CN117670777A - Visual detection method and device for surface defects of silicon wafer - Google Patents
Visual detection method and device for surface defects of silicon wafer Download PDFInfo
- Publication number
- CN117670777A CN117670777A CN202211040991.7A CN202211040991A CN117670777A CN 117670777 A CN117670777 A CN 117670777A CN 202211040991 A CN202211040991 A CN 202211040991A CN 117670777 A CN117670777 A CN 117670777A
- Authority
- CN
- China
- Prior art keywords
- silicon wafer
- area
- image
- module
- region
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 title claims abstract description 205
- 229910052710 silicon Inorganic materials 0.000 title claims abstract description 204
- 239000010703 silicon Substances 0.000 title claims abstract description 204
- 230000007547 defect Effects 0.000 title claims abstract description 124
- 238000001514 detection method Methods 0.000 title claims abstract description 62
- 230000000007 visual effect Effects 0.000 title claims description 10
- 238000000034 method Methods 0.000 claims abstract description 16
- 235000012431 wafers Nutrition 0.000 claims description 181
- 230000011218 segmentation Effects 0.000 claims description 15
- 238000000605 extraction Methods 0.000 claims description 14
- 238000011179 visual inspection Methods 0.000 claims description 13
- 230000005540 biological transmission Effects 0.000 claims description 8
- 230000002950 deficient Effects 0.000 claims description 6
- 238000005507 spraying Methods 0.000 claims description 5
- 238000005286 illumination Methods 0.000 claims description 3
- 230000001131 transforming effect Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 abstract description 3
- 238000012546 transfer Methods 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 4
- 238000007599 discharging Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 239000007921 spray Substances 0.000 description 3
- 239000000284 extract Substances 0.000 description 2
- 230000033001 locomotion Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Landscapes
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- Testing Or Measuring Of Semiconductors Or The Like (AREA)
Abstract
The invention relates to the technical field of machine vision defect detection, in particular to a method and a device for detecting surface defects of a silicon wafer, wherein the detection method comprises the following steps: acquiring a silicon wafer surface image; performing Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer; removing a low-frequency signal in the spectrogram; fourier transform of the spectrogram without the low-frequency signal is reversed to a return space domain, so that a transformed image is obtained; dividing the transformed image by a threshold on a airspace, and extracting a bright region to obtain a potential defect region; judging whether each potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region. The invention detects the defects of silicon drop, dirt and the like on the surface of the silicon wafer by collecting the image on the surface of the silicon wafer and applying the image processing technology, and has higher detection precision.
Description
Technical Field
The invention relates to the technical field of machine vision defect detection, in particular to a method and a device for vision detection of silicon wafer surface defects.
Background
With the rapid development of the semiconductor and photovoltaic industries, the quality requirements of equipment on silicon wafers are higher and higher, and the surface defects such as dirt defects and silicon drop defects of the silicon wafers are one of the main quality defects of the silicon wafers. The traditional detection method for the dirt and silicon drop defects adopts manual naked eye identification detection, has larger instability and unreliability, has limited detection capability for the defects of subtle defects and insignificant gray scale chromatic aberration, and is difficult to realize accurate comprehensive detection. Due to the defects of the manual naked eye detection, how to improve the dirt on the surface of the silicon wafer and the detection precision of the silicon drop defect is a technical problem which needs to be solved by the technicians in the field.
Disclosure of Invention
In view of the above, the invention provides a visual detection method and device for surface defects of a silicon wafer, which mainly aims to solve the technical problems that: how to improve the detection precision of dirt on the surface of the silicon wafer and silicon drop defects.
In order to achieve the above purpose, the present invention mainly provides the following technical solutions:
in one aspect, an embodiment of the present invention provides a method for visually detecting a surface defect of a silicon wafer, including the steps of: acquiring a silicon wafer surface image; performing Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer; removing a low-frequency signal in the spectrogram; fourier transform of the spectrogram without the low-frequency signal is reversed to a return space domain, so that a transformed image is obtained; dividing the transformed image by a threshold on a airspace, and extracting a bright region to obtain a potential defect region; judging whether each potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region.
Optionally, the acquiring the surface image of the silicon wafer specifically includes: transmitting the silicon wafer to a set shooting area; photographing the set photographing region to obtain a first image containing the surface of the silicon wafer; extracting a silicon wafer surface area in a first image; and generating a silicon wafer surface image according to the silicon wafer surface area.
