CN108507953B - Method and device for detecting self-defect of membrane assembly - Google Patents
Method and device for detecting self-defect of membrane assembly Download PDFInfo
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- CN108507953B CN108507953B CN201810282997.2A CN201810282997A CN108507953B CN 108507953 B CN108507953 B CN 108507953B CN 201810282997 A CN201810282997 A CN 201810282997A CN 108507953 B CN108507953 B CN 108507953B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
Abstract
The application provides a method and a device for detecting self-defects of a membrane assembly, wherein the method comprises the following steps: obtaining a reference signature spectrum, the reference signature spectrum comprising: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component; acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum; acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum; and comparing the first image with the second image, and judging whether the to-be-detected film assembly has self defects. The detection method provided by the application can effectively solve the problem of low accuracy of the existing surface defect detection method.
Description
Technical Field
The application relates to the field of electronic product component defect detection, in particular to a method and a device for detecting self-defect of a strip membrane component.
Background
In the manufacturing process of electronic consumer product components, such as liquid crystal display screens, batteries, sound films, cameras and the like, defects such as scratches, stains, edge breakage and the like can be generated on the surfaces of the electronic product components due to poor process, insufficient environmental cleanliness, transportation collision and the like. The production and use of electronic consumer products have very high requirements on the cleanliness of the surfaces of the components, and therefore, cleaning and attaching a protective film are the most common way to ensure the cleanliness of the surfaces of the components. The surface quality of the electronic product assembly is usually carried out after cleaning and film pasting, so that the accurate detection of the surface defects of the electronic product assembly with the film can effectively improve the product yield and reduce the manufacturing cost.
Generally, an Automatic Optical Inspection (AOI) method is used to detect defects on the surface of an electronic product component, and in the method, an industrial camera is used in cooperation with a reasonable light source illumination mode to collect images on the surface of the electronic product component, and then a vision processing system is used to process the collected images and output a detection result through operation.
The inventors have problems in detecting surface defects of electronic product components using AOI. If the cleaning machine in the upstream process cannot completely clean the dirt on the surface of the component or the protective film is damaged, when AOI detection is adopted, the imaging characteristics of the dirt left after cleaning are the same as the imaging characteristics of the dirt of the component; the protection film scratch has the same imaging characteristics as the scratch on the surface of the component. Therefore, the component self-defect and the external interference factor are difficult to distinguish by simply using the vision processing system, and the detection accuracy is greatly reduced.
Disclosure of Invention
The application provides a method and a device for detecting the self-defect of a membrane assembly, which aim to solve the problem of low accuracy of the existing surface defect detection method.
The application provides a method for detecting self-defects of a strip membrane module in a first aspect, which comprises the following steps:
obtaining a reference signature spectrum, the reference signature spectrum comprising: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component;
acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum;
acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum;
and comparing the first image with the second image, and judging whether the to-be-detected film assembly has self defects.
Optionally, the specific step of acquiring the reference characteristic spectrum includes:
acquiring spectral response curves of an ideal component, an ideal protection membrane component and a dirty component;
determining the first characteristic spectrum which enables an ideal protective film not to be imaged according to the spectral response curve of the ideal component and the spectral response curve of the membrane component with the ideal protective film;
determining the second characteristic spectrum for non-imaging component contamination based on the spectral response curve of the ideal component and the spectral response curve of the soiled component.
Optionally, the specific steps of obtaining a first image of the to-be-tested film assembly according to the first characteristic spectrum and obtaining a second image of the to-be-tested film assembly according to the second characteristic spectrum further include:
determining the gray value distribution of the first image according to the first image;
and determining the gray value distribution of the second image according to the second image.
Optionally, the step of comparing the first image with the second image to determine whether the to-be-tested film assembly has a self-defect includes:
determining the coincidence value of each gray area of the first image and the second image according to the gray value distribution of the first image and the gray value distribution of the second image;
judging whether the coincidence value is 0 or not;
if the coincidence value is 0, the to-be-detected component with the film does not have self-defects;
and if the coincidence value is larger than 0, the to-be-detected film assembly has self-defect, and the same part of the gray scale area is a self-defect area.
