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WO2011114449A1 - Procédé et dispositif d'inspection de grilles à transistors en couches minces (tft) - Google Patents

Procédé et dispositif d'inspection de grilles à transistors en couches minces (tft) Download PDF

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Publication number
WO2011114449A1
WO2011114449A1 PCT/JP2010/054523 JP2010054523W WO2011114449A1 WO 2011114449 A1 WO2011114449 A1 WO 2011114449A1 JP 2010054523 W JP2010054523 W JP 2010054523W WO 2011114449 A1 WO2011114449 A1 WO 2011114449A1
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Prior art keywords
shape
registered
defect
shapes
target shape
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English (en)
Japanese (ja)
Inventor
正道 永井
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Shimadzu Corp
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Shimadzu Corp
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Priority to JP2012505357A priority Critical patent/JP5408333B2/ja
Priority to CN201080065328.1A priority patent/CN102803940B/zh
Priority to PCT/JP2010/054523 priority patent/WO2011114449A1/fr
Publication of WO2011114449A1 publication Critical patent/WO2011114449A1/fr
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    • G—PHYSICS
    • G02—OPTICS
    • G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
    • G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
    • G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour 
    • G02F1/13—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour  based on liquid crystals, e.g. single liquid crystal display cells
    • G02F1/133—Constructional arrangements; Operation of liquid crystal cells; Circuit arrangements
    • G02F1/136—Liquid crystal cells structurally associated with a semi-conducting layer or substrate, e.g. cells forming part of an integrated circuit
    • G02F1/1362—Active matrix addressed cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/22—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material
    • G01N23/225—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion
    • G01N23/2255—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion using incident ion beams, e.g. proton beams
    • G—PHYSICS
    • G02—OPTICS
    • G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
    • G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
    • G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour 
    • G02F1/13—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour  based on liquid crystals, e.g. single liquid crystal display cells
    • G02F1/133—Constructional arrangements; Operation of liquid crystal cells; Circuit arrangements
    • G02F1/136—Liquid crystal cells structurally associated with a semi-conducting layer or substrate, e.g. cells forming part of an integrated circuit
    • G02F1/1362—Active matrix addressed cells
    • G02F1/136254—Checking; Testing

Definitions

  • the present invention relates to a TFT array inspection for inspecting an array of a TFT substrate such as a liquid crystal substrate, and more particularly to data processing of detection intensity used for detecting a defect in the TFT array.
  • an optical image obtained by optical imaging or a charged beam such as an electron beam or an ion beam is used as an image obtained by imaging a substrate such as a liquid crystal substrate.
  • a scanning image obtained by two-dimensionally scanning the substrate on the substrate can be used.
  • Patent Documents 1 and 2 In the manufacturing process of the TFT array substrate used in the TFT display device, an inspection is performed to check whether the manufactured TFT array substrate is driven correctly (Patent Documents 1 and 2).
  • an inspection signal is applied to an array of substrates to be inspected to bring the array into a predetermined potential state, and the substrate is scanned by two-dimensionally irradiating a charged beam such as an electron beam or an ion beam.
  • An array inspection apparatus that inspects an array of TFTs based on a scanning image obtained is known.
  • TFT array inspection for example, secondary electrons emitted by irradiation with an electron beam are converted into an analog signal by a photomultiplier or the like and detected, and an array defect is determined based on the signal intensity of the detection signal.
  • the array and pixels of the TFT substrate are formed correspondingly, and a specific pixel can be driven by applying a drive signal to the array.
  • a drive signal of a predetermined pattern is applied to the array to drive each pixel of the panel formed in the substrate with a predetermined pattern, and these pixels are irradiated with an electron beam and emitted from the irradiation point. Secondary electrons detected. A detection signal is acquired from each pixel in the panel by performing this electron beam irradiation in the panel.
  • each pixel is irradiated with, for example, 4 ⁇ 4 points or 4 ⁇ 3 points of a charged beam, and the irradiation point is set as a sampling point.
  • the signal intensity for detecting the defect of the array corresponding to the pixel is calculated using the detected signal.
  • FIG. 14 is a schematic diagram for explaining a conventional sampling example.
  • a total of 16 charged beams of 4 ⁇ 4 points are irradiated to one pixel, and each irradiation point is set as a sampling point, and a detection signal detected at each sampling point is used to detect a defect.