Optionally, the extracting the surface area of the silicon wafer in the first image specifically includes: dividing the first image threshold value into a brightness-taking area; filling the bright areas with a filling function; performing open operation on the filled bright region to obtain a silicon wafer detection region, wherein the silicon wafer detection region comprises a silicon wafer surface region; cutting the silicon wafer detection area to obtain a silicon wafer surface area;
optionally, the function formula of the fourier transform is:
and/or the number of the groups of groups,
the inverse fourier transform function is:
wherein x, y are the spatial variables of the image respectively, and u, v are the frequency variables of the image respectively.
Optionally, the removing the low-frequency signal in the spectrogram specifically includes: generating a circular region with the radius r by taking the center of the frequency domain image as the circle center; and spraying the round area to enable the gray value to be 0.
Optionally, in the method for visually detecting a surface defect of a silicon wafer, according to characteristics of each potential defect area, determining whether each potential defect area is a silicon drop and dirt area includes: comparing the area, perimeter, length, width and density of each potential defect area with the upper limit value and the lower limit value of the corresponding first set range value and the upper limit value and the lower limit value of the second set range value respectively, and judging that the potential defect is a silicon falling area if any one or more than two of the area, perimeter, length, width and density of the potential defect area are in the corresponding first set range value; and if any one or more of the area, the perimeter, the length, the width and the density of the potential defect area are within the corresponding second set range value, judging that the potential defect is a dirty area.
On the other hand, the embodiment of the invention also provides a silicon wafer surface defect visual detection device, which comprises:
the silicon wafer image acquisition module is used for acquiring a silicon wafer surface image;
the Fourier transform module is used for carrying out Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer;
the low-frequency signal removing module is used for removing the low-frequency signals in the spectrogram;
the inverse Fourier transform module is used for inversely Fourier transforming the spectrogram without the low-frequency signal into a return space domain to obtain a transformed image;
the potential defect area generating module is used for threshold segmentation of the transformed image in the airspace, extracting a bright area and obtaining a potential defect area;
the defect judging module is used for judging whether the potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region.
Optionally, the silicon wafer image acquisition module comprises a transmission module, a photographing module, an extraction module and an image generation module; the transmission module is used for transmitting the silicon wafer to a set shooting area; the photographing module is used for photographing the set photographing area to obtain a first image containing the surface of the silicon wafer; the extraction module is used for extracting the surface area of the silicon wafer in the first image; the image generation module is used for generating a silicon wafer surface image according to the silicon wafer surface area.
Optionally, the visual detection device for the surface defects of the silicon wafer further comprises a motor, a system controller, a light source controller, an encoder, a photoelectric sensor and a light source; the motor is used for providing power for the transmission module to transmit the silicon wafer to the set shooting area; the encoder is used for being connected with the motor so as to generate a first signal when the motor is started; the photoelectric sensor is used for generating a second signal when detecting that the silicon wafer enters the set shooting area; the light source is used for providing illumination for photographing of the photographing module; the light source controller is used for controlling the light source to be turned on for a set time according to the second signal; the system controller is used for controlling the photographing module to photograph according to the first signal and the second signal.
Optionally, the extracting module comprises a threshold segmentation module, a function filling module, an open operation module and a clipping module; the threshold segmentation module is used for threshold segmentation and brightness extraction of the first image; the function filling module is used for filling the bright area by using a filling function; the on operation module is used for performing on operation on the filled bright region to obtain a silicon wafer detection region, wherein the silicon wafer detection region comprises a silicon wafer surface region; the cutting module is used for cutting the silicon wafer detection area to obtain the silicon wafer surface area.
Optionally, the low-frequency signal removing module comprises a circular area generating module and a spraying module; the circular region generation module is used for generating a circular region with the radius r by taking the center of the frequency domain image as the circle center; and the spraying module sprays the round area to enable the gray value of the round area to be 0.
Optionally, the defect judging module comprises a comparing module and a controller; the comparison module is used for comparing the area, the perimeter, the length, the width and the density of each potential defect area with the upper limit value and the lower limit value of the corresponding first set range value and the upper limit value and the lower limit value of the corresponding second set range value respectively; the controller is used for generating a silicon drop zone signal when any one or more of the area, the perimeter, the length, the width and the density of the potential defect zone are within a corresponding first set range value; and any one or more of the area, perimeter, length, width and density of the potential defect area is within a corresponding second set range value, generating a dirty area signal.