Optionally, the step of comparing the first image with the second image to determine whether the to-be-tested film assembly has a self-defect includes:
extracting the sub-gray values of the first image in the areas with the same gray values according to the gray value distribution of the first image;
extracting the sub-gray values of the second image in the same gray value area according to the gray value distribution of the second image;
traversing the first image sub-gray value and the second image sub-gray value, and judging whether the sub-gray values are the same;
if the sub-gray values are the same, the to-be-detected assembly with the film has self-defects, and the gray value area corresponding to the same sub-gray value is a self-defect area;
and if the sub-gray values are different, the to-be-detected assembly with the film does not have self defects.
In a second aspect, the present application provides an apparatus for self-defect detection of a strip membrane module, the apparatus comprising:
a reference characteristic spectrum acquisition unit configured to acquire a reference characteristic spectrum including: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component;
the first image acquisition unit is used for acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum;
the second image acquisition unit is used for acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum;
and the image comparison unit is used for comparing the first image with the second image and judging whether the to-be-detected film assembly has self defects.
Optionally, the reference characteristic spectrum acquiring unit includes:
the spectral response curve acquisition unit is used for acquiring the spectral response curves of the ideal component, the membrane component with the ideal protection membrane and the component with the dirt;
a first characteristic spectrum determination unit for determining the first characteristic spectrum for making an ideal protective film not imaged according to the spectral response curve of the ideal component and the spectral response curve of the membrane component with the ideal protective film;
and the second characteristic spectrum determining unit is used for determining the second characteristic spectrum for enabling the component to be dirty and not to be imaged according to the spectral response curve of the ideal component and the spectral response curve of the component with the dirt.
Alternatively,
the first image acquisition unit includes:
a first gray value distribution determining unit, configured to determine a gray value distribution of a first image according to the first image;
the second image acquisition unit includes:
and the second gray value distribution determining unit is used for determining the gray value distribution of the second image according to the second image.
Optionally, the image contrast unit comprises:
a coincidence value determining unit, configured to determine a coincidence value of each gray area of the first image and the second image according to a gray value distribution of the first image and a gray value distribution of the second image;
a first judgment unit, configured to judge whether the coincidence value is 0;
if the coincidence value is 0, the to-be-detected component with the film does not have self-defects;
and if the coincidence value is larger than 0, the to-be-detected film assembly has self-defect, and the same part of the gray scale area is a self-defect area.
Optionally, the image contrast unit comprises:
the first extraction unit is used for extracting the sub-gray values of the first image in the same gray value areas according to the gray value distribution of the first image;
the second extraction unit is used for extracting the sub-gray values of the second image in the same gray value area according to the gray value distribution of the second image;
the second judging unit is used for traversing the first image sub-gray value and the second image sub-gray value and judging whether the sub-gray values are the same;
if the sub-gray values are the same, the to-be-detected assembly with the film has self-defects, and the gray value area corresponding to the same sub-gray value is a self-defect area;
and if the sub-gray values are different, the to-be-detected assembly with the film does not have self defects.
As can be seen from the above technologies, the present application provides a method and an apparatus for detecting a self-defect of a membrane module, wherein the method includes: obtaining a reference signature spectrum, the reference signature spectrum comprising: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component; acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum; acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum; and comparing the first image with the second image, and judging whether the to-be-detected film assembly has self defects. The device comprises: a reference characteristic spectrum acquisition unit configured to acquire a reference characteristic spectrum including: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component; the first image acquisition unit is used for acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum; the second image acquisition unit is used for acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum; and the image comparison unit is used for comparing the first image with the second image and judging whether the to-be-detected film assembly has self defects. When the method is used, before membrane module products with the membrane are detected in batches, each reference characteristic spectrum is determined by using spectrometer analysis and is used as a judgment reference of a subsequent step. And imaging each to-be-detected film-carrying component under the first characteristic spectrum and the second characteristic spectrum respectively, comparing the images obtained twice, and judging that the defect of the two images is the self-defect of the component. The defect detection method and the defect detection device can avoid the influence of membrane damage and uncleaned dirt on the self-defect detection result of the component, and effectively improve the detection accuracy of the surface defect of the component.
