CN113256630A - Light spot monitoring method and system, dark field defect detection equipment and storage medium - Google Patents
Light spot monitoring method and system, dark field defect detection equipment and storage medium Download PDFInfo
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Abstract
According to the light spot monitoring method and system, the dark field defect detection equipment and the storage medium, the light intensity characterization quantity of a plurality of rows of detection points on the light spot image is detected by acquiring the light spot image, wherein the detection points in the same row are arranged along the width direction of the light spot, and the detection points in each row are arranged along the length direction of the light spot; and obtaining a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection. Therefore, the invention realizes the quantification of the light spot deformation cause, is beneficial to assisting the subsequent light path adjustment and variable analysis, and improves the automation degree.
Description
Technical Field
The invention relates to the technical field of optical detection, in particular to a light spot monitoring method and system, dark field defect detection equipment and a storage medium.
Background
Dark field defect detection equipment is an automatic equipment for detecting defects of a product to be detected through light beams in a dark field environment, and in the using process, the directivity of the light beams or the position of light spots can shift along with the time, the shift can directly cause the quality of the light spots to be reduced, so that the overall sensitivity of the detection equipment is reduced, and the detection stability is also influenced. The spot needs to be monitored. In the prior art, a light spot quality analyzer is usually adopted to directly observe the change of the light spot form, and although whether the light spot (light source) needs to be adjusted can be judged through the change of the light spot form, the change of the light spot caused by which factor can not be analyzed; therefore, the existing spot monitoring is not automated to a high degree.
Disclosure of Invention
The invention provides a light spot monitoring method and system, dark field defect detection equipment and a storage medium, and aims to improve the automation degree of light spot monitoring.
According to a first aspect, an embodiment provides a method of spot monitoring, comprising:
acquiring a light spot image;
detecting light intensity characterization quantities of a plurality of rows of detection points on the light spot image, wherein the detection points in the same row are arranged along the width direction of the light spot, and the detection points in each row are arranged along the length direction of the light spot;
and obtaining a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection.
In the method for monitoring the light spot,
the light spot deformation comprises defocusing; the step of obtaining the quantitative index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof comprises the following steps: respectively calculating the dispersion degree of the light intensity characterization quantity of each row of detection points, and obtaining a defocusing quantization index according to each dispersion degree; alternatively, the first and second electrodes may be,
the spot deformation comprises uniformity; the step of obtaining the quantitative index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof comprises the following steps: obtaining peak value related parameters or mean value related parameters of the light intensity characteristic quantities of the detection points in each row according to the light intensity characteristic quantities of the detection points in each row, and obtaining a quantitative index of uniformity according to the maximum value and the minimum value of all the peak value related parameters or the mean value related parameters; alternatively, the first and second electrodes may be,
the spot deformation comprises deflection, and the deflection comprises translation and rotation; the step of obtaining the quantitative index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof comprises the following steps: determining the light spot central position of each row of detection points according to the light intensity characterization quantity of each row of detection points, and obtaining a translational quantitative index according to the light spot central position of each row; and performing straight line fitting on the central positions of the light spots in each row, and taking the inclination angle of the straight line obtained by fitting as a rotation quantization index.
In the method for monitoring the light spot,
the step of respectively calculating the discrete degree of the light intensity characterization quantity of each row of detection points comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and calculating to obtain the variance or standard deviation of each normal distribution curve, wherein the variance or standard deviation represents the dispersion degree;
the obtaining of the uniformity quantization index according to the maximum value and the minimum value of all the peak value correlation parameters or the average value correlation parameters includes: calculating to obtain a quantitative index of uniformity according to a formula 1- (Imax-Imin)/(Imax + Imin); wherein Imax is the maximum value of the peak value related parameter or the mean value related parameter, and Imin is the minimum value of the peak value related parameter or the mean value related parameter;
the step of determining the light spot center position of each row of detection points according to the light intensity characterization quantity of each row of detection points respectively comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and determining the position corresponding to the maximum light intensity characteristic quantity in the normal distribution curve as the central position of the light spot of the row in which the normal distribution curve is positioned; or summing the position coordinates after weighting the detection points in the same row and summing the light intensity characteristic quantities of the detection points in the same row respectively, and dividing the sum of the position coordinates after weighting the light intensity characteristic quantities by the sum of the light intensity characteristic quantities to obtain the coordinates of the light spot center positions of the detection points in the row, thereby obtaining the light spot center position of each row of the detection points; or, determining the light spot edge corresponding to each row of detection points according to the light intensity characterization quantity of each row of detection points, and determining the light spot center position according to the light spot edge.
The light spot monitoring method further comprises the following steps:
judging whether the quantization index of the light spot deformation exceeds a preset threshold value, if so, adjusting a light source for forming the light spot according to the quantization index of the light spot deformation; the height of the light source is adjusted according to the defocusing quantization index, the horizontal position and/or horizontal inclination angle of the light source is adjusted according to the deflection quantization index, and the pitching inclination angle of the light source is adjusted according to the uniformity quantization index.