By means of the technical scheme, the visual detection method and device for the surface defects of the silicon wafer have the following beneficial effects:
1. the invention detects the defects of silicon falling, dirt and the like on the surface of the silicon wafer by collecting the image on the surface of the silicon wafer and applying the image processing technology, and compared with the manual naked eye detection in the prior art, the invention has higher detection precision, can detect the surface defects of the silicon wafer by adopting a machine and has higher detection efficiency;
2. compared with the prior art, the invention uses vision to inspect the defects of silicon falling, dirt and the like on the surface of the silicon wafer, detects and eliminates the defects of the silicon wafer on the premise of not influencing the productivity of a loading and unloading machine, reduces the influence of the defective silicon wafer on the manufacturing process, greatly improves the detection efficiency and the detection precision in the production and detection link of the solar cell, has simple and scientific structure and has good application and popularization values.
The foregoing description is only an overview of the present invention, and is intended to provide a better understanding of the present invention, as it is embodied in the following description, with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
FIG. 1 is a flow chart of a visual inspection method for surface defects of a silicon wafer according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of wafer contamination detection;
FIG. 3 is a photograph logic flow diagram;
fig. 4 is a schematic diagram of a visual inspection device for surface defects of a silicon wafer.
Reference numerals: 1. an industrial personal computer; 2. an electric appliance cabinet; 3. a light source controller; 4. a camera; 5. a lens; 6. a light source; 7. a mechanical module; 8. a photoelectric sensor; 9. and (3) a silicon wafer.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, if directional indications (such as up, down, left, right, front, and rear … …) are included in the embodiments of the present invention, the directional indications are merely used to explain the relative positional relationship, movement conditions, etc. between the components in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indications are correspondingly changed.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present invention, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present invention.
As shown in fig. 1, a visual inspection method for surface defects of a silicon wafer according to an embodiment of the present invention may be implemented through the following steps S1 to S6. Steps S1 to S6 are described below, respectively.
Wherein, step S1: and obtaining a silicon wafer surface image. The "wafer surface image" herein includes only the surface region of the wafer, and does not include other regions other than the wafer surface. The wafer has two sides, and if the wafer is placed horizontally, the surface image of the wafer may be the upper surface image of the wafer or the lower surface image of the wafer.
In order to acquire the surface image of the silicon wafer, it can be realized by the following steps S11 to S14. Specifically, step S11: and transmitting the silicon wafer to a set shooting area. The silicon wafer may be transferred to the set photographing region by a conveyor belt or the like, for example. Step S12: and photographing the set photographing region to obtain a first image containing the surface of the silicon wafer. In this step, a camera such as an area array CCD camera may be used to take a picture of the set photographing region. Step S13: and extracting the surface area of the silicon wafer in the first image. Step S14: and generating a silicon wafer surface image according to the silicon wafer surface area.
The first image includes the silicon wafer surface area and other areas such as a conveyor belt area, etc., and in order to extract the silicon wafer surface area in the first image, it may be implemented by the following steps S131 to S134. Steps S131 to S134, specifically, step S131 will be described below: the first image is thresholded to highlight the region. The specific manner of threshold segmentation is the prior art and will not be described in detail herein. Step S132: the bright areas are filled with a filling function. The filling function is a prior art and will not be described in detail herein. Step S133: and performing open operation on the filled bright region to obtain a silicon wafer detection region, wherein the silicon wafer detection region comprises a silicon wafer surface region. The filled bright area can be subjected to open operation in the horizontal direction by using a rectangle with the length and the width of a multiplied by b so as to remove the area and the noise point of the conveyor belt, wherein a/b is more than or equal to 10. Step S134: cutting the silicon wafer detection area to obtain the silicon wafer surface area. The silicon wafer detection area is cut, so that the surface area of the silicon wafer can be extracted from the silicon wafer detection area, the calculation amount of the later-stage image can be reduced, and the image of other areas can be prevented from being interfered.
Step S2: and carrying out Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer.
Wherein, the function formula of the Fourier transform is:x and y are the spatial variables of the image, and u and v are the frequency variables of the image.
