,y)、I2(x,y)、I3(x,y)、I4(x, y) are 4 interference imagesThe light intensities at the same (x, y) positions, respectively, a (x, y) being the background intensity and B (x, y) being the intensity of the illumination beam.
In one embodiment, the processor is further configured to obtain a defect identification model based on machine learning, where the defect identification model includes at least output categories of cracks, bubbles, stones, and defects, and the output categories have corresponding confidence degrees after being trained by machine learning of sample stress distributions of corresponding categories;
the processor is further used for inputting the stress distribution into the defect identification model, and determining the defect corresponding to the curved surface inspection material according to the obtained confidence of the output category.
The embodiment of the invention has the following beneficial effects:
after the stress analysis system of the curved surface material to be detected is adopted, the wavefront modulation lenses are added in the front and the back of the curved surface material to be detected in the light path passing through the curved surface material to be detected, and the wavefront modulation lenses enable the wavefront of the illumination light beam reaching the curved surface material to be matched with the outer surface of the curved surface material to be detected due to the fact that optical path differences of the light beams transmitted to the outer surface of the curved surface material to be detected when the illumination light beam for interference imaging detection stress distribution reaches the curved surface material to be detected, so that the formed interference imaging is only objective reflection of the stress distribution in the curved surface material to be detected, and cannot be simultaneously influenced by interference phenomena generated due to inconsistent wavefronts, and therefore the accuracy of stress analysis is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
in order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Wherein:
FIG. 1 is a schematic diagram of a stress analysis system for curved test material in one embodiment;
FIG. 2 is a schematic diagram of wavefront modulation in one embodiment;
FIG. 3 is a schematic diagram of a process for computing a phase map by phase shifting in one embodiment;
FIG. 4 is a flow diagram of a process for computing a stress profile from interferometric imaging in one embodiment;
FIG. 5 is a schematic diagram of defect identification for stress distribution based on machine learning in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to solve the technical problem of low accuracy in analyzing curved surface material to be tested such as 3D curved surface glass and the like by using a stress analysis system based on the interference principle in the conventional technology, the invention specifically provides a stress analysis system for curved surface material to be tested, which can be seen in fig. 1, wherein fig. 1 shows an optical device and a light path diagram, wherein the stress analysis system comprises:
a light source 10 for emitting an illumination beam. As the light source 10, a light emitting diode, a laser diode, or the like may be employed. In this embodiment, to improve accuracy, the light source 10 is a monochromatic coherent light source, and the emitted illumination beam is monochromatic coherent light. For example, a blue laser or a blue laser diode, etc.
As shown in fig. 1, the stress analysis system further includes a polarizer 20, a first wavefront modulation lens 30, a second wavefront modulation lens 40, an analyzer 50, and an image sensor 60, which are sequentially disposed on the optical path of the illumination beam. When the stress distribution of the curved surface material to be inspected is analyzed, the curved surface material to be inspected needs to be placed between the first wavefront modulation lens 30 and the second wavefront modulation lens 40, the outer curved surface of the curved surface material to be inspected faces the first wavefront modulation lens 30, the inner curved surface faces the second wavefront modulation lens 40, and the distance and the relative position between the curved surface material to be inspected and the first wavefront modulation lens 30 and the first wavefront modulation lens 40 need to meet certain conditions, specifically:
the polarizer 20 is used to polarize the illumination beam to a preset target polarization direction.
The thickness distribution of the first wavefront modulation lens 30 and the distance to the curved test material satisfy the condition: the wavefront of the illumination beam reaching the incident surface of the curved surface material to be detected is consistent with the incident surface of the curved surface material to be detected.
In the present embodiment, the design of the wavefront modulation lens 30 is a key of the optical system. In the embodiment, based on the huygens principle, the design is carried out simultaneously by combining light and wavefront, under the condition that the geometric shape of the surface of the curved surface inspection material is known, the lattice of the lens surface is calculated by utilizing the wavefront, and then the smooth and continuous lens surface shape is finally generated by fitting a spline curve.
The thickness distribution of the first wavefront modulation lens and the distance from the curved surface material to be inspected satisfy the following conditions:
n is the refractive index of the first wavefront modulation lens, and two beams i and j of the illumination light beam enter the incident surface of the first wavefront modulation lens through the positions Ai and Aj, exit through the positions Bi and Bj on the exit surface of the first wavefront modulation lens, and enter through the positions Ci and Cj on the incident surface of the curved inspection material.