  • the detection signal is acquired.
  • a voltage pattern inspection signal is applied to each pixel by generating different potentials between adjacent pixels.
  • the signal intensity for defect detection is calculated from the detection signal of 4 ⁇ 4 points or 4 ⁇ 3 sampling points in the pixel, and this signal intensity is compared with a predetermined threshold value.
  • detection signals are acquired for a plurality of sampling points such as 4 ⁇ 4 points or 4 ⁇ 3 points.
  • Defect determination is performed in units of pixels. By detecting a defective pixel, it is possible to detect that there is a defect such as a short circuit or an open in the array portion that drives the pixel and perform an array inspection.
  • the determination of the defect type of the array can be changed by changing the voltage pattern of each pixel on the panel.
  • the voltage pattern of each pixel can be changed, for example, by changing the voltage pattern applied to the vertical or horizontal array.
  • Defect determination in units of pixels is performed by calculating the signal intensity for defect determination based on a plurality of detection signals detected at the sampling points of each pixel, and the threshold for defect determination in which this signal intensity is determined in advance. It is done by comparing with the value.
  • the detection signal detected at the sampling point of each pixel may contain noise. This noise component shifts the signal intensity of the detection signal from the original value. For this reason, if defect determination is performed based on the signal strength of the detection signal including noise, there is a risk of erroneous detection such as determining a normal pixel as a defective pixel or determining a defective pixel as a normal pixel.
  • an object of the present invention is to solve the above-described problems and to perform an array inspection by detecting defective pixels without being affected by noise added to a detection signal.
  • the inventors of the present application show that a defect shape peculiar to the defect type caused by the defect and a noise shape due to noise appear in the signal image obtained by scanning the charged beam on the panel. It was found that they can be distinguished by their shapes.
  • the present invention detects a defect shape by distinguishing it from a noise shape from shapes appearing in a signal image, and detects the defect pixel and an array corresponding to the defect pixel by detecting the defect shape.
  • the array is inspected by detecting defects.
  • the present invention applies an inspection signal of a predetermined voltage to a panel of a TFT substrate to drive the array, scans the panel by irradiating a charged beam, and based on a detection signal detected by the charged beam scanning, the TFT
  • This is a TFT array inspection for inspecting an array of substrates, and can be an aspect of an array inspection method and an aspect of an array inspection apparatus.
  • the array inspection method includes a detection step of detecting a signal intensity at a sampling point on a panel by irradiation with a charged beam, and binarizing the signal intensity of the sampling point detected in the detection step to obtain a binary image.
  • the binarization step to be obtained and the shape included in the binarized image obtained in the binarization step are set as the shape to be collated, and the collation is performed by comparing the shape of the collation target shape with the registered shape registered in advance.
  • Discriminator Preparative provided to detect the array corresponding to the defect and determine pixels in the defect determination process as a defect array.
  • the aspect of the array inspection apparatus of the present invention includes a detection unit that detects the signal intensity of a sampling point on a panel by irradiation of a charged beam, and a binarized image obtained by binarizing the signal intensity of the sampling point detected in the detection process.
  • the binarization unit to be obtained and the shape included in the binarized image obtained by the binarization unit are set as the shape to be collated, and the collation is performed by comparing the shape of the collation target shape with the registered shape registered in advance.
  • an electron beam is used as a charged beam, the electron beam is irradiated onto the panel, secondary electrons emitted from a sampling point on the panel are detected, and a detection signal of the secondary electron is detected.
  • Detect signal strength The signal strength obtained in the detection process varies depending on the voltage of the sampling point on the panel, and if the pixel is defective due to an array defect, the signal strength obtained at the sampling point on this pixel is normal pixel. Therefore, the normal pixel and the defective pixel are discriminated based on the signal intensity.
  • the binarization step and the binarization unit binarize the signal by comparing the signal strength at the sampling point with a predetermined threshold value and associating the binary value with the position corresponding to the sampling point according to the comparison result. Form an image.
  • the signal intensity obtained in the detection step and the detection unit has an intensity distribution corresponding to each state in the normal pixel and the defective pixel, and the signal intensity includes variations. For this reason, when a signal image is formed with this signal intensity, the shape changes due to variations in the signal intensity, so the shape cannot be specified, and it is difficult to distinguish between normal and defective pixels based on the shape. Become. Therefore, in the present invention, by binarizing the signal intensity of the detection signal, it is possible to avoid the indefinite shape due to variations in signal intensity, and to distinguish between a normal pixel and a defective pixel based on the shape.