Step S3: the low frequency signal in the spectrogram is removed.
Specifically, the surface image of the silicon wafer is subjected to Fourier transform to obtain a frequency domain image, and a circular area with the radius r can be generated by taking the center of the frequency domain image as the center of a circle. Then, the circular area is sprayed so that the gray value is 0. The farther the distance from the center point of the frequency domain image is, the higher the corresponding frequency is, and the middle and low frequency parts can be approximately included by adjusting the gray value in the circular area to 0, so that the purpose of removing the low frequency signals is achieved. The r value can be selected according to actual conditions.
Step S4: and (3) performing inverse Fourier transform on the spectrogram without the low-frequency signals to obtain a transformed image.
Wherein the inverse fourier transform function is:x and y are the spatial variables of the image, and u and v are the frequency variables of the image.
Step S5: and (5) segmenting the transformed image in the spatial domain by a threshold value, and extracting a bright region to obtain a potential defect region. In the step S5, after the bright area is obtained by extraction, if the bright area is an integral, the bright area needs to be subjected to a process of disconnecting the connected area, so as to obtain discrete potential defect areas.
Step S6: judging whether each potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region.
To determine whether each potentially defective region is a silicon drop and dirty region, it may be implemented in the following steps S61 and S62, specifically, step S61: the area, perimeter, length, width and density of each potential defect area are compared with the upper and lower limit values of the corresponding first set range value and the upper and lower limit values of the second set range value, respectively. In other words, each of the parameters of the area, perimeter, length, width and density of the region corresponds to a first set range value and a second set range value, for example, the first set range value of the region area is a1-a2, and the second set range value is: a1'-a2'; the first set range of values for the perimeter of the region is b1-b2, and the second set range of values is: b1'-b2'; the first set range value of the zone length is c1-c2, and the second set range value is: c1'-c2'; the first set range value of the area width is d1-d2, and the second set range value is: d1'-d2'; the first set range of values for the area density is e1-e2, and the second set range of values is: e1'-e2'. Step S62: if any one or more of the area, the perimeter, the length, the width and the density of the potential defect area are within the corresponding first set range value, judging that the potential defect is a silicon falling area; and if any one or more of the area, the height and the width of the potential defect area are within the corresponding second set range value, judging that the potential defect is a dirty area.
In a specific application example, if the area, perimeter, length, width and density of the potential defect area are all within the first set range values corresponding to each other, that is, the area of the potential defect area is within a1-a2, the perimeter is within b1-b2, the length is within c1-c2, the width is within d1-d2, and the density is within e1-e2, the potential defect area is determined to be a silicon drop area. If the area, perimeter, length, width and density of the potential defect area are all within the second set range values corresponding to each other, namely the area of the potential defect area is within a1'-a2', the perimeter is within b1'-b2', the length is within c1'-c2', the width is within d1'-d2', and the density is within e1'-e2', judging that the potential defect area is a dirty area. Wherein fig. 2 shows a schematic view of a wafer dirty region.
Wherein, the characteristic value of the dirty defect area is obviously larger than that of the silicon falling area.
In the above example, the invention detects the defects of silicon drop, dirt and the like on the surface of the silicon wafer by collecting the image on the surface of the silicon wafer and applying the image processing technology, compared with the detection by naked eyes in the prior art, the detection precision of the invention is higher, and the detection efficiency is also higher by adopting a machine to detect the surface defects of the silicon wafer.
The embodiment of the invention also provides a visual detection device for the surface defects of the silicon wafer, which comprises a silicon wafer image acquisition module, a Fourier transform module, a low-frequency signal removal module, an inverse Fourier transform module, a potential defect area generation module and a defect judgment module.
The silicon wafer image acquisition module is used for acquiring a silicon wafer surface image. The "wafer surface image" herein includes only the surface region of the wafer 9, and does not include other regions than the surface of the wafer 9. The silicon wafer 9 has two sides, and if the silicon wafer 9 is placed horizontally, the surface image of the silicon wafer 9 may be the upper surface image or the lower surface image of the silicon wafer 9.
The Fourier transform module is used for carrying out Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer. The function formula of the fourier transform may be referred to in the above corresponding description, and will not be described herein.