Drawings
In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any creative effort.
FIG. 1 is a flow chart of a method for detecting self-contained defects of a membrane module provided by the present application;
FIG. 2(A) is a first image of the type provided herein;
FIG. 2(B) is a second image of the type provided herein;
FIG. 3 is a flow chart of a method for obtaining a reference signature spectrum provided herein;
FIG. 4 is a flowchart of a method for acquiring a first image and a second image provided herein;
FIG. 5 is a flow chart of a method for determining self-defects of a tape film assembly under test according to the present application;
FIG. 6 is a flow chart of another method provided herein for determining self-defects in a tape film assembly under test;
FIG. 7 is a schematic structural diagram of an apparatus with a membrane module for detecting self-defects provided by the present application;
fig. 8 is a schematic structural diagram of a reference characteristic spectrum obtaining unit provided in the present application;
fig. 9 is a schematic structural diagram of a first image acquiring unit and a second image acquiring unit provided in the present application;
FIG. 10 is a schematic diagram of an embodiment of an image contrast unit provided in the present application;
fig. 11 is a schematic diagram of another specific structure of an image contrast unit provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying 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 application.
Referring to fig. 1, a flow chart of a method for detecting a self-contained defect of a membrane module.
The embodiment of the application provides a method for detecting the self-defect of a strip membrane assembly, which comprises the following steps:
s100, acquiring a reference characteristic spectrum, wherein the reference characteristic spectrum comprises: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component;
s200, acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum;
s300, acquiring a second image of the to-be-detected assembly with the film according to the second characteristic spectrum;
s400, comparing the first image with the second image, and judging whether the to-be-detected film assembly has self defects.
Due to the fact that various substances (atoms, groups, molecules and high molecular compounds) have the characteristics of emission, absorption and scattering spectrums when interacting with light radiation energy, due to the fact that the energy levels of microstructures in the substances are different, characteristic spectrum curves generated by the substances are unique, namely a component with an ideal film, a component with dirt, an ideal component and self-defects on the component have unique characteristic spectrums. Therefore, whether the to-be-tested film assembly has the self-defect or not can be distinguished and identified by using different characteristic spectral curves.
When the device is used, before the membrane module products are detected in batches, firstly, the membrane module with an ideal protective film is analyzed by a spectrometer to obtain a first characteristic spectrum, wherein the ideal protective film is a protective film without damage and dirt; and analyzing the dirty assemblies by using a spectrometer to obtain a second characteristic spectrum, wherein the dirty assemblies do not have self-defects, and the dirty types can be greasy dirt, water stain, fingerprint and the like. In order to improve the detection accuracy, the stain types should be expanded as much as possible, and the second characteristic spectrums of various stained components can be formed into a characteristic spectrum library for later use and analysis. And taking the first characteristic spectrum and the second characteristic spectrum as judgment references of subsequent steps. And imaging each to-be-detected film assembly under the first characteristic spectrum and the second characteristic spectrum respectively to obtain a first image and a second image respectively. As shown in fig. 2, wherein fig. 2(a) is a type of the first image, there are: A. no special imaging (no change in gray level); B. showing uncleaned soiling of the component and/or a component defect itself, fig. 2(B) is a type of second image, having: A. no special imaging (no change in gray level); B. damage to the display protection film and/or component defects themselves. Comparing the two images, wherein if the two images have the same image block, the image block is the self-defect of the component; if any identical image block does not exist in the two images, the detected component has no self-defect, and the displayed images are all damages of the protective film and/or dirt on the component for cleaning. Different remedial measures can be accurately taken according to the judgment result, so that the time and the cost are saved.