According to a second aspect, an embodiment provides a speckle monitoring system, comprising:
the light intensity acquisition module is used for acquiring light intensity characterization quantities of a plurality of rows of detection points on the light spot image, wherein the detection points in the same row are arranged along the width direction of the light spot, and the detection points in each row are arranged along the length direction of the light spot;
and the processing module is used for obtaining a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection.
In the system for monitoring the light spot, the light spot is monitored,
the light spot deformation includes defocusing, and the processing module obtains the quantization index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, and comprises: respectively calculating the dispersion degree of the light intensity characterization quantity of each row of detection points, and obtaining a defocusing quantization index according to each dispersion degree; alternatively, the first and second electrodes may be,
the spot deformation comprises uniformity; the processing module obtains the quantization index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, and comprises the following steps: obtaining peak value related parameters or mean value related parameters of the light intensity characteristic quantities of the detection points in each row according to the light intensity characteristic quantities of the detection points in each row, and obtaining a quantitative index of uniformity according to the maximum value and the minimum value of all the peak value related parameters or the mean value related parameters; alternatively, the first and second electrodes may be,
the spot deformation comprises deflection, and the deflection comprises translation and rotation; the processing module obtains the quantization index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, and comprises the following steps: determining the light spot central position of each row of detection points according to the light intensity characterization quantity of each row of detection points, and obtaining a translational quantitative index according to the light spot central position of each row; and performing straight line fitting on the central positions of the light spots in each row, and taking the inclination angle of the straight line obtained by fitting as a rotation quantization index.
In the system for monitoring the light spot, the light spot is monitored,
the processing module respectively calculates the discrete degree of the light intensity characterization quantity of each row of detection points, and comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and calculating to obtain the variance or standard deviation of each normal distribution curve, wherein the variance or standard deviation represents the dispersion degree;
the processing module obtains the uniformity quantization index according to the maximum value and the minimum value of all the peak value related parameters or the average value related parameters, and the method comprises the following steps: calculating to obtain a quantitative index of uniformity according to a formula 1- (Imax-Imin)/(Imax + Imin); wherein Imax is the maximum value of the peak value related parameter or the mean value related parameter, and Imin is the minimum value of the peak value related parameter or the mean value related parameter;
the processing module determines the light spot center position of each row of detection points according to the light intensity characterization quantity of each row of detection points respectively, and the processing module comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and determining the position corresponding to the maximum light intensity characteristic quantity in the normal distribution curve as the central position of the light spot of the row in which the normal distribution curve is positioned; or summing the position coordinates after weighting the detection points in the same row and summing the light intensity characteristic quantities of the detection points in the same row respectively, and dividing the sum of the position coordinates after weighting the light intensity characteristic quantities by the sum of the light intensity characteristic quantities to obtain the coordinates of the light spot center positions of the detection points in the row, thereby obtaining the light spot center position of each row of the detection points; or, determining the light spot edge corresponding to each row of detection points according to the light intensity characterization quantity of each row of detection points, and determining the light spot center position according to the light spot edge.
In the light spot monitoring system, the processing module is further configured to:
judging whether the quantization index of the light spot deformation exceeds a preset threshold value, if so, adjusting a light source for forming the light spot according to the quantization index of the light spot deformation; the height of the light source is adjusted according to the defocusing quantization index, the horizontal position and/or horizontal inclination angle of the light source is adjusted according to the deflection quantization index, and the pitching inclination angle of the light source is adjusted according to the uniformity quantization index.
According to a third aspect, there is provided in an embodiment a dark field defect detection apparatus comprising:
the light source is used for emitting detection light beams to the product to be detected so as to form light spots on the product to be detected;
a spot monitoring system as described above.
According to a fourth aspect, an embodiment provides a computer readable storage medium having a program stored thereon, the program being executable by a processor to implement the method as described above.
According to the light spot monitoring method and system, the dark field defect detection device and the storage medium of the embodiment, the light intensity representation quantity of a plurality of rows of detection points on the light spot image is detected by acquiring the light spot image, wherein the detection points in the same row are arranged along the width direction of the light spot, and the detection points in each row are arranged along the length direction of the light spot; and obtaining a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection. Therefore, the invention realizes the quantification of the light spot deformation cause, is beneficial to assisting the subsequent light path adjustment and variable analysis, and improves the automation degree.
Drawings
Fig. 1 is a block diagram of a light spot monitoring system according to an embodiment of the present invention;
fig. 2 is a light spot image of an embodiment of the light spot monitoring system provided in the present invention;
FIG. 3 is a schematic diagram of a normal distribution curve of light intensity characterization quantities of each row of detection points obtained from a light spot image in the light spot monitoring system provided by the invention;
FIG. 4 is a flowchart of an embodiment of a method for monitoring a light spot according to the present invention;
FIG. 5 is a top view of a detection station in the dark field defect detection apparatus provided in the present invention;
fig. 6 is a schematic diagram of a normal distribution curve obtained by fitting Y-axis coordinates of a row of detection points with gray scale in the light spot monitoring system provided by the present invention;
fig. 7 is a schematic diagram of the center positions of light spots in each row and a fitting straight line thereof in the light spot monitoring system provided by the present invention;
fig. 8a is a schematic diagram of a normal distribution curve after gaussian fitting of first-column data in the light spot monitoring system provided by the present invention;
fig. 8b is a schematic diagram of a normal distribution curve after gaussian fitting of the second line of data in the light spot monitoring system according to the present invention;
fig. 8c is a schematic diagram of a normal distribution curve after gaussian fitting of the third column of data in the light spot monitoring system provided by the present invention;
fig. 8d is a schematic diagram of a normal distribution curve after gaussian fitting of the fourth column of data in the light spot monitoring system provided by the present invention;
fig. 8e is a schematic diagram of a normal distribution curve after gaussian fitting of fifth column data in the light spot monitoring system provided by the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings. Wherein like elements in different embodiments are numbered with like associated elements. In the following description, numerous details are set forth in order to provide a better understanding of the present application. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present application have not been shown or described in detail in order to avoid obscuring the core of the present application from excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they may be fully understood from the description in the specification and the general knowledge in the art.
Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the method descriptions may be transposed or transposed in order, as will be apparent to one of ordinary skill in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.
The numbering of the components as such, e.g., "first", "second", etc., is used herein only to distinguish the objects as described, and does not have any sequential or technical meaning. The term "connected" and "coupled" when used in this application, unless otherwise indicated, includes both direct and indirect connections (couplings).
As shown in fig. 1, the light spot monitoring system provided by the present invention includes: a light intensity obtaining module 20 and a processing module 30. The light intensity obtaining module is connected with the processing module 30.
The light intensity obtaining module 20 is configured to obtain light intensity characterization quantities of multiple rows of detection points on the light spot image, where, as shown in fig. 3, the detection points (black dots in the drawing) in the same row are arranged along a width direction (such as a vertical line direction in the drawing) of the light spot a, and the detection points b in each row are arranged along a length direction of the light spot a, and specifically, the detection points b in each row can be uniformly arranged along the length direction of the light spot a, so that the overall situation of the light spot a can be better reflected.
The light spot monitoring system further comprises an image obtaining module 10, and the image obtaining module 10 is connected to the processing module 30 through the light intensity obtaining module 20.
The light intensity obtaining module 20 can obtain the light intensity characterization quantities of the multiple rows of detecting points on the light spot image in multiple ways, which are described as follows:
in one mode, the image acquisition module 10 is used to acquire a spot image. The light spot can be the light spot of multiple shape, and in this embodiment, as shown in fig. 2, the light spot is the bar light spot, and the light that the light source was emergent forms the bar light spot after the light spot plastic promptly. The image acquisition module 10 may include an image acquisition device of a dark field defect detection apparatus, such as various types of industrial cameras and the like, and may also include a beam quality analyzer. The image acquisition module 10 outputs the light spot image to the light intensity acquisition module 20, the light intensity acquisition module 20 sequentially detects light intensity characteristic quantities of a plurality of detection points along the width direction respectively at different positions in the length direction of the light spot A according to the light spot image to obtain light intensity characteristic quantities of a plurality of rows of detection points b (10 rows of detection points are distributed along the length direction of the light spot A in the figure), a plurality of detection points are arranged on one row of detection points b, and the more the detection points are, the more the density of the detection points is, the better the effect of subsequent processing is; for example, the light intensity characteristic quantities of all the points of the light spot are detected in sequence along the width direction of the light spot, and the light intensity characteristic quantities of a row of points are obtained. The light intensity characterizing quantity is used for characterizing the light intensity (luminous intensity) of the light spot. In this embodiment, the light intensity characterization quantity at the detection point is the gray scale of the image at the detection point, and the gray scale is between 0 and 255 taking 256 gray scales of the display as an example. Of course, in some embodiments, the accuracy of the gray detection is high, and is not limited to 256 gray levels, and is not limited herein.
In another mode, the light intensity obtaining module 20 obtains the light intensity characterization quantities of the multiple rows of detection points on the light spot image directly from the outside. For example, after the image obtaining module 10 obtains the light spot image, the light intensity characterization quantities of the multiple rows of detection points on the light spot image are detected, and the specific implementation process and the implementation process of the light intensity obtaining module 20 in the above method are not described herein again. The image obtaining module 10 outputs the light intensity characterization quantities of the detection points in the plurality of rows on the light spot image to the light intensity obtaining module 20.
The processing module 30 is configured to obtain a quantitative index of spot deformation according to the position (for example, XY coordinates) of each detection point and the light intensity characterization quantity thereof, and output the quantitative index. The spot deformation includes at least one of defocus, uniformity and deflection, and may include, for example, three of defocus, uniformity and deflection, may include only one of defocus, uniformity and deflection, and may include only two of defocus, uniformity and deflection. The light intensity obtaining module 20 and the processing module 30 may employ devices with operation processing capability, such as a processor, a single chip, a Programmable Logic Controller (PLC), a programmable logic array (FPGA), and the like. The light intensity obtaining module 20 and the processing module 30 may be integrated in the same device or may belong to different devices.