Referring to FIG. 2, A1 and A2 are two points on the incident surface of the first wavefront modulating lens, the beams1 from a1 into the first wavefront modulating lens and B1 out of the first wavefront modulating lens, line segment
I.e. the thickness L1 of the first wavefront modulating lens at the a1 location. C1 is the position where the beam 1 is emitted from B1 and enters the curved inspection material.
I.e. the optical path for beam 1 incident from a1 through B1 to C1,
i.e., the optical path for beam 2 to enter from a2 through B2 to C2. Keeping the optical paths of the light beam 1 and the light beam 2 reaching different positions of the incident surface of the curved surface material to be detected consistent, thus ensuring that the wavefront of the illuminating light beam reaching the incident surface of the curved surface material to be detected is consistent with the incident surface of the curved surface material to be detected.
In one embodiment, the first wavefront modulation lens is a free-form surface mirror, and the outer surface of the material to be inspected is a process for customizing the surface of the free-form surface mirror. From wavefront A to wavefront C, the optical path length is determined to be NxL 1+ B1C 1. Since the wavefront C has already been determined (the incident surface of the curved test material), C2 is determined. The A2 on the wavefront a is also determined, and since the optical path length passed by the corresponding point in the process of the wavefront a evolving into the wavefront C is the same, the thickness L2 of the A2B2 can be calculated. By analogy, the lens thicknesses of the first wavefront modulation lens at different positions can be calculated and fitted, namely the shape of the curved surface of the first wavefront modulation lens corresponds to the incident surface of the curved surface material to be inspected, the shape can be adapted to the incident surface of any curved surface material to be inspected and is a free-form surface, and therefore the design of the free-form surface wavefront modulation lens is completed.
Accordingly, in this embodiment, the thickness distribution of the second wavefront modulation lens and the distance to the curved inspection material also satisfy the condition: the second wavefront modulating lens forms a conjugate system with the first wavefront modulating lens.
That is, the wavefront of the illumination beam exiting the exit face of the second wavefront modulation lens coincides with the exit face of the second wavefront modulation lens. For the same reason, the matched second wavefront modulation lens can also be customized by calculating the optical path length, and the process is not described in detail.
In the conventional technology, when the stress distribution of the plane glass is analyzed by an interference method, the principle is based on that the light rays at the same wavefront position generate interference due to phase change caused by the non-uniformity of the stress distribution, and the phase change is analyzed by interference fringes, so that the stress distribution can be analyzed. When the plane glass is analyzed, the illuminating light beam is parallel light, when the illuminating light beam vertically irradiates on the plane glass, the wave front is naturally attached to the surface of the plane glass, but if the curved surface material to be detected is directly irradiated without modulation, the attachment of the wave front and the curved surface cannot be ensured, so that the interference fringes are not only dependent on phase change caused by uneven stress distribution, but also influenced by the phase change generated by inconsistent wave front.
However, with the first wavefront adjustment lens 30 and the second wavefront modulation lens 40, the influence of phase change caused by wavefront inconsistency on the interference fringes is eliminated, so that the phase change detected by the interference fringes depends only on the stress distribution, and therefore, the stress distribution analysis can be performed more accurately.
In this embodiment, the analyzer 50 is used to combine the components of the illumination beam with different polarization directions to generate interference.
The image sensor 60 is used to acquire interferometric imaging of the illumination beam.
That is, the light emitted from the monochromatic light source passes through the polarizer and then becomes linearly polarized light with the same vibration direction, and then passes through the first wavefront modulation lens (customized according to the surface of the curved test material), so that the wavefront of the emergent light can be consistent with the surface of the curved test material. After the light passes through the curved glass, the light is decomposed into different polarized lights according to the main stress direction of the stress point, and then the polarized lights pass through the second wavefront modulation lens and the analyzer. The analyzer combines two light components of different polarization directions before and after the light passes through, thereby generating an interference fringe pattern, which is collected by the image sensor 60.