The defect detection method and the defect detection device can avoid the influence of membrane damage and uncleaned dirt on the self-defect detection result of the component, and effectively improve the detection accuracy of the surface defect of the component.
Referring to fig. 3, a flow chart for obtaining a baseline signature spectrum.
Optionally, the specific step of acquiring the reference characteristic spectrum includes:
s101, acquiring spectral response curves of an ideal component, an ideal protective membrane component and a component with dirt;
s102, determining the first characteristic spectrum which enables an ideal protective film not to be imaged according to the spectral response curve of the ideal component and the spectral response curve of the membrane component with the ideal protective film;
s103, determining the second characteristic spectrum which enables the component to be dirty and not to be imaged according to the spectral response curve of the ideal component and the spectral response curve of the component with the dirty component.
If the spectra with the ideal protective film component and the dirty component detected by the spectrometer are directly used as the first characteristic spectrum and the second characteristic spectrum, the image of the film component to be detected obtained by using the two characteristic spectra can display interference images such as dirt of different components and a protective film besides necessary characteristic images, which greatly increases the difficulty and time consumption of subsequent image comparison work.
By comparing and analyzing the spectral response curves of an ideal module and an ideal module with an ideal protective film module, wherein the ideal module is a module without damage and dirt, a characteristic spectrum which can enable the protective film not to be imaged is obtained, and the characteristic spectrum is determined as a first characteristic spectrum. And comparing and analyzing the spectral response curves of the ideal component and the component with the dirt to obtain a characteristic spectrum which can enable each dirt not to be imaged, and determining the characteristic spectrum as a second characteristic spectrum. Therefore, the image obtained by the membrane assembly to be detected through the first characteristic spectrum and the second characteristic spectrum is an image without special imaging or only containing necessary characteristic images, wherein the necessary characteristic images in the first image are the dirt and self-defect of the assembly, and the necessary characteristic images in the second image are the damage of the protective membrane and the self-defect of the assembly, so that the interference of various dirt of the protective membrane image in the first image and the assembly in the second image on the subsequent image comparison process is effectively avoided, and the accuracy and the efficiency of detection are improved.
Referring to fig. 4, a flow chart of a method of acquiring a first image and a second image.
Optionally, the specific steps of obtaining a first image of the to-be-tested film assembly according to the first characteristic spectrum and obtaining a second image of the to-be-tested film assembly according to the second characteristic spectrum further include:
s201, determining the gray value distribution of the first image according to the first image;
s202, determining the gray value distribution of the second image according to the second image.
Various defects on the assembly with the membrane, such as a damaged part of the membrane, self-defect of the assembly and dirt of the assembly, can present different gray values on the image, and by determining the gray value distribution of the first image and the second image, the characteristic image of each defect part can be analyzed and determined rapidly and clearly, so that the basis of accurate data and graph is provided for the comparison work of subsequent images, and the efficiency and the accuracy of the whole detection process are effectively improved.
Referring to fig. 5, a flow chart of a method for determining self-defects of a tape film assembly under test is shown.
Optionally, the step of comparing the first image with the second image to determine whether the to-be-tested film assembly has a self-defect includes:
s401, determining a coincidence value of each gray scale region of the first image and the second image according to the gray scale value distribution of the first image and the gray scale value distribution of the second image;
s402, judging whether the coincidence degree value is 0 or not;
s403, if the coincidence value is 0, the to-be-detected assembly with the film does not have self-defects;
s404, if the coincidence value is larger than 0, the to-be-detected film assembly has self-defects, and the same gray scale area is a self-defect area.