  • the collation process and the collation device have a plurality of registered shapes, and compare the shape with the shape to be collated for each registered shape selected from the plurality of registered shapes.
  • the shape due to the defect appearing on the signal image differs depending on the type of defect and the position of the defect on the pixel, and the shape can be obtained in advance.
  • the shape due to this defect is obtained in advance and prepared as a registered shape.
  • the registered shape is binarized data, and is compared with the target shape of the binarized image obtained in the binarization process.
  • a selection process for selecting a registered shape from a plurality of registered shapes and a shape comparison process for comparing the shape of the registered shape selected in this selection process with the matching target shape. The process is repeated until the defect is determined as a defect.
  • the collation between the shape to be collated and the registered shape can be performed by binarized image data processing, and various processing modes can be used.
  • the image is superimposed on the data while moving the window with respect to the binarized image, and whether or not the data of the binarized image in this window matches the shape of the window.
  • Data processing for discrimination data processing for discrimination by passing the binary image data through a matching filter corresponding to the registered shape, a square matrix corresponding to the matching target shape and a square matrix corresponding to the registered shape are formed, Data processing that determines the product of the inverse matrix of the square matrix and the other square matrix and determines whether the product is a unit matrix can be used.
  • the present invention it is possible to detect a defective pixel and perform an array inspection without being affected by noise added to the detection signal.
  • FIG. 1 the flowchart for explaining the TFT array inspection step of the present invention in FIG. 1 and the steps until forming the signal image of the TFT array inspection of the present invention in FIG. 3 and 4 are flowcharts for explaining the binarized image of the TFT array inspection of the present invention
  • FIG. 5 is an explanatory diagram for explaining the binarized image of the TFT array inspection of the present invention. Description will be made with reference to FIGS. 6 and 7 for explaining the collation of the TFT array inspection of the present invention, and FIGS. 8 to 10 for explaining the collation processing example of the TFT array inspection of the present invention. .
  • the detection step (S1) for detecting the signal intensity at the sampling point on the panel by irradiation of the charged beam and the signal intensity at the sampling point detected in the detection step (S1) are binarized to 2
  • an inspection signal of a predetermined voltage is applied to the TFT substrate panel to drive the array, and scanning is performed by irradiating the panel with a charged beam, and a signal emitted from the irradiation point is detected by this charged beam scanning.
  • a secondary electron detection signal is detected.
  • the irradiation point of the charged beam corresponds to a sampling point for detecting the detection signal.
  • FIG. 2 (a) schematically shows sampling points.
  • the sampling point is a point where a detection signal is obtained, and corresponds to a point where a charged beam is irradiated on the panel (S2).
  • the position of the sampling point obtained by scanning is unknown in the positional relationship with the pixel formed on the panel, and if it remains as it is, the sampling point corresponding to the pixel cannot be specified, and the array defect can be detected. Can not.
  • the present invention obtains sampling points included in each pixel by associating the sampling points with the pixels of the panel in order to identify the relationship of the sampling points to the pixels.
  • the position of the sampling point is a position on the panel to be inspected, and this correspondence can be obtained from the position on the stage that supports the substrate on which the panel is formed and the irradiation position of the charged beam.
  • a predetermined voltage pattern in the pixel By forming a predetermined voltage pattern in the pixel, detecting the signal intensity between adjacent points, obtaining a boundary between the pixels based on the difference in signal intensity, and obtaining a sampling point correspondence relationship with the pixel based on the boundary. it can. Thereby, the correspondence between the sampling points and the pixels is obtained, and the pixels are identified in the detection data.
  • FIG. 2B shows the correspondence between sampling points and pixels (S3).
  • the detection data can form a signal image from its position and signal intensity.
  • this signal intensity has an intensity distribution corresponding to each state in the normal pixel and the defective pixel, and the signal intensity includes variations.
  • FIG. 2C schematically shows the relationship between the pixel and the signal image obtained from the signal intensity of the detection signal at the sampling point.
  • Binary image is formed from signal image by binarization process.