The conventional mode of monitoring the light spot can only judge whether the form of the light spot changes, and as for how to adjust the light source after the form of the light spot changes, a technician is required to analyze, and the process is time-consuming and labor-consuming. The light spot monitoring system provided by the invention gives at least one quantitative index of defocusing, uniformity and deflection, so that a technician can know whether the light spot changes caused by defocusing or deflection, whether the uniformity meets the requirements and the like, thereby assisting in subsequent light path adjustment and variable analysis and improving the automation degree of light spot monitoring.
The following explains a specific process of performing the spot monitoring by the spot monitoring system, as shown in fig. 4, including the following steps:
table 1.
And 3, the processing module 30 obtains a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection.
For example, the spot deformation includes defocus, the processing module 30 calculates the discrete degree of the light intensity characterization quantity of each row of detection points, and obtains a defocus quantization index according to each discrete degree. The dispersion degree is represented by the variance or standard deviation of the light intensity characterization quantities of the detection points on the same column. Specifically, as shown In fig. 3 and fig. 6, the processing module 30 may perform gaussian fitting on the light intensity characterizations of each row of detection points, respectively, to obtain a normal distribution curve c of the light intensity characterizations of each row of detection points, where the normal distribution curve c reflects a relationship between positions (Y1, Y2, … …, Yn) of the detection points In the spot width direction and corresponding grayscales (I1, I2, … …, In) because the detection points on the row of this embodiment are distributed along the Y axis, and n is an integer greater than 2. The processing module 30 further calculates the variance or standard deviation σ of each normal distribution curve, and the variance or standard deviation σ represents the dispersion degree of the light intensity characterization quantity of each detection point on the column. The quantization index of defocus is obtained from each discrete degree, the discrete degrees are averaged, the average discrete degree is used as the quantization index of defocus, and higher discrete degree (higher variance or standard deviation σ) indicates more defocus.
When the light intensity characterization quantities of the detection points in each row are fitted in a polynomial fitting mode, calculating the half-peak width of a polynomial fitting curve, and when the half-peak width of the fitting curve is larger, the larger the discrete degree is, the more serious the defocusing is, wherein the half-peak width is the width of a line segment which is at the half position of the peak height of the fitting curve and is parallel to the peak bottom.
In a preferred embodiment, the polynomial equation is y = a x ^4+ b ^ x ^3+ c ^ x ^2+ d ^ x, and when the fitting is performed by using a polynomial method, the values of a, b, c and d are determined respectively, and then a polynomial fitting curve is determined. In a specific embodiment, as with the fitting by the gaussian formula, the polynomial fitting curve is used to describe the distribution of the light intensity characterizations of each row of detection points, so that the dispersion degree of the light intensity characterizations of each row of detection points can be determined according to the polynomial fitting curve.
It can be understood that, when the gaussian is used to fit the light intensity characterization quantities of each row of detection points, the dispersion degree of the light spots can also be evaluated through the half-peak width of the gaussian fitting curve, and since the manner of evaluating the dispersion degree through the half-peak width of the gaussian fitting curve is the same as the manner of evaluating the dispersion degree through the half-peak width of the polynomial fitting curve, details are not repeated here.
For example, the spot deformation includes uniformity, and the processing module 30 obtains a peak value related parameter or a mean value related parameter of the light intensity characteristic of each row of detection points according to the light intensity characteristic of each row of detection points. The peak correlation parameter is a parameter related to the peak value (maximum value in this embodiment), and may be the peak value itself, or may be a number proportional to the peak value, such as 1/2 peak value or 1/3 peak value. The mean value-related parameter is a parameter related to the mean value (mean value), and may be the mean value itself, or may be a number proportional to the mean value, such as 1/2 mean value, 1/3 mean value, or the like. The processing module 30 obtains a quantization index of uniformity according to the maximum value and the minimum value of all peak value related parameters or mean value related parameters, for example, the processing module 30 obtains the quantization index of uniformity by calculating according to the formula 1- (Imax-Imin)/(Imax + Imin); wherein Imax is the maximum value of the peak value correlation parameter or the mean value correlation parameter, and Imin is the minimum value of the peak value correlation parameter or the mean value correlation parameter. Specifically to the present embodiment, referring to table 1, the mean values of the five columns of grays are 106.43, 106.83, 107.15, 104.34 and 107.71, respectively, and then the maximum value Imax =107.71 and the minimum value Imin =104.34 of the five mean values, so that the quantization index (i.e., uniformity) =1- (Imax-Imin)/(Imax + Imin) =0.98 of the uniformity of the corresponding spot.
For example, spot deformation includes deflection, which includes translation and rotation, i.e., the spot may be offset horizontally, rotated, or both. The processing module 30 determines the spot center position of each row of detection points according to the light intensity characterization quantity of each row of detection points, and obtains a translational quantization index according to the spot center position of each row, and the specific modes can be various, and the following detailed descriptions are provided:
one is that: the processing module 30 determines the light spot edge corresponding to each row of detection points according to the light intensity characterization quantity of each row of detection points, and as described above, determines the rectangular area of the light spot through the gray level threshold, and the edge of the rectangular area is determined, so that the center position of the light spot can be determined.