The low-frequency signal removing module is used for removing the low-frequency signals in the spectrogram. In one specific application example, the low frequency signal removal module may include a circular area generation module and a spray module. The circular region generation module is used for generating a circular region with the radius r by taking the center of the frequency domain image as the circle center. The spraying module sprays the round area to enable the gray value to be 0. The farther the distance from the center point of the frequency domain image is, the higher the corresponding frequency is, and the middle and low frequency parts can be approximately included by adjusting the gray value in the circular area to 0, so that the purpose of removing the low frequency signals is achieved. The r value can be selected according to actual conditions.
And the inverse Fourier transform module is used for inversely Fourier transforming the spectrogram without the low-frequency signal into a return space domain to obtain a transformed image. The function formula of the inverse fourier transform may be referred to the corresponding description above, and will not be described herein.
The potential defect area generating module is used for threshold segmentation of the transformed image in the airspace, and extracting a bright area to obtain a potential defect area. If the bright area is a whole, the potential defect area generating module further performs the process of disconnecting the connected area on the bright area to obtain discrete potential defect areas.
The defect judging module is used for judging whether the potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region. In one specific example of an application, the defect determination module may include a comparison module and a controller. The comparison module is used for comparing the area, the perimeter, the length, the width and the density of each potential defect area with the upper limit value and the lower limit value of the corresponding first set range value and the upper limit value and the lower limit value of the corresponding second set range value respectively. The specific comparison process can be referred to the corresponding description above, and will not be repeated here. The controller is used for generating a silicon falling region signal when any one or more of the area, the perimeter, the length, the width and the density of the potential defect region are within a corresponding first set range value, namely judging that the potential defect region is a silicon falling region. The controller is further configured to generate a dirty region signal when any one or more of an area, a perimeter, a length, a width, and a density of the potentially defective region is within a corresponding second set range value, i.e., determine that the potentially defective region is a dirty region.
In order to realize the functions of the silicon wafer image acquisition module, the silicon wafer image acquisition module can acquire the surface image of the silicon wafer, and in a specific application example, the silicon wafer image acquisition module can comprise a transmission module, a photographing module, an extraction module and an image generation module. The transfer module is used for transferring the silicon wafer 9 to a set shooting area. The transfer module may include a transfer belt to transfer the silicon wafer 9 to the set photographing region by the transfer belt. The photographing module is used for photographing the set photographing area to obtain a first image containing the surface of the silicon wafer 9. The photographing module may include a camera 4, and the camera 4 may be an area array CCD camera to photograph a set photographing region through the camera 4. The extraction module is used for extracting the surface area of the silicon wafer in the first image. The image generation module is used for generating a silicon wafer surface image according to the silicon wafer surface area.
In order to implement the function of the extraction module, the extraction module may extract the surface area of the silicon wafer in the first image, and in a specific application example, the extraction module may include a threshold segmentation module, a function filling module, an open operation module, and a clipping module. The threshold segmentation module is used for threshold segmentation of the first image to obtain a bright area. The function filling module is used for filling the bright area by using a filling function. The open operation module is used for carrying out open operation on the filled bright region to obtain a silicon wafer detection region. The silicon wafer detection area comprises a silicon wafer surface area. The open operation module can open the filled bright area with a rectangle with the length and the width of a multiplied by b in the horizontal direction so as to remove the area of the conveyor belt and noise points, and a/b is more than or equal to 10. The cutting module is used for cutting the silicon wafer detection area to obtain the silicon wafer surface area. The silicon wafer detection area is cut, so that the silicon wafer surface area can be extracted from the silicon wafer detection area, the later image calculation amount can be reduced, and the image of other areas can be prevented from being interfered.