The optical path portion of the stress analysis system for the curved surface material inspection is the optical path portion of the stress analysis system for the curved surface material inspection, and the stress analysis system further comprises a processor 70, which is used for obtaining the interference image collected by the image sensor and detecting the stress distribution of the curved surface material inspection according to the interference image.
Specifically, the processor 70 is configured to detect an interference position and an interference fringe interval of the interference imaging, determine a stress point of the curved surface material to be inspected according to the interference position, and determine a stress distribution of the stress point according to the interference fringe interval.
That is to say, the method for analyzing the stress distribution by the processor 70 can refer to a detection method for the flat glass based on the interference principle in the conventional technology, because due to the action of the first wavefront modulation lens and the second wavefront modulation lens, the interference image acquired by the image sensor 60 is not interfered by the phase error caused by the non-fitting between the curved surface material to be detected and the wavefront, so that the stress distribution of the curved surface material to be detected and the stress distribution of the flat surface material to be detected are analyzed by the interference method with the same accuracy.
In this embodiment, the first wavefront modulation lens and the second wavefront modulation lens are optical devices customized according to a curved test material. That is, when the curved test material with different shapes or different outer surface curvatures is replaced for testing, the first wavefront modulation lens and the second wavefront modulation lens matched with the curved test material need to be customized according to the method.
In yet another embodiment, in order to accommodate a variety of curved inspection materials, customizable refractive elements may also be employed as the first and second wavefront modulating lenses. The customizable refractive element includes a transparent elastic cavity and a fill fluid having a fixed refractive index. The processor 70 is connected with the curved surface inspection material, after the curved surface inspection material is replaced, the outer surface shape of the curved surface inspection material is shot through the camera, then the processor 70 controls the filling or extraction of the filling liquid in the transparent elastic cavity according to the outer surface shape, and therefore the thickness of the refraction element is increased or decreased through the filling and extraction method of the filling liquid, and the effect of wave front modulation is achieved.
In one embodiment, as shown in fig. 1, the stress analysis system for curved test materials further comprises a phase adjuster 80 disposed in the optical path of the illumination beam, the phase adjuster being located between the light source and the polarizer for adjusting the phase of the illumination beam.
The image sensor 60 is also used to acquire interferometric imaging at multiple phases adjusted by the phase adjuster 80.
Specifically, the adjacent phase difference of the multiple phases adjusted by the phase adjuster is pi/2, the processor 70 is further configured to obtain at least 4 interference images acquired by the image sensor, and the phase differences of the illumination beams corresponding to the 4 interference images are pi/2, pi, and 3 pi/2, respectively.
That is, as shown with reference to FIG. 3, the processor 70 needs to control the image sensor 60 to capture at least 4 images. Firstly shooting one piece (corresponding to phase shift of 0 pi), then shooting another piece after shifting the phase of the illumination light beam by pi/2 relative to the initial phase on the light path of the illumination light beam through the phase adjuster 80, shooting another piece after shifting the phase of the illumination light beam by pi relative to the initial phase on the light path of the illumination light beam through the phase adjuster 80, shooting another piece after shifting the phase of the illumination light beam by 3 pi/2 relative to the initial phase on the light path of the illumination light beam through the phase adjuster 80, and collecting 4 interference images in total. In this embodiment, the phase adjuster 80 may be connected to the processor 70, and sequentially performs phase adjustment under the control of the control command of the processor 70. In other embodiments, the phase adjuster 70 may be adjusted manually, each phase shift of π/2, i.e., the manual control processor 70 acquires the interference image corresponding to that phase from the image sensor 60.
The processor 70 is further configured to obtain light intensity information of the same position in the 4 interference images, calculate a phase of an interference fringe of the position according to the light intensity information, perform wrapping processing to obtain a phase distribution of the interference fringe, and obtain a stress distribution of the curved surface inspection material according to the phase distribution and a photoelastic coefficient of the curved surface inspection material.
Specifically, the processor is configured to calculate the phase of the interference fringe at the same position in the 4 interference-imaged images according to the light intensity information at the same position, according to the following formula:
calculating the phase of the corresponding illumination beam at the (x, y) position on the interference image
Said I1(x,y)、I2(x,y)、I3(x,y)、I4(x, y) is the light intensity of the 4 interference images at the same (x, y) position respectively, wherein A (x, y) is the background intensity, and B (x, y) is the intensity of the illumination light beam. That is, when the conventional interferometry detects the stress distribution, the interference image detected by the image sensor is affected by the ambient light and the background light, and the light intensity of the ambient light or the background light cannot be effectively measured, so that the phase is reversely calculated by calculating the cosine value
In time, the calculation results are inaccurate, and thus erroneous phase data is obtained.