The other is as follows: the processing module 30 represents the maximum light intensity (peak value) in the normal distribution curve c) The corresponding position mu is determined as the spot center position of the column in which the position mu is located, so that the spot center position of each column is obtained. The detection point with the maximum light intensity characteristic quantity is not necessarily the true spot center position of the row where the detection point is located, and the gray level of detection also has the precision problem or the interference problem, so the position mu corresponding to the maximum light intensity characteristic quantity in the normal distribution curve c is used as the spot center position of the row where the detection point is located, and the precision of the spot center position is improved. The spot center position can be expressed by Y-axis coordinates, and the coordinate mean value of the spot center positions of each column can be used as a quantitative index of translation. Specifically, taking the data in table 1 as an example, the processing module 30 performs fitting on the gray value Ii of each row of the detection points by using a preset gaussian function, so as to obtain a normal distribution curve c of the gray value Ii of each row of the detection points. Wherein the gaussian function is as follows: y = y0+ (A/(w sqrt (PI/2))). exp (-2 [ ((x-xc)/w) ^2), i.e. x-y, x-y, x-x, y, x, y, x, (i.e. x, sqrt (PI/2))). The
，y0Is a baseline, A is the area of the peak, w is the full width at half maximum of the peak, xcIs the peak position and pi is the circumferential ratio. The normal distribution curve c can be expressed by the above-mentioned Gaussian function, and thus y in the Gaussian function is determined0A, w and xcThe normal distribution curve is also determined. Therefore, the Ii and Yi values in the first column can be substituted into the gaussian function as the values of x and y, respectively, and after gaussian fitting, a fitted normal distribution curve (fig. 8 a) and a fitting result (see table below, and y in the table below) are obtained0A, w and xcSubstituting into a gaussian function results in a fitted normal distribution curve c),
wherein the central position of the light spot is u = xc=7.29, standard deviation σ = 2.83. Fitting a proper normal distribution curve according to a set of data subject to positive-too-distribution belongs to the prior art, and is not described herein.
In the same manner, the second column, after Gaussian fitting, yields a fitted normal distribution curve (FIG. 8 b) and fitting results (see Table below),
wherein the spot center position in the fitting result is u = xc=7.31, standard deviation σ = 2.85.
In the same manner, the third column, after Gaussian fitting, yields a fitted normal distribution curve (FIG. 8 c) and fitting results (see Table below),
the spot center position in the fitting result was u = xc=7.31, standard deviation σ = 2.81.
In the same manner, the fourth column, after Gaussian fitting, yields a fitted normal distribution curve (FIG. 8 d) and fitting results (see Table below),
wherein the spot center position in the fitting result is u = xc=7.28, standard deviation σ = 2.87.
In the same manner, the fifth column, after gaussian fitting, yields a fitted normal distribution curve (fig. 8 e) and fitting results (see table below),
wherein the spot center position in the fitting result is u = xc=7.19, standard deviation σ = 2.78.
The processing module 30 performs straight line fitting on the central position of each row of light spots to obtain a fitted straight line, as shown in fig. 7, the central position of each row of light spots is horizontal in an ideal state, and if the fitted straight line is an oblique line, it indicates that the light spots are rotationally deformed. Therefore, the processing module 30 calculates the inclination angle of the fitting straight line, and uses the inclination angle as the quantitative index of the rotation. Specifically, since the number of data columns in table 1 is small, five example data columns are added to the original five example data columns for convenience of description, so that the straight line fitting is performed on the spot center positions of the columns (as shown in table 2 below).
Table 2.
The straight line fitting formula is y = a + bx, where a, b are the fitting variables. The data of table 2 were fitted to give y =7.2747+ 0.0013 x.
a =7.2747, b =0.0013, and the data average Y (ave) =7.282, i.e., the Y-axis coordinate of the center position of the entire spot can be regarded as 7.282. The length (X axis) of the strip-shaped light spot is longer and usually exceeds the defect detection area, so the offset in the length direction can not be calculated, if the offset is calculated, the X axis coordinate of the central position of the whole light spot can be determined through the rectangular area of the light spot in the previous mode, and the X coordinate of the central position of the middle column can be used as the X coordinate of the central position of the whole light spot by uniformly distributing a plurality of columns of detection points in the length direction of the light spot.
The inclination corresponding to the fitted line is arctan (0.0013)/pi 180=0.074 °, i.e. the spot is rotated by 0.074 °, where pi = 3.1415.
The other method is as follows: the processing module 30 weights the position coordinates of a row of detection points by using the light intensity characteristic quantities of the detection points, sums the position coordinates weighted by the detection points in the same row and sums the light intensity characteristic quantities of the detection points in the same row respectively, and divides the sum of the position coordinates weighted by the light intensity characteristic quantities to obtain the coordinates of the light spot center positions of the row of detection points, so that the robustness is improved through weighting calculation. Specifically, as shown In table 3 below, the light intensity characterizing quantities at the detection points In each column are I1, I2, … …, In, represented by Ii, I ∈ [ 1, n ], the positions (Y-axis coordinates) of the points of the normal distribution curve obtained by gaussian fitting at the detection points In each column are Y1, Y2, … …, Yn, represented by Yi, I ∈ [ 1, n ], and the ordinate Y0 of the weighted spot center position = sum (Ii × Yi)/sum (Ii).
Table 3.