  • the binarization process is performed by comparing the signal intensity at the sampling point with a predetermined threshold value. Two values are determined according to the comparison result, and are associated with the positions corresponding to the sampling points. Thereby, a binarized image is formed.
  • FIG. 3 is a diagram for explaining binarization. Pixel defects appear in two ways in the pixel voltage. One aspect is when the defective pixel voltage appears at a lower voltage than the normal pixel voltage and is called a black defect. The other aspect is when the defective pixel voltage appears at a higher voltage than the normal pixel voltage, which is called a white defect.
  • Fig. 3 (a) shows binarization in the case of a black defect.
  • the defect strength max is determined in advance as a threshold value for binarizing the signal strength, the position of the signal image whose signal strength is lower than the defect strength max is associated with the defect, and the signal strength is the defect strength max. The signal image position higher than that is normally associated.
  • FIG. 3B shows binarization in the case of a white defect.
  • a defect intensity min ( ⁇ defect intensity max) is determined in advance as a threshold value for binarizing the signal intensity, and the position of the signal image whose signal intensity is higher than the defect intensity min is associated with the defect. The position of the signal image whose signal intensity is lower than the defect intensity min is normally associated.
  • FIG. 4 is a flowchart showing the black defect binarization procedure.
  • the signal intensity at the sampling point stored in S2 is read (S4a), and the read signal intensity is compared with the defect intensity max which is the threshold value of the black defect (S4b).
  • the signal intensity When the signal intensity is larger than the defect intensity max, the signal intensity is assumed to be a normal level, and a value representing a normal pixel is set at the position of the signal image corresponding to the sampling point (S4c). On the other hand, when the signal intensity is equal to or lower than the defect intensity max, the signal intensity is assumed to be the defect level, and a value representing the defective pixel is set at the position of the signal image corresponding to the sampling point. Values set in correspondence with normal pixels and defective pixels by binarization can be arbitrarily determined, for example, “0” and “1” (S4d).
  • FIG. 5 is a flowchart showing the binarization procedure for white defects.
  • the signal intensity at the sampling point stored in S2 is read (S4A), and the read signal intensity is compared with the defect intensity min, which is the threshold value for white defects (S4B).
  • the signal intensity is assumed to be the defect level, and a value representing the defective pixel is set at the position of the signal image corresponding to the sampling point (S4C).
  • the signal intensity is assumed to be a normal level, and a value representing a normal pixel is set at the position of the signal image corresponding to the sampling point.
  • Values set in correspondence with normal pixels and defective pixels by binarization can be arbitrarily determined, for example, “0” and “1” (S4D).
  • ⁇ S4A to S4D processing is performed on the signal intensity at all sampling points to form a binary signal image from the signal image (S4E).
  • the binarized data can be, for example, the value set in the binarization process and the position in the pixel (S5).
  • the collation target shape appearing in the binarized image is compared with the registered shape, and it is determined whether or not the registered shape is included in the collation target shape.
  • the shape to be collated is a shape formed by a set of points determined as a defect level by binarization processing, a shape formed by a set of points caused by defects, or a shape formed by a set of points due to noise Is included. If it is determined that the registered shape is included in the verification target shape, the pixel is determined as a defective pixel.
  • the shape in the binary image that appears in the defective pixel is obtained in advance.
  • This registered shape can be configured by recording data representing the shape when the collating process is performed by software, and by element arrangement representing the shape when the collating process is performed by hardware.
  • FIG. 6A and FIG. 7A show an example of collation.
  • FIG. 6A and FIG. 7A show an example of a binarized image of a black defect, and a white portion in the figure indicates a normal level and a black portion indicates a defect level. Since the defect level includes a portion due to a defect and a portion due to noise, the shape due to the defect is discriminated regardless of noise by collating the shape to be collated with the registered shape.
  • the pixels shown in FIGS. 6B to 6G show an example of matching between the matching target shape in the binarized image and the registered shape.
  • the registered shape is not included in the binarized image, so these pixels are normal. Discriminated as a pixel.
  • the pixel matching shown in FIG. 6F since it is determined that the registered shape is included in the binarized image, this pixel is determined as a defective pixel.
  • FIG. 7 shows an example in which after a defective pixel is detected by collation using one registered shape shown in FIG. 6, collation is performed using another registered shape.
  • the pixels shown in FIGS. 7B to 7G show an example of matching between the matching target shape in the binarized image and the registered shape.
  • the pixel matching shown in FIGS. 7B to 7E since the registered shape is not included in the binarized image, these pixels are determined as normal pixels. Since the registered shape of the pixel shown in FIG. 7 (f) is detected by the above-described pixel matching in FIG. 6 (f), the matching of the registered shape here is unnecessary and is omitted.
  • the collation shown in FIG. 7G it is determined that a registered shape is included in the binarized image, and this pixel is determined as a defective pixel.
  • the matching between the matching target shape and the registered shape can be performed by data processing of a binarized image, and various processing modes can be used.
  • FIG. 8 shows that the registered shape is a window and is superimposed on the data while moving the window with respect to the binarized image, and whether the data of the binarized image in this window matches the shape of the window. This shows an example of data processing for determining whether or not.
  • FIG. 8A shows an example of a binarized image of one pixel, where a white part in the figure indicates a normal level and a black part indicates a defect level.
  • FIG. 8B shows an example of a registered shape. In this collation example, the registration shape is used as a window to overlap the binarized image on the data, and collation is performed by determining whether the data of the binarized image in the window matches the shape of the window.
  • FIGS. 8C to 8H schematically show an example of superimposing the binarized image while sequentially shifting the windows. In the superposition shown in FIG. 8C and FIG. 8E to FIG.
  • the superimposition of the binarized image, the window, and the image can be performed by extracting data corresponding to the registered shape window from the binarized image of the pixels and comparing the binary values of the corresponding pixel positions. it can.
  • FIG. 9 shows an example of data processing that is determined by passing binarized image data through a matching filter corresponding to a registered shape.
  • the configuration of the matching filter shown in FIG. 9 forms a square matrix including a registered shape, and is configured by a delay element, an AND circuit, and an OR circuit corresponding to this square matrix.
  • delay elements are arranged between the values of the respective signals, and among the outputs of the respective delay elements, "1"
  • An AND circuit is arranged at the output of the delay element corresponding to ", and an AND circuit is arranged at the output of all AND circuits included in the registered shape. “1” is input to the other input terminal of the AND circuit.
  • square matrices P, Q, and R are formed for the binary signal of the registered shape. Elements other than the binary signal of the registered shape in the square matrix are indicated by “x”.
  • the AND circuits 200 to 203 are formed corresponding to “1” of the binarized signals of the square matrix P, and the outputs of the AND circuits 200 to 203 are input to the AND circuit 204.
  • AND circuits 300 to 303 are formed corresponding to “1” in the binarized signal of the square matrix Q, the outputs of the AND circuits 300 to 303 are input to the AND circuit 304, and the binary of the square matrix R AND circuits 400 to 403 are formed corresponding to “1” of the digitized signals, the outputs of the AND circuits 400 to 403 are input to the AND circuit 404, and the outputs are input to the AND circuits 204, 304, 404. To do.
  • an output is obtained from the OR circuit 500 when the registered shape is included in the shape to be matched.
  • a signal is output only from the AND circuit 304 corresponding to the square matrix Q, and an output is obtained from the OR circuit 500.
  • a matching filter corresponding to a predetermined registered shape is configured by hardware, and defect determination is performed by sequentially inputting a binary signal of a binary image of each pixel. It can be carried out.
  • FIG. 10A shows an example of forming a square matrix corresponding to the shape to be collated
  • FIG. 10B shows an example of forming a square matrix corresponding to the registered shape.
  • the corresponding square matrix is 3 rows ⁇ 3 columns.
  • the square matrix A1 corresponding to this registered shape is formed by adding [000] to the third column.
  • defect determination is performed including the case where the element array of “0” is “1” in addition to the element array of “1” included in the registered shape. Therefore, in addition to the square matrix A1, square matrices A2, A3, and A4 obtained by inverting the element array “0” to “1” are also prepared.
  • a 3 ⁇ 3 square matrix is formed from the shape to be verified.
  • 3 ⁇ 3 square matrices B1 to B6 are formed from a 4 ⁇ 4 square matrix B formed from the matching target shape.
  • [000] is added to the third column to form a square matrix.
  • the square matrices A1 to A4 formed from the registered shapes are regular matrices, the inverse matrices A1 ⁇ 1 to A4 ⁇ 1 are formed, respectively, and the products of the square matrices B1 to B6 formed from the matching target shapes are obtained.