The phase shift method can show that 4 interference imaging images with phase differences of 0, pi/2, pi and 3 pi/2 in sequence are shot, the influence of ambient light A (x, y) can be eliminated through corresponding operation, and then the phase of any point on the interference imaging can be obtained through calculating the arc tangent
Finally, a phase diagram of the whole interference imaging is obtained (refer to fig. 3).
And after a phase diagram of interference imaging is obtained, the wrapping processing can be carried out, the phase distribution of interference fringes is obtained, and the stress distribution of the curved surface material to be detected is obtained according to the phase distribution and the photoelastic coefficient of the curved surface material to be detected. Specifically, referring to fig. 4, the processor may execute the following method by executing the computer program:
step S102: and acquiring an interference imaging image acquired by the image sensor.
Step S104: and calculating the arctangent of the phase of the point position according to the light intensity information of any point in the interference imaging image, thereby calculating the phase of the point position.
Step S106: and (4) obtaining a phase diagram (full-field phase distribution diagram) corresponding to the interference imaging by combining filtering denoising with a de-wrapping algorithm.
Step S108: and calculating to obtain a corresponding stress distribution diagram by combining the phase diagram and the photoelastic coefficient of the curved surface material to be detected.
The glass is subjected to stress by various reasons, including residual stress not released after heat treatment, structural stress due to defects of foreign matter (cracks, bubbles, stones, etc.), and the like. Different reasons correspond to different stress maps, so that the collected stress maps can be analyzed class by class, and reference is provided for the improvement of the glass production process. In this embodiment, large sample training and learning can also be performed using machine learning based on the glass stress profile. Specifically, referring to fig. 5, the processor is further configured to obtain a defect identification model based on machine learning, where the defect identification model at least includes output categories of cracks, bubbles, stones, and defects, and the output categories have corresponding confidence degrees after being trained by machine learning of sample stress distributions of corresponding categories;
the processor is further used for inputting the stress distribution into the defect identification model, and determining the defects corresponding to the curved surface material checking according to the obtained confidence degree of the output category.
That is, a stress distribution map generated by cracks, a stress distribution map generated by bubbles, and a stress distribution map generated by stones may be input as sample data into the defect recognition model for training, and the probability decision tree corresponding to the features in the stress distribution map is gradually perfected and accurate through deepening of training and increasing of samples. When the processor inputs the analyzed stress distribution map into the trained defect identification model, the defect identification model outputs the probability degree, i.e. the confidence degree, of each defect type (crack, bubble, stone and defect-free) corresponding to the stress distribution map. The processor may select the defect type with the highest confidence as the defect identification for the curved inspection material corresponding to the stress profile.
The embodiment of the invention has the following beneficial effects:
after the stress analysis system of the curved surface material to be detected is adopted, the wavefront modulation lenses are added in the front and the back of the curved surface material to be detected in the light path passing through the curved surface material to be detected, and the wavefront modulation lenses enable the wavefront of the illumination light beam reaching the curved surface material to be matched with the outer surface of the curved surface material to be detected due to the fact that optical path differences of the light beams transmitted to the outer surface of the curved surface material to be detected when the illumination light beam for interference imaging detection stress distribution reaches the curved surface material to be detected, so that the formed interference imaging is only objective reflection of the stress distribution in the curved surface material to be detected, and cannot be simultaneously influenced by interference phenomena generated due to inconsistent wavefronts, and therefore the accuracy of stress analysis is improved.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.