Similarly, the weighted Y-axis coordinates of the center positions of the respective light spots may be averaged, and the averaged Y-axis coordinates may be used as a quantization index of the light spot translation.
The processing module 30 performs straight line fitting on the central positions of the light spots to obtain a fitted straight line, as shown in fig. 7, the central positions of the light spots in each row are horizontal in an ideal state, and if the fitted straight line is an oblique line, it indicates that the light spots are rotationally deformed. Therefore, the processing module 30 calculates the inclination angle of the fitting straight line, and uses the inclination angle as the quantitative index of the rotation. Specifically, since the data columns in table 3 are fewer, the fitting is performed by adding five example data columns to the original five example data columns (as shown in table 4 below) for convenience of description.
Table 4.
The straight line fitting formula is y = a + bx, where a, b are the fitting variables. The data of table 4 were fitted to yield y =7.3166-0.0036 x.
a =7.3166, b = -0.0036, and the data average Y (ave) =7.296, that is, the Y-axis coordinate of the center position of the entire spot can be regarded as 7.296.
The inclination corresponding to the fitted straight line is arctan (0.0036)/pi 180= -0.206 °, i.e. the spot is rotated by-0.206 °, where pi = 3.1415.
After the quantitative index of the light spot deformation is obtained, the method can be applied to various applications. Some examples are listed below.
In some embodiments, the spot monitoring further comprises a display, and the processing module 30 is connected to the display. The processing module 30 outputs the quantitative index of the light spot deformation to the display, and the quantitative index is displayed by the display, so that technicians can conveniently master the current deformation condition of the light spot.
In some embodiments, the processing module 30 is further configured to determine whether the quantization index of the light spot deformation exceeds a preset threshold, for example, whether the quantization index of the defocusing exceeds a preset defocusing threshold, whether the quantization index of the uniformity exceeds a preset uniformity threshold, whether the quantization index of the translation exceeds a preset translation threshold, whether the quantization index of the rotation exceeds a preset rotation threshold, and the like, if one of the quantization indexes exceeds the preset rotation threshold, the processing module 30 outputs corresponding alarm information to prompt a technician that the corresponding quantization index exceeds a standard. The alarm information may be a sound, light, electrical, etc. signal.
In some embodiments, the processing module 30 is further configured to determine whether the quantization index of the light spot deformation exceeds a preset threshold, and if so, adjust the light source forming the light spot according to the quantization index of the light spot deformation. For example, if the processing module 30 determines that the quantization index of defocus exceeds the defocus threshold, the height of the light source is adjusted according to the quantization index of defocus. Specifically, defocus (defocus degree) is mainly evaluated by the standard deviation of the light intensity distribution, and the standard deviation of the distribution curve of the data is a σ value. Based on the original five columns of example data, supplementing five columns of example data facilitates fitting, as shown in table 5:
the processing module 30 performs a straight line fitting on the quantization index σ of defocus for each column, where the straight line fitting formula is y = a + bx, where a and b are fitting variables. After fitting, y =2.8227+0.0015x was obtained. a =2.8227, b = -0.0015, and data average value y (ave) =2.831, and the height of the light source can be adjusted according to the average value 2.831.
In table 1, the uniformity is 0.98, and if the uniformity threshold is 0.8, it indicates that the light source needs to be adjusted, in this embodiment, the processing module 30 adjusts the pitch angle of the light source according to the quantization index of the uniformity. Specifically, the light spots are not uniform, which may be the case that one end of each light spot is thick and the other end of each light spot is thin, for example, abnormal pitching of the light source may cause one end of each light spot to be thick, and the light intensity dispersion degree of each row of detection points in the thick portion is high, and the peak value related parameter and the average value related parameter are low. Therefore, the processing module 30 can adjust the pitch angle of the light source according to the discrete degree of the light intensity characterization quantity of each column, the peak value related parameter and/or the average value related parameter. The pitch angle of the light source is the angle between the light source and the X0Y plane. Taking the straight line y =2.8227+0.0015x fitted in table 5 as an example, if the inclination angle corresponding to the fitted straight line obtained by the processing module 30 according to the fitted straight line is arctan (0.0015)/pi × 180=0.086 °, the pitch inclination angle adjustment angle to the spot is 0.086 °. The processing module 30 can adjust the tilt angle of the light source according to the tilt angle.
The processing module 30 may further adjust a horizontal position and/or a horizontal tilt angle of the light source according to the quantitative indicator of the deflection, where the horizontal tilt angle is an included angle between the light source and the X0Z plane. Specifically, taking the data in table 2 as an example, the processing module 30 adjusts the horizontal inclination angle of the light spot to 0.074 degrees, and performs angle correction on the light spot according to the adjustment angle. Taking the data in table 4 as an example, the processing module 30 adjusts the horizontal tilt angle of the light spot to-0.206 degree, and performs angle correction on the light spot according to the adjustment angle.