According to the gray value distribution of the first image and the second image, the gray areas with the same gray value can be obviously determined, the gray areas of the two images are compared one by one, and the gray areas with the same boundary shape can be found. Calculating the coincidence value of the gray level regions of the two images, for example, if the two images have one corresponding gray level region, the coincidence value is 1, if the two images have two corresponding gray level regions, the coincidence value is 2, and so on; if such a gray scale region does not exist, the coincidence value is 0. Only when the component has self defects, no matter which characteristic spectrum is adopted, the phenomenon that the gray value change area appears can occur. Therefore, when the coincidence value is greater than 0, it is proved that the gray areas of the two images under the first characteristic spectrum and the second characteristic spectrum are the same, that is, the to-be-tested component with the film has self-defects, and the same gray area is the self-defect area. The detection method provided by the embodiment can quickly and accurately find the self-defect area of the component, and avoids the interference of other factors.
Referring to fig. 6, another flow chart of a method for determining self-defects of a tape film assembly under test is shown.
Optionally, the step of comparing the first image with the second image to determine whether the to-be-tested film assembly has a self-defect includes:
s405, extracting the sub-gray values of the first image in the areas with the same gray values according to the gray value distribution of the first image;
s406, extracting the sub-gray values of the second image in the areas with the same gray values according to the gray value distribution of the second image;
s407, traversing the first image sub-gray value and the second image sub-gray value, and judging whether the sub-gray values are the same;
s408, if the gray sub-values are the same, the to-be-tested assembly with the film has self-defects, and the gray value area corresponding to the same gray sub-value is a self-defect area;
and S409, if the sub-gray values are different, the to-be-detected assembly with the film does not have self defects.
According to the gray value distribution of the first image and the second image, the gray value of the area with the same gray value can be accurately obtained, for example, the gray value of the area with the same gray value in the first image is respectively defined as a first image sub-gray value A, a first image sub-gray value B, a first image sub-gray value C and the like; the gray values of the regions with the same gray value in the second image are respectively defined as a second image sub-gray value A, a second image sub-gray value B, a second image sub-gray value C and the like. According to the principle that the regions with the same gray value are necessarily the same defect, the same defect region with the same gray value in the two images can be accurately judged. Only the device is self-defective can show the region with the gray value change under the first characteristic spectrum and the second characteristic spectrum, so that the gray regions with the same gray value in the two images are the self-defective positions of the device. Therefore, if the two images have the same sub-gray value, the film-attached component to be detected has self-defect, and the area with the same sub-gray value is a self-defect area; and if the same sub-gray value does not exist, the to-be-detected assembly with the film does not have self-defect. The detection method provided by the embodiment can accurately judge whether the component has the defect, and effectively avoids the interference of other factors.
Referring to fig. 7, a schematic structural diagram of a self-defect detection device with a membrane module.
The embodiment of the application also provides a take membrane module from there being defect detection device, the device includes:
a reference characteristic spectrum acquisition unit 1 configured to acquire a reference characteristic spectrum, the reference characteristic spectrum including: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component;
the first image acquisition unit 2 is used for acquiring a first image of the to-be-detected film-attached component according to the first characteristic spectrum;
the second image acquisition unit 3 is used for acquiring a second image of the to-be-detected film-attached component according to the second characteristic spectrum;
and the image comparison unit 4 is used for comparing the first image with the second image and judging whether the to-be-detected film assembly has self defects.
Referring to fig. 8, a specific structure diagram of a reference characteristic spectrum acquiring unit is shown.
Optionally, the reference characteristic spectrum acquiring unit 1 includes:
a spectral response curve acquiring unit 11, configured to acquire spectral response curves of an ideal component, an ideal protective film component and a dirty component;
a first characteristic spectrum determination unit 12 for determining the first characteristic spectrum for making an ideal protective film not to be imaged according to the spectral response curve of the ideal module and the spectral response curve of the module with the ideal protective film;
a second characteristic spectrum determination unit 13 for determining said second characteristic spectrum for rendering the component dirty non-imaging, based on the spectral response curve of said ideal component and the spectral response curve of said component with dirt.