As shown in fig. 4, the aforementioned silicon wafer surface defect visual inspection device may further include a motor, a system controller, a light source controller 3, an encoder, a photoelectric sensor 8, and a light source 6. The motor is used for providing power for the transmission module to transmit the silicon wafer 9 to the set shooting area. The transfer module may include a transfer belt to transfer the silicon wafer 9 to the set photographing region by the transfer belt. The motor is used for driving the conveyor belt to move. The encoder may be a digital encoder, the encoder being adapted to be coupled to the motor to generate the first signal when the motor is started. The photosensor 8 is configured to generate a second signal when it is detected that the silicon wafer 9 enters the set photographing region. The light source 6 is used to provide illumination for photographing by the photographing module. The light source 6 may be a uniform highlight bar light. The light source controller 3 may be a microprocessor or a PLC or the like. The light source controller 3 is configured to control the light source 6 to be turned on for a set time according to the second signal. The system controller may be the industrial personal computer 1 or the like. The system controller is used for controlling the photographing module to photograph according to the first signal and the second signal. Specifically, as shown in fig. 3, the motion of the conveyor belt is transmitted by a motor, the motor is connected with a digital encoder, when the conveyor belt runs, the digital encoder sends a real-time first signal1 to a system controller, when a silicon wafer 9 enters a set shooting area under the drive of the conveyor belt, a photoelectric sensor 8 is triggered, the photoelectric sensor 8 sends a second signal2 to the system controller and a light source controller 3, and the light source controller 3 sends a control instruction to turn on the light source 6 for a period of highlighting after receiving the second signal2. Under the condition that the system controller receives the first signal1 and the second signal2 simultaneously, the system controller sends a shooting control instruction delay signal to control the shooting module to shoot the silicon wafer 9 of the set shooting area.
The second signal2 is generated in the following manner: a photoelectric sensor 8 is arranged below the conveyor belt, when a silicon wafer 9 reaches a set shooting area under the drive of the conveyor belt, a light beam of the photoelectric sensor 8 can be blocked, the photoelectric sensor 8 sends out a high-level signal, the high-level signal is transmitted into a terminal for data processing, and a system generates a second signal2 according to the high-level signal.
What needs to be explained here is: when the photoelectric sensor 8 does not detect the silicon wafer 9 in the set shooting area, the light source 6 and the camera 4 are in a standby state, and the silicon wafer 9 is judged after the placing position is adjusted.
The aforementioned silicon wafer surface defect visual inspection device further comprises a mechanical module 7, an industrial personal computer 1 and an electrical cabinet 2, wherein the camera 4 is an area array camera 4, and the number of the area array camera 4, the lens 5 and the light source 6 can be 2 and corresponds to one another. Wherein, the camera 4 is an 8K pixel black-and-white CCD, the lens 5 is a high-definition low-distortion 40mm focal length lens, the light source 6 is a uniform high-brightness tunnel light, and the light source controller 3 is a quick response trigger controller.
The front optical module is additionally arranged above the automatic feeding and discharging reserved station, and the back optical module is additionally arranged below the automatic feeding and discharging reserved conveyor belt gap, so that the conveyor belt gap is required to be ensured to be more than 20 mm; the reserved gap between the two groups of conveyor belts is not less than 10mm; the photoelectric sensors 8 are respectively arranged below the gaps of the conveyor belts, and trigger the cameras 4 to scan and photograph when products respectively reach corresponding detection stations, namely set photographing areas; detecting stains and silicon drops on the upper surface and the lower surface by acquiring images; the industrial personal computer 1 and the electrical cabinet 2 are separated from the optical module.
The detection station sets up the conveyer belt or the metalwork of shooting regional department promptly and need use black non-reflective material, and reflection of light can cause image quality to drop, and the precision drops.
The system of the visual detection device for the surface defects of the silicon wafers also stores the detection information of the silicon wafers in real time, displays the calculation result on a software interface, and transmits the discrimination data to a lower computer for silicon wafer screening. The method specifically comprises the following steps: the method comprises the steps of storing shot defect picture data in real time, obtaining defect data through calculation and classification, displaying statistical results on a system display interface, sending detection results to a rejecting device and an automatic feeding and discharging device, simultaneously storing silicon wafer detection information in real time by software, subdividing bad types of silicon wafers on an operation interface, and facilitating operators to check the number of various defects at any time.
The working principle and preferred embodiments of the present invention are described below.
The invention can respectively detect the defects of the front surface and the back surface of the silicon wafer by using the upper and lower sets of modules, triggers a camera to scan and photograph when products respectively reach corresponding detection stations, extracts the detection area of the silicon wafer by threshold segmentation, converts the fast Fourier transform into a frequency domain to shield a low-frequency signal, and finally returns to the spatial threshold segmentation and combines the characteristic extraction defect area of the region to detect stains and silicon drop areas of the upper and lower surfaces. The invention uses vision to inspect the silicon falling and dirt defects of the silicon wafer, detects and eliminates the defects of the silicon wafer on the premise of not influencing the productivity of the feeding and discharging machine, greatly improves the detection efficiency and precision, has simple and scientific structure, and has good application and popularization values.