Furthermore, the light spots can be periodically monitored and adjusted, namely, the steps shown in fig. 4 are periodically executed, and the light source is adjusted when the quantization index exceeds the threshold value, so that the light spots are ensured to meet the requirements all the time, and the stability of defect detection is favorably ensured. The steps shown in fig. 4 can be performed once to obtain defocus, uniformity, and deflection, and then adjusted after the determination; or, the step shown in fig. 4 may be performed once to obtain one of defocus, uniformity, and deflection, and then adjusted after the determination, and then the step shown in fig. 4 is performed once again to obtain another one of defocus, uniformity, and deflection, and then adjusted after the determination, and finally the step shown in fig. 4 is performed once again to obtain the last one of defocus, uniformity, and deflection, and then adjusted after the determination, so that the adjustment of defocus, uniformity, and deflection is completed. After the adjustment, the position of the edge of the light spot can be further determined through the light intensity, then the central position of the light spot is determined, and then the central position of the light spot is adjusted to a preset position and the like.
The light spot monitoring system provided by the invention can be applied to dark field defect detection equipment, in other words, the dark field defect detection equipment comprises a light source and the light spot monitoring system. The light source is used for emitting detection light beams to the product to be detected, so that light spots are formed on the product to be detected. The image acquisition module 10, such as a TDI camera (non-light beam quality analyzer), acquires a spot image for defect detection, and the processing module 30, such as a processor, performs detection analysis on the spot image for defect detection to obtain a detection result such as the presence or absence of a defect, a defect position, and the like. As for the dark field defect detecting device to monitor the light spot and adjust the light spot subsequently, the details are already described in the above embodiments, and are not described herein again.
According to the device, the system and the method, whether the light path needs to be readjusted or not is evaluated by monitoring the state of the light spot, and the automation degree of light spot monitoring is improved by quantifying, judging and adjusting the deformation cause of the light spot, so that the quality of the light spot of the whole system is kept at a higher level.
Those skilled in the art will appreciate that all or part of the functions of the various methods in the above embodiments may be implemented by hardware, or may be implemented by computer programs. When all or part of the functions of the above embodiments are implemented by a computer program, the program may be stored in a computer-readable storage medium, and the storage medium may include: a read only memory, a random access memory, a magnetic disk, an optical disk, a hard disk, etc., and the program is executed by a computer to realize the above functions. For example, the program may be stored in a memory of the device, and when the program in the memory is executed by the processor, all or part of the functions described above may be implemented. In addition, when all or part of the functions in the above embodiments are implemented by a computer program, the program may be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a removable hard disk, and may be downloaded or copied to a memory of a local device, or may be version-updated in a system of the local device, and when the program in the memory is executed by a processor, all or part of the functions in the above embodiments may be implemented.
The present invention has been described in terms of specific examples, which are provided to aid understanding of the invention and are not intended to be limiting. For a person skilled in the art to which the invention pertains, several simple deductions, modifications or substitutions may be made according to the idea of the invention.
Claims (8)
1. A method of spot monitoring, comprising:
acquiring a light spot image;
detecting light intensity characterization quantities of a plurality of rows of detection points on the light spot image, wherein the detection points in the same row are arranged along the width direction of the light spot, and the detection points in each row are arranged along the length direction of the light spot;
obtaining a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection; wherein the content of the first and second substances,
the light spot deformation comprises defocusing; the step of obtaining the quantitative index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof comprises the following steps:
respectively calculating the discrete degree of the light intensity characterization quantity of each row of detection points;
obtaining defocusing quantization indexes according to the discrete degrees; alternatively, the first and second electrodes may be,
the spot deformation comprises uniformity; the step of obtaining the quantitative index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof comprises the following steps:
obtaining the peak value related parameter or the mean value related parameter of the light intensity characteristic quantity of each row of detection points according to the light intensity characteristic quantity of each row of detection points,
obtaining a quantitative index of uniformity according to the maximum value and the minimum value of all peak value related parameters or average value related parameters; alternatively, the first and second electrodes may be,
the spot deformation comprises deflection, and the deflection comprises translation and rotation; the step of obtaining the quantitative index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof comprises the following steps:
determining the light spot center position of each row of detection points according to the light intensity characterization quantity of each row of detection points;
obtaining a translational quantization index according to the central position of each row of the light spots;
and performing straight line fitting on the central positions of the light spots in each row, and taking the inclination angle of the straight line obtained by fitting as a rotation quantization index.
2. The method of spot monitoring according to claim 1,
the step of respectively calculating the discrete degree of the light intensity characterization quantity of each row of detection points comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and calculating to obtain the variance or standard deviation of each normal distribution curve, wherein the variance or standard deviation represents the dispersion degree;
the obtaining of the uniformity quantization index according to the maximum value and the minimum value of all the peak value correlation parameters or the average value correlation parameters includes: calculating to obtain a quantitative index of uniformity according to a formula 1- (Imax-Imin)/(Imax + Imin); wherein Imax is the maximum value of the peak value related parameter or the mean value related parameter, and Imin is the minimum value of the peak value related parameter or the mean value related parameter;
the step of determining the light spot center position of each row of detection points according to the light intensity characterization quantity of each row of detection points respectively comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and determining the position corresponding to the maximum light intensity characteristic quantity in the normal distribution curve as the central position of the light spot of the row in which the normal distribution curve is positioned; or summing the position coordinates after weighting the detection points in the same row and summing the light intensity characteristic quantities of the detection points in the same row respectively, and dividing the sum of the position coordinates after weighting the light intensity characteristic quantities by the sum of the light intensity characteristic quantities to obtain the coordinates of the light spot center positions of the detection points in the row, thereby obtaining the light spot center position of each row of the detection points; or, determining the light spot edge corresponding to each row of detection points according to the light intensity characterization quantity of each row of detection points, and determining the light spot center position according to the light spot edge.