Referring to fig. 9, a specific structure of the first image capturing unit and the second image capturing unit is schematically illustrated.
Alternatively,
the first image acquisition unit 2 includes:
a first gray value distribution determining unit 21 configured to determine a gray value distribution of a first image according to the first image;
the second image acquisition unit 3 includes:
a second distribution of gray values determining unit 31 is configured to determine a distribution of gray values of the second image according to the second image.
Referring to fig. 10, a detailed structure diagram of an image contrast unit is shown.
Optionally, the image comparison unit 4 includes:
a coincidence value determining unit 41, configured to determine a coincidence value of each gray scale region of the first image and the second image according to the gray scale value distribution of the first image and the gray scale value distribution of the second image;
a first judgment unit 42, configured to judge whether the coincidence value is 0;
if the coincidence value is 0, the to-be-detected component with the film does not have self-defects;
and if the coincidence value is larger than 0, the to-be-detected film assembly has self-defect, and the same part of the gray scale area is a self-defect area.
Referring to fig. 11, another specific structure of the image contrast unit is shown.
Optionally, the image comparison unit 4 includes:
a first extracting unit 43, configured to extract a first image sub-gray value of each same gray value region according to the gray value distribution of the first image;
a second extracting unit 44, configured to extract a second image sub-gray value of each region with the same gray value according to the gray value distribution of the second image;
a second determining unit 45, configured to traverse the first image sub-gray scale value and the second image sub-gray scale value, and determine whether the sub-gray scale values are the same;
if the sub-gray values are the same, the to-be-detected assembly with the film has self-defects, and the gray value area corresponding to the same sub-gray value is a self-defect area;
and if the sub-gray values are different, the to-be-detected assembly with the film does not have self defects.
According to the technical scheme, the application provides a method for detecting the self-defect of the membrane assembly, and the method comprises the following steps: obtaining a reference signature spectrum, the reference signature spectrum comprising: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component; acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum; acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum; and comparing the first image with the second image, and judging whether the to-be-detected film assembly has self defects. When the method is used, before membrane module products with the membrane are detected in batches, each reference characteristic spectrum is determined by using spectrometer analysis and is used as a judgment reference of a subsequent step. And imaging each to-be-detected film-carrying component under the first characteristic spectrum and the second characteristic spectrum respectively, comparing the images obtained twice, and judging that the defect of the two images is the self-defect of the component. The defect detection method and the defect detection device can avoid the influence of membrane damage and uncleaned dirt on the self-defect detection result of the component, and effectively improve the detection accuracy of the surface defect of the component.
It should be noted that, in specific implementations, the present invention also provides a computer storage medium, where the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment of the user identity service providing method or the user registration method provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (8)
1. A method for detecting the self-defect of a membrane assembly, which is characterized by comprising the following steps:
obtaining a reference signature spectrum, the reference signature spectrum comprising: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component;
acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum;
acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum;
comparing the first image with the second image, and judging whether the to-be-detected film assembly has self defects;
the specific steps of obtaining the reference characteristic spectrum comprise:
acquiring spectral response curves of an ideal component, an ideal protection membrane component and a dirty component;
determining the first characteristic spectrum which enables an ideal protective film not to be imaged according to the spectral response curve of the ideal component and the spectral response curve of the membrane component with the ideal protective film;
determining the second characteristic spectrum for non-imaging component contamination based on the spectral response curve of the ideal component and the spectral response curve of the soiled component.
2. The method for detecting the self-defect of the film-equipped component according to claim 1, wherein the specific steps of obtaining the first image of the film-equipped component to be detected according to the first characteristic spectrum and obtaining the second image of the film-equipped component to be detected according to the second characteristic spectrum further comprise:
determining the gray value distribution of the first image according to the first image;
and determining the gray value distribution of the second image according to the second image.
3. The method for detecting the self-defect of the film assembly according to claim 2, wherein the step of comparing the first image with the second image to determine whether the film assembly to be detected has the self-defect comprises the steps of:
determining the coincidence value of each gray area of the first image and the second image according to the gray value distribution of the first image and the gray value distribution of the second image;
judging whether the coincidence value is 0 or not;
if the coincidence value is 0, the to-be-detected component with the film does not have self-defects;
and if the coincidence value is larger than 0, the to-be-detected film assembly has self-defect, and the same part of the gray scale area is a self-defect area.
4. The method for detecting the self-defect of the film assembly according to claim 2, wherein the step of comparing the first image with the second image to determine whether the film assembly to be detected has the self-defect comprises the steps of:
extracting the sub-gray values of the first image in the areas with the same gray values according to the gray value distribution of the first image;
extracting the sub-gray values of the second image in the same gray value area according to the gray value distribution of the second image;
traversing the first image sub-gray value and the second image sub-gray value, and judging whether the sub-gray values are the same;
if the sub-gray values are the same, the to-be-detected assembly with the film has self-defects, and the gray value area corresponding to the same sub-gray value is a self-defect area;
and if the sub-gray values are different, the to-be-detected assembly with the film does not have self defects.
5. A self-defect detection device with a membrane module is characterized by comprising:
a reference characteristic spectrum acquisition unit configured to acquire a reference characteristic spectrum including: a first characteristic spectrum with an ideal protective membrane component and a second characteristic spectrum with a dirty component;
the first image acquisition unit is used for acquiring a first image of the to-be-detected film assembly according to the first characteristic spectrum;
the second image acquisition unit is used for acquiring a second image of the to-be-detected film-carrying component according to the second characteristic spectrum;
the image comparison unit is used for comparing the first image with the second image and judging whether the to-be-detected film assembly has self defects;
the reference characteristic spectrum acquisition unit includes:
the spectral response curve acquisition unit is used for acquiring the spectral response curves of the ideal component, the membrane component with the ideal protection membrane and the component with the dirt;
a first characteristic spectrum determination unit for determining the first characteristic spectrum for making an ideal protective film not imaged according to the spectral response curve of the ideal component and the spectral response curve of the membrane component with the ideal protective film;
and the second characteristic spectrum determining unit is used for determining the second characteristic spectrum for enabling the component to be dirty and not to be imaged according to the spectral response curve of the ideal component and the spectral response curve of the component with the dirt.
6. The film-attached component self-defect detecting method according to claim 5,
the first image acquisition unit includes:
a first gray value distribution determining unit, configured to determine a gray value distribution of a first image according to the first image;
the second image acquisition unit includes:
and the second gray value distribution determining unit is used for determining the gray value distribution of the second image according to the second image.
7. The film assembly self-defect detection method of claim 6, wherein the image contrast unit comprises:
a coincidence value determining unit, configured to determine a coincidence value of each gray area of the first image and the second image according to a gray value distribution of the first image and a gray value distribution of the second image;
a first judgment unit, configured to judge whether the coincidence value is 0;
if the coincidence value is 0, the to-be-detected component with the film does not have self-defects;
and if the coincidence value is larger than 0, the to-be-detected film assembly has self-defect, and the same part of the gray scale area is a self-defect area.
8. The film assembly self-defect detection method of claim 6, wherein the image contrast unit comprises:
the first extraction unit is used for extracting the sub-gray values of the first image in the same gray value areas according to the gray value distribution of the first image;
the second extraction unit is used for extracting the sub-gray values of the second image in the same gray value area according to the gray value distribution of the second image;
the second judging unit is used for traversing the first image sub-gray value and the second image sub-gray value and judging whether the sub-gray values are the same;
if the sub-gray values are the same, the to-be-detected assembly with the film has self-defects, and the gray value area corresponding to the same sub-gray value is a self-defect area;
and if the sub-gray values are different, the to-be-detected assembly with the film does not have self defects.
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