Claims (8)
1. The utility model provides a material's stress analysis system is examined to curved surface which characterized in that includes:
a light source for emitting an illumination beam;
the polarizer, the first wavefront modulation lens, the curved surface detection material, the second wavefront modulation lens, the analyzer and the image sensor are sequentially arranged on the light path of the illumination light beam;
the polarizer is used for polarizing the illumination light beam in a preset target polarization direction;
the thickness distribution of the first wavefront modulation lens and the distance from the curved surface material to be inspected satisfy the condition: the wavefront of the illumination beam reaching the incident surface of the curved surface material to be inspected is consistent with that of the curved surface material to be inspected
N is a refractive index of the first wavefront modulation lens, and two beams i and j of the illumination light beam enter the incident surface of the first wavefront modulation lens through positions Ai and Aj, exit through positions Bi and Bj on the exit surface of the first wavefront modulation lens, and enter through positions Ci and Cj on the incident surface of the curved inspection material;
the thickness distribution of the second wavefront modulation lens and the distance from the curved surface material to be inspected satisfy the condition: the second wavefront modulation lens and the first wavefront modulation lens form a conjugate system;
the analyzer is used for combining components of the illumination light beams with different polarization directions to generate interference;
the image sensor is used for acquiring interference imaging of the illumination light beam;
the stress analysis system further comprises a processor, wherein the processor is used for acquiring the interference imaging acquired by the image sensor and detecting the stress distribution of the curved surface material to be detected according to the interference imaging.
2. The stress analysis system of claim 1, wherein the light source is a monochromatic coherent light source and the illumination beam is a monochromatic coherent light beam.
3. The stress analysis system for curved surface material detection according to claim 1, wherein the processor is configured to detect an interference position and an interference fringe interval of the interference imaging, determine a stress point of the curved surface material detection according to the interference position, and determine a stress distribution of the stress point according to the interference fringe interval.
4. The stress analysis system of curved inspection material of claim 1, further comprising:
a phase adjuster disposed in an optical path of the illumination beam, the phase adjuster being positioned between the light source and the polarizer for adjusting a phase of the illumination beam;
the image sensor is also used for acquiring interference imaging under a plurality of phases adjusted by the phase adjuster.
5. The stress analysis system according to claim 4, wherein the phase adjuster adjusts the phase difference between adjacent phases to be pi/2.
6. The stress analysis system for curved inspection materials according to claim 5, wherein the processor is further configured to obtain at least 4 interference images collected by the image sensor, and the phase differences of the illumination light beams corresponding to the 4 interference images are pi/2, pi, 3 pi/2, respectively;
the processor is further configured to obtain light intensity information of the same position in the 4 interference images, calculate an interference fringe phase of the position according to the light intensity information, perform wrapping processing to obtain phase distribution of the interference fringe, and obtain stress distribution of the curved surface inspection material according to the phase distribution and the photoelastic coefficient of the curved surface inspection material.
7. The stress-analyzing system of claim 6, wherein the processor is further configured to analyze the material according to:
calculating the phase of the corresponding illumination beam at the (x, y) position on the interference image
Said I1(x，y)、I2(x，y)、I3(x，y)、I4(x, y) is the light intensity of the 4 interference images at the same (x, y) position respectively, wherein A (x, y) is the background intensity, and B (x, y) is the intensity of the illumination light beam.
8. The system for stress analysis of curved inspection material according to any one of claims 1 to 7, wherein the processor is further configured to obtain a defect identification model based on machine learning, the defect identification model at least comprises output categories of cracks, bubbles, stones and no defects, and the output categories have corresponding confidence degrees after being trained by machine learning of sample stress distribution of corresponding categories;
the processor is further used for inputting the stress distribution into the defect identification model, and determining the defect corresponding to the curved surface inspection material according to the obtained confidence of the output category.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2019/079333 WO2020191545A1 (en) | 2019-03-22 | 2019-03-22 | System for analyzing stress of curved detection sample |
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| CN112508043A (en) * | 2021-01-20 | 2021-03-16 | 苏州协同创新智能制造装备有限公司 | Method for detecting outer arc defects of screen edge based on die stress receptor |
| CN112802003B (en) * | 2021-02-08 | 2022-05-06 | 锋睿领创(珠海)科技有限公司 | Defect detection method, device and equipment based on photoelasticity and storage medium |
| US20220373411A1 (en) * | 2021-05-18 | 2022-11-24 | Palo Alto Research Center Incorporated | Stress engineering of transparent materials |
| CN115187594B (en) * | 2022-09-08 | 2023-09-08 | 济南博图信息技术有限公司 | Cerebral cortex model reconstruction method and system |
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| WO2020191545A1 (en) | 2020-10-01 |
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