What needs to be explained here is: under the condition of no conflict, the technical features related to the examples can be combined with each other according to actual situations by a person skilled in the art so as to achieve corresponding technical effects, and specific details of the combination situations are not described in detail herein.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above examples, and all technical solutions belonging to the concept of the present invention belong to the protection scope of the present invention. It should be noted that modifications and adaptations to the present invention may occur to one skilled in the art without departing from the principles of the present invention and are intended to be within the scope of the present invention.
Claims (10)
1. The visual detection method for the surface defects of the silicon wafer is characterized by comprising the following steps of:
acquiring a silicon wafer surface image;
performing Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer;
removing a low-frequency signal in the spectrogram;
fourier transform of the spectrogram without the low-frequency signal is reversed to a return space domain, so that a transformed image is obtained;
dividing the transformed image by a threshold on a airspace, and extracting a bright region to obtain a potential defect region;
judging whether each potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region.
2. The method for visual inspection of surface defects of a silicon wafer according to claim 1, wherein the step of obtaining the surface image of the silicon wafer comprises the following steps:
transmitting the silicon wafer to a set shooting area;
photographing the set photographing region to obtain a first image containing the surface of the silicon wafer;
extracting a silicon wafer surface area in a first image;
and generating a silicon wafer surface image according to the silicon wafer surface area.
3. The method for visual inspection of surface defects of silicon wafer according to claim 2, wherein the extracting the surface area of the silicon wafer in the first image specifically comprises:
dividing the first image threshold value into a brightness-taking area;
filling the bright areas with a filling function;
performing open operation on the filled bright region to obtain a silicon wafer detection region, wherein the silicon wafer detection region comprises a silicon wafer surface region;
cutting the silicon wafer detection area to obtain the silicon wafer surface area.
4. A method for visual inspection of surface defects of silicon wafers according to any one of claims 1 to 3 wherein the fourier transform function formula is:
and/or the number of the groups of groups,
the inverse fourier transform function is:
wherein x, y are the spatial variables of the image respectively, and u, v are the frequency variables of the image respectively.
5. A method for visual inspection of surface defects of a silicon wafer according to any one of claims 1 to 3, wherein the removing of low frequency signals in a spectrogram specifically comprises:
generating a circular region with the radius r by taking the center of the frequency domain image as the circle center;
and spraying the round area to enable the gray value to be 0.
6. A method for visual inspection of surface defects of silicon wafers according to any one of claims 1 to 3, wherein the step of determining whether each potentially defective region is a silicon drop and dirty region according to the characteristics of each potentially defective region comprises:
comparing the area, perimeter, length, width and density of each potential defect area with the upper limit value and the lower limit value of the corresponding first set range value and the upper limit value and the lower limit value of the corresponding second set range value respectively;
if any one or more of the area, the perimeter, the length, the width and the density of the potential defect area are within the corresponding first set range value, judging that the potential defect area is a silicon falling area;
and if any one or more of the area, the perimeter, the length, the width and the density of the potential defect area are within the corresponding second set range value, judging the potential defect area as a dirty area.
7. The visual detection device for the surface defects of the silicon wafer is characterized by comprising the following components:
the silicon wafer image acquisition module is used for acquiring a silicon wafer surface image;
the Fourier transform module is used for carrying out Fourier transform on the surface image of the silicon wafer to obtain a spectrogram of the silicon wafer;
the low-frequency signal removing module is used for removing the low-frequency signals in the spectrogram;
the inverse Fourier transform module is used for inversely Fourier transforming the spectrogram without the low-frequency signal into a return space domain to obtain a transformed image;
the potential defect area generating module is used for threshold segmentation of the transformed image in the airspace, extracting a bright area and obtaining a potential defect area;
the defect judging module is used for judging whether the potential defect area is a silicon drop and dirt area according to the characteristics of each potential defect area; wherein the features include any one or more of area, perimeter, length, width, and density of the potential defect region.