3. The method of spot monitoring according to claim 1, further comprising:
judging whether the quantization index of the light spot deformation exceeds a preset threshold value, if so, adjusting a light source for forming the light spot according to the quantization index of the light spot deformation; the height of the light source is adjusted according to the defocusing quantization index, the horizontal position and/or horizontal inclination angle of the light source is adjusted according to the deflection quantization index, and the pitching inclination angle of the light source is adjusted according to the uniformity quantization index.
4. A speckle monitoring system, comprising:
the light intensity acquisition module is used for acquiring a light spot image;
the detection module is used for detecting the light intensity characterization quantity of a plurality of rows of detection points on the light spot image, wherein the detection points in the same row are arranged along the width direction of the light spot, and the detection points in each row are arranged along the length direction of the light spot;
the processing module is used for obtaining a quantitative index of light spot deformation according to the position of each detection point and the light intensity characterization quantity of the detection point, wherein the light spot deformation comprises at least one of defocusing, uniformity and deflection; wherein the content of the first and second substances,
the light spot deformation includes defocusing, and the processing module obtains the quantization index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, and comprises: respectively calculating the dispersion degree of the light intensity characterization quantity of each row of detection points, and obtaining a defocusing quantization index according to each dispersion degree; alternatively, the first and second electrodes may be,
the spot deformation comprises uniformity; the processing module obtains the quantization index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, and comprises the following steps: obtaining peak value related parameters or mean value related parameters of the light intensity characteristic quantities of the detection points in each row according to the light intensity characteristic quantities of the detection points in each row, and obtaining a quantitative index of uniformity according to the maximum value and the minimum value of all the peak value related parameters or the mean value related parameters; alternatively, the first and second electrodes may be,
the spot deformation comprises deflection, and the deflection comprises translation and rotation; the processing module obtains the quantization index of the light spot deformation according to the position of each detection point and the light intensity characterization quantity thereof, and comprises the following steps: determining the light spot central position of each row of detection points according to the light intensity characterization quantity of each row of detection points, and obtaining a translational quantitative index according to the light spot central position of each row; and performing straight line fitting on the central positions of the light spots in each row, and taking the inclination angle of the straight line obtained by fitting as a rotation quantization index.
5. The spot monitoring system according to claim 4,
the processing module respectively calculates the discrete degree of the light intensity characterization quantity of each row of detection points, and comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and calculating to obtain the variance or standard deviation of each normal distribution curve, wherein the variance or standard deviation represents the dispersion degree;
the processing module obtains the uniformity quantization index according to the maximum value and the minimum value of all the peak value related parameters or the average value related parameters, and the method comprises the following steps: calculating to obtain a quantitative index of uniformity according to a formula 1- (Imax-Imin)/(Imax + Imin); wherein Imax is the maximum value of the peak value related parameter or the mean value related parameter, and Imin is the minimum value of the peak value related parameter or the mean value related parameter;
the processing module determines the light spot center position of each row of detection points according to the light intensity characterization quantity of each row of detection points respectively, and the processing module comprises the following steps: respectively carrying out Gaussian fitting on the light intensity characteristic quantities of each row of detection points to obtain a normal distribution curve of the light intensity characteristic quantities of each row of detection points, and determining the position corresponding to the maximum light intensity characteristic quantity in the normal distribution curve as the central position of the light spot of the row in which the normal distribution curve is positioned; or summing the position coordinates after weighting the detection points in the same row and summing the light intensity characteristic quantities of the detection points in the same row respectively, and dividing the sum of the position coordinates after weighting the light intensity characteristic quantities by the sum of the light intensity characteristic quantities to obtain the coordinates of the light spot center positions of the detection points in the row, thereby obtaining the light spot center position of each row of the detection points; or, determining the light spot edge corresponding to each row of detection points according to the light intensity characterization quantity of each row of detection points, and determining the light spot center position according to the light spot edge.
6. The spot monitoring system of claim 4, wherein the processing module is further configured to:
judging whether the quantization index of the light spot deformation exceeds a preset threshold value, if so, adjusting a light source for forming the light spot according to the quantization index of the light spot deformation; the height of the light source is adjusted according to the defocusing quantization index, the horizontal position and/or horizontal inclination angle of the light source is adjusted according to the deflection quantization index, and the pitching inclination angle of the light source is adjusted according to the uniformity quantization index.
7. A dark field defect detection apparatus, comprising:
the light source is used for emitting detection light beams to the product to be detected so as to form light spots on the product to be detected;
a spot monitoring system as claimed in claim 4, 5 or 6.
8. A computer-readable storage medium, characterized in that the medium has stored thereon a program which is executable by a processor to implement the method of claim 1, 2 or 3.
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