  • FIG. 10C shows the product of the square matrix B and the inverse matrix A ⁇ 1 of the square matrix A.
  • the product of the square matrix B and the inverse matrix A ⁇ 1 is a unit matrix, it indicates that the square matrix B and the square matrix A match. This indicates that the verification target shape matches the registered shape.
  • the product of the square matrix B and the inverse matrix A3 ⁇ 1 of the square matrix A3 becomes the unit matrix E, which indicates that the registered shape is included in the matching target shape.
  • FIG. 11 is a diagram for explaining a configuration example of an inspection apparatus for performing the TFT array inspection of the present invention.
  • a TFT substrate such as a liquid crystal substrate is irradiated with an electron beam, secondary electrons emitted from the TFT substrate are detected, and a signal image is formed from a detection signal of the secondary electrons.
  • the example of a structure which performs defect detection based on this is shown.
  • the substrate to be inspected is not limited to a liquid crystal substrate, and substrate scanning is not limited to an electron beam, and a charged beam such as an ion beam can be used.
  • the detection signal depends on the charged beam to be irradiated and is not limited to secondary electrons.
  • a TFT array inspection apparatus 1 includes a stage 2 on which a TFT substrate 100 such as a liquid crystal substrate is placed and can be conveyed in the XY directions, and an electron gun 3 disposed above the stage 2 and spaced from the stage 2 And a detector 4 for detecting secondary electrons emitted from a pixel (not shown) of the panel 101 of the TFT substrate 100.
  • the electron gun 3 and the detector 4 can be provided with a plurality of sets.
  • the stage drive control unit 6 controls the driving of the stage 2, and the electron beam scanning control unit 5 controls the scanning direction of the electron beam on the TFT substrate 100 by controlling the irradiation direction of the electron beam irradiated by the electron gun 3.
  • the signal processing unit 10 performs signal processing on the detection signal of the secondary electrons detected by the detector 4 and sends it to the defect detection unit 11.
  • the defect detection unit 11 detects a pixel defect based on the detection signal sent from the signal processing unit 10, and detects a defective pixel and a corresponding defect array based on the detection position.
  • the pixels and the array are formed on the panel of the TFT substrate, and each pixel is driven by applying a voltage to the array. Therefore, the defect detection of the pixel corresponds to the array inspection for the pixel.
  • the driving operation of each of the electron beam scanning control unit 5, the stage drive control unit 6, the signal processing unit 10, and the defect detection unit 11 is controlled by the control unit 7.
  • the control unit 7 has a function of performing control including the entire operation of the TFT array inspection apparatus 1, and can be configured by a CPU that performs these controls and a memory that stores a program that controls the CPU.
  • the stage 2 mounts the TFT substrate 100 and is movable in the X-axis direction and the Y-axis direction by the stage drive control unit 6, and the electron beam irradiated from the electron gun G is an electron beam scanning control unit 5. Can be swung in the X-axis direction or the Y-axis direction.
  • the stage drive control unit 6 and the electron beam scanning control unit 5 can scan the electron beam on the TFT substrate 100 and irradiate each pixel on the panel 101 of the TFT substrate 100 by single or cooperative operation.
  • FIG. 12 is a diagram for explaining a configuration example of the defect detection unit 20, and shows a configuration in which defect detection is performed by data processing by software.
  • the detection unit 21 forms a signal image from the detection signal sent from the signal processing unit 10, and stores the signal strength and detection position of the obtained signal image in the storage unit 25 as detection data 25a.
  • the binarization unit 22 binarizes the signal intensity at the sampling points detected by the detection unit 21 to obtain a binarized image.
  • the obtained binarized image data is stored in the storage unit 25 as binarized data 25b.
  • the collation unit 23 uses the shape included in the binarized image obtained by the binarization unit 22 as a collation target shape, and collates the collation target shape with a registered shape registered in advance. . In this verification, the binarized data 25b and the registered shape data 25c are read from the storage unit 25.
  • the defect discriminating unit 24 discriminates whether or not the registered shape is included in the verification target shape based on the verification result of the verification unit 23, and when at least one registered shape is included in the verification target shape. A pixel including the matching target shape is determined as a defect. On the other hand, if none of the registered shapes of all registered shapes is included in the matching target shape, the pixel including the matching target shape is determined to be normal.
  • the defect determination unit 24 detects an array corresponding to a pixel determined as a defect as a defect array.
  • defect detection based on a comparison between a matching target shape and a registered shape is not limited to determination within one pixel.
  • Defect determination can be performed in a plurality of adjacent pixels.
  • FIG. 13 shows an example in which defect determination is performed on a plurality of adjacent pixels.
  • FIG. 13A an example in which a defect occurs between two pixels adjacent in the horizontal direction, an example in which a defect occurs between two pixels adjacent in the vertical direction, and a horizontal direction and a vertical direction An example in which a defect occurs between four adjacent pixels is shown, and a registered shape is detected at these locations.
  • FIG. 13B shows an example in which a registered shape is detected when a defect occurs between two adjacent pixels in the horizontal direction.
  • two pixels adjacent in the horizontal direction are set as a determination range, and defect detection is performed by detecting a registered shape in the same manner as described above for a verification target shape within the determination range.
  • FIG. 13C shows an example in which a registered shape is detected when a defect occurs between two pixels adjacent in the vertical direction.
  • two pixels adjacent in the vertical direction are used as a determination range, and defect detection is performed by detecting a registered shape in the same manner as described above for a verification target shape within the determination range.
  • FIG. 13D shows an example in which a registered shape is detected when a defect occurs between four pixels adjacent in the horizontal and vertical directions.
  • four pixels adjacent in the horizontal direction and the vertical direction are set as the determination range, and the defect detection is performed by detecting the registered shape in the same manner as described above with respect to the verification target shape within the determination range.
  • the TFT substrate can be a liquid crystal substrate or an organic EL, and can be applied to a film forming apparatus for forming various semiconductor substrates in addition to a film forming apparatus for forming a liquid crystal substrate or an organic EL.

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Abstract

L'invention concerne un agencement reposant sur un processus de détection qui, grâce à l'émission de faisceaux à charge, permet de détecter des intensités de signaux au niveau de certains points d'échantillonnage sur des panneaux ; sur un processus de binarisation pour binariser les intensités de signaux constatées aux points d'échantillonnage et qui ont été détectées lors du processus de détection, ce qui permet ainsi d'obtenir des images binarisées ; sur un processus de comparaison dans lequel des formes inhérentes aux images binarisées obtenues lors du processus de binarisation sont considérées comme des formes à comparer, et dans lequel lesdites formes à comparer sont comparées à des formes qui ont été enregistrées au préalable, ce qui permet de faire des comparaisons ; et sur un processus de détermination de défauts dans lequel il est déterminé, à partir des résultats du processus de comparaison, si des formes enregistrées font partie de formes comparées, dans lequel, si l'une au moins des formes enregistrées est incluse dans les formes comparées, il est déterminé que les pixels dont les formes comparées précitées font partie sont défectueux, et dans lequel, si aucune des formes enregistrées n'est incluse dans les formes comparées, il est déterminé que les pixels dont les formes comparées précitées font partie sont normaux. L'agencement, décrit dans la présente invention, permet d'effectuer une détection des défauts qui n'est pas affectée par les effets de bruit ajoutés aux signaux détectés, et procure ainsi une inspection des grilles.
PCT/JP2010/054523 2010-03-17 2010-03-17 Procédé et dispositif d'inspection de grilles à transistors en couches minces (tft) Ceased WO2011114449A1 (fr)

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JP2012505357A JP5408333B2 (ja) 2010-03-17 2010-03-17 Ｔｆｔアレイ検査方法およびｔｆｔアレイ検査装置
CN201080065328.1A CN102803940B (zh) 2010-03-17 2010-03-17 Tft阵列检查方法以及tft阵列检查装置
PCT/JP2010/054523 WO2011114449A1 (fr) 2010-03-17 2010-03-17 Procédé et dispositif d'inspection de grilles à transistors en couches minces (tft)

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CN107515481B (zh) 2017-08-29 2020-09-11 惠科股份有限公司 一种显示面板的检测方法和装置
JP7015001B2 (ja) * 2018-03-14 2022-02-02 オムロン株式会社 欠陥検査装置、欠陥検査方法、及びそのプログラム

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JP2005321308A (ja) * 2004-05-10 2005-11-17 Shimadzu Corp アレイ検査装置
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