8. The visual inspection device of surface defects of a silicon wafer according to claim 7, wherein the silicon wafer image acquisition module comprises a transmission module, a photographing module, an extraction module and an image generation module;
the transmission module is used for transmitting the silicon wafer to a set shooting area;
the photographing module is used for photographing the set photographing area to obtain a first image containing the surface of the silicon wafer;
the extraction module is used for extracting the surface area of the silicon wafer in the first image;
the image generation module is used for generating a silicon wafer surface image according to the silicon wafer surface area.
9. The visual inspection device of surface defects of a silicon wafer according to claim 8, further comprising a motor, a system controller, a light source controller, an encoder, a photosensor and a light source;
the motor is used for providing power for the transmission module to transmit the silicon wafer to the set shooting area;
the encoder is used for being connected with the motor so as to generate a first signal when the motor is started;
the photoelectric sensor is used for generating a second signal when detecting that the silicon wafer enters the set shooting area;
the light source is used for providing illumination for photographing of the photographing module;
the light source controller is used for controlling the light source to be turned on for a set time according to the second signal;
the system controller is used for controlling the photographing module to photograph according to the first signal and the second signal.
10. The visual inspection device of surface defects of silicon chips according to claim 8 or 9, wherein the extraction module comprises a threshold segmentation module, a function filling module, an open operation module and a clipping module;
the threshold segmentation module is used for threshold segmentation and brightness extraction of the first image;
the function filling module is used for filling the bright area by using a filling function;
the on operation module is used for performing on operation on the filled bright region to obtain a silicon wafer detection region, wherein the silicon wafer detection region comprises a silicon wafer surface region;
the cutting module is used for cutting the silicon wafer detection area to obtain the silicon wafer surface area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211040991.7A CN117670777A (en) | 2022-08-29 | 2022-08-29 | Visual detection method and device for surface defects of silicon wafer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211040991.7A CN117670777A (en) | 2022-08-29 | 2022-08-29 | Visual detection method and device for surface defects of silicon wafer |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117670777A true CN117670777A (en) | 2024-03-08 |
Family
ID=90077511
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211040991.7A Pending CN117670777A (en) | 2022-08-29 | 2022-08-29 | Visual detection method and device for surface defects of silicon wafer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117670777A (en) |
-
2022
- 2022-08-29 CN CN202211040991.7A patent/CN117670777A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN208860761U (en) | A kind of industry detection apparatus with floor light | |
| JP7026309B2 (en) | Optical visual inspection device and optical visual inspection system using it | |
| CN107402216B (en) | Film-coated product detection system and method | |
| US10438340B2 (en) | Automatic optical inspection system and operating method thereof | |
| EP2316127B1 (en) | Method and system for detecting micro-cracks in wafers | |
| CN109932369B (en) | Method and device for detecting special-shaped display panel | |
| CN112394064A (en) | Point-line measuring method for screen defect detection | |
| KR102000906B1 (en) | Appearance vision inspection system for ferrite part | |
| CN111551559A (en) | LCD (liquid Crystal display) liquid crystal screen defect detection method based on multi-view vision system | |
| Abdelhedi et al. | Design of automatic vision-based inspection system for monitoring in an olive oil bottling line | |
| CN114529510B (en) | Automatic detection and classification method for cathode copper on-line quality | |
| CN114092375A (en) | Automatic detection system and method for printing defects of packaging bag cover | |
| CN113030095A (en) | Polaroid appearance defect detecting system | |
| KR102000907B1 (en) | Appearance vision inspection method for ferrite part | |
| CN114820439A (en) | PCB bare board defect detection system and method based on AOI | |
| CN117670777A (en) | Visual detection method and device for surface defects of silicon wafer | |
| CN114257736A (en) | Self-adaptive shooting method for workpieces | |
| KR102241989B1 (en) | Semiconductor inspecting method, semiconductor inspecting apparatus and semiconductor manufacturing method | |
| CN210102906U (en) | Automatic identification grabbing device of miniaturized electric capacity | |
| CN217059974U (en) | Fixed fretwork pattern thin metal product quality on-line measuring device | |
| CN116087104A (en) | Scanning system and method for line scanning micro-distance camera | |
| CN113953208B (en) | Full-automatic sorting device and method for electronic components | |
| CN114527131A (en) | Online detection device and detection method for internal and external defects of raw material silicon wafer | |
| KR20200055208A (en) | Apparatus and method for inspecting glass substrate | |
| CN117686512A (en) | Visual detection method and device for silicon wafer chamfering edge breakage |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |