A method for interferometric detection of the flatness of a non-continuous surface of a semiconductor chuck

Abstract

The present invention relates to a method for interferometric detection of the flatness of a semiconductor chuck discontinuous surface. An interference image containing phase information of the semiconductor chuck discontinuous surface is collected by a single-wavelength laser plane interferometer, valid data points are screened out, and the wrapped phase of the discontinuous surface is calculated. The characteristic that the discrete binary phase data is close in distance in a three-dimensional coordinate system after being stacked is utilized, and a three-dimensional morphological method is used to complete the expansion and connection of the discrete binary phase. After the connected body containing the most data is screened out, inverse discretization and system error elimination are performed to complete the interferometric detection of the flatness of the semiconductor chuck discontinuous surface. The present invention solves the technical problem that phase resolution errors occur when the existing laser plane interferometer detects the flatness of the discontinuous surface, and the flatness of the discontinuous surface cannot be detected, and achieves the technical effect of large-scale, accurate and rapid detection of the flatness of the semiconductor chuck discontinuous surface.

Description

Technical Field

[0001] The invention belongs to the technical field of optical interference measurement, and in particular relates to a flatness interference detection method for a discontinuous surface of a semiconductor chuck. Background Art

[0002] With the development of the semiconductor industry, there are more and more components with non-continuous working surfaces, and the demand for flatness detection of non-continuous surfaces is also increasing. For example, vacuum chucks used to clamp wafers are widely used in lithography and detection equipment. In order to reduce the impact of dust on wafer clamping, vacuum chucks are usually designed with non-continuous surfaces, including needle-shaped and ring-shaped. The lower the flatness of the wafer after the vacuum chuck adsorbs the wafer, the more conducive it is to lithography and detection of the wafer. Therefore, it is necessary to use a technology that can efficiently detect non-continuous surfaces using a laser interferometer to detect the flatness of the vacuum chuck surface. The characteristic of a non-continuous surface is that there are no valid data points for interference detection between two surfaces with clear boundaries.

[0003] For laser interferometry flatness detection, the key is to extract the phase containing the relative height information of the object to be tested. The phase pheromone is calculated by inverse trigonometric functions, and the phase value is truncated between (-π, π), that is, the wrapped phase. To perform interferometry flatness detection on the non-continuous surface of the suction cup, it is necessary to unwrap the non-continuous surface phase.

[0004] In optical interferometry, phase unwrapping technology can accurately measure the phase change of light waves to obtain the three-dimensional shape information of the object's surface.

[0005] The current phase unwrapping methods are divided into two categories: route-related and route-independent. The current route-related phase unwrapping algorithms mostly use methods to identify phase mutation boundaries and phase rises between boundaries. When facing discontinuous surface phase unwrapping, they can only perform local continuous surface phase unwrapping. The phase will be truncated at the discontinuous boundary and the entire surface cannot be phase unwrapped. Route-independent phase unwrapping methods mostly use the least squares method, which is time-consuming and has limited accuracy.

[0006] Chinese patent CN115456991A discloses a discrete cosine unwrapping algorithm based on phase gradient weighted moving average correction, which calculates the weighted moving average of the phase gradient in the x-direction and the y-direction as the phase gradient correction value, corrects the phase gradient caused by noise and the phase gradient with a large difference from the true value, and provides a method that can accurately and quickly unfold the phase when there is a lot of noise in the wrapped phase. The discrete cosine unwrapping concept mentioned in the invention refers to a transformation method, not a discontinuous surface.

[0007] Chinese patent CN107202550A discloses a method of phase unwrapping based on the least squares method, which establishes a discrete Poisson equation on an M×N rectangular image through the least squares method, brings the first-order differences in four directions of the two-dimensional wrapped image after secondary shearing into the Poisson equation, and solves the Poisson equation by discrete cosine transform (DCT) to obtain the true phase Φ of the wrapped image. The measurement object is the phase of a continuous surface, and it is difficult to achieve phase unwrapping of a discontinuous surface.

[0008] Yang X, Hu H, Xue D, et al. Discontinuous phase unwrapping based on the minimization of Zernike gradient polynomial residual[J]. Optics Express, 2022, 30(26): 47992-48003. A method based on minimizing the Zernike gradient polynomial residual is proposed to estimate the segmentation error and correct the erroneous phase unwrapping results. This method can accurately obtain the segment height error under complex aberration forms and various occlusions, has reliable practicality, and completes the phase unwrapping of discontinuous surfaces. However, this method is only applicable to a small number of discontinuous surfaces and cannot complete the flatness detection of suction cups with a large number of discontinuous surfaces.

[0009] In summary, the existing technology is still unable to accurately and quickly complete the flatness detection of a suction cup with a large number of discontinuous surfaces. Summary of the invention

[0010] The technical problem to be solved by the present invention is to provide a method for interferometric detection of the flatness of the discontinuous surface of a semiconductor suction cup, which can accurately and quickly detect the flatness of the discontinuous surface of the semiconductor suction cup over a large range, and has the characteristics of high accuracy, strong stability, and a discontinuous surface phase unwrapping method that can simultaneously process a large number of discontinuous surfaces.

[0011] The present invention provides a method for interferometric detection of the flatness of a discontinuous surface of a semiconductor chuck, comprising the following steps:

[0012] S1: Screening valid data points; obtaining the interference image of the discontinuous surface of the semiconductor chuck by a single-wavelength laser plane interferometer, generating the phase data information to be processed by grayscale processing, and screening the valid data points by setting a threshold for the brightness change, retaining the screened valid data points, and establishing a binary valid data screening matrix for the valid data points;

[0013] S2: Discontinuous surface phase calculation: The wrapped phase of the valid data points is calculated by the nine-step averaging method;

[0014] S3: Data discretization and binarization: discretize the data calculated by the wrapped phase into three-dimensional space and binarize it to obtain a binarized three-dimensional matrix;

[0015] S4: Data stacking, morphological expansion and connection: stacking the binary three-dimensional matrix multiple times in a three-dimensional coordinate system, and performing three-dimensional morphological expansion and connection on the valid data points of the stacked binary three-dimensional matrix to form a number of connected bodies;

[0016] S5: Connected body screening and inverse discretization: The largest connected body among several connected bodies is screened out by the number of valid data points it contains, and inverse discretization is performed to obtain the initial unwrapped phase;

[0017] S6: System error elimination: taking the wrapped phase of the binarized effective data screening matrix established by the effective data points as a reference, the system phase error introduced in the data discrete binarization is calculated, and it is eliminated from the initial unwrapped phase to obtain the unwrapped phase;

[0018] S7: Reasonableness check and processing; the flatness of the chuck surface is obtained by unwrapping the phase, and the number of bright or dark fringes in the interference pattern of the laser interferometer is used as the standard for reasonableness check; when the result is reasonable, the flatness detection result obtained by unwrapping the phase is used as the flatness interference detection result of the non-continuous surface of the semiconductor chuck; when the data is unreasonable, the data is re-screened or the binary three-dimensional matrix is ​​corroded, the phase is re-unwrapped, and the flatness interference detection result of the non-continuous surface of the semiconductor chuck is recalculated.

[0019] The flatness interference detection method of the discontinuous surface of the semiconductor suction cup of the present invention is applied to a flatness detection system, and the flatness detection system is communicated with an electronic computer.

[0020] The unwrapped discontinuous surface of the present invention is any discontinuous surface where there are no valid data points for interference detection between two surfaces with clear boundaries.

[0021] Preferably, step S1 comprises the following steps:

[0022] Nine interference images with M×N pixels and a phase difference of π / 2 between each image and the previous image are obtained by a single-wavelength laser plane interferometer, and the phase data information to be processed is generated by grayscale processing, and the effective data points are screened by setting a threshold for the brightness change;

[0023] The brightness change calculation formula is as follows:

[0024] D(x,y)=max(I(x,y))-min(I(x,y)) (1),

[0025] Among them, (x, y) is the coordinate of the pixel point, I(x, y) is the brightness of the pixel point, and D(x, y) is the extreme value of the brightness change of the pixel point in the nine phase images;

[0026] The calculation formula of the binary effective data screening matrix is ​​as follows:

[0027]

[0028] Among them, e(x,y) is the binary screening matrix, and F is the brightness change screening threshold;

[0029] The effective data point screening calculation formula is as follows:

[0030] E i (x,y)=I i (x,y)·e(x,y),i=1,2,…,9 (3),

[0031] Among them, E i (x, y) is the brightness of the effective data point after screening, I i (x, y) is the brightness of the effective pixel after filtering.

[0032] Preferably, step S2 comprises the following steps:

[0033] The filtered data points were used through the nine-step averaging method to obtain the wrapped phase data;

[0034] The formula for calculating the package phase data is as follows:

[0035]

[0036] in, is the wrapped phase data, E i (x, y)i=1, 2, ..., 9 is the brightness of the effective data points after screening obtained in step S1.

[0037] Preferably, step S3 comprises the following steps:

[0038] The wrapped phase data is binarized and discretized to obtain a binarized phase matrix; the binarized phase matrix data is divided into l layers, that is, the height of each layer is 2π / l, binarized and discretized into a three-dimensional data space, the valid data points are 1, and the invalid data points are 0, to obtain a three-dimensional binarized matrix BW(x, y, z).

[0039] Preferably, step S4 comprises the following steps:

[0040] The binary discretized phase matrices are stacked to obtain a three-dimensional binary matrix BW1(x, y, z) and connected through morphological three-dimensional expansion to generate several connected bodies;

[0041] The calculation formula for generating several connected bodies is as follows:

[0042]

[0043] Among them, S is a spherical structure element, and its radius determines the connectivity of the two stacked binary matrices; the generation process of BW2 is to place S at the coordinate point (x, y, z) of BW1. When the intersection of S and BW1 here is not an empty set, BW2(x, y, z) = 1; when the intersection of S and BW1 here is an empty set, BW2(x, y, z) = 0.

[0044] Preferably, step S5 comprises the following steps:

[0045] The largest connected body is selected by the number of valid data points, and the initial unwrapped phase is obtained by inverse discretization operation; the number of valid data points is the number of valid data points;

[0046] The calculation formula of the largest connected body is as follows:

[0047]

[0048] Among them, BW3 is the largest connected body, |L i | is the number of valid data points;

[0049] The initial unwrapping phase calculation formula is as follows:

[0050]

[0051] in, is the initial unwrapped phase distribution obtained by inverse discretization operation.

[0052] Preferably, step S6 comprises the following steps:

[0053] The system error caused by the discretization operation is calculated and removed to obtain the unwrapped phase information. The calculation formula is as follows:

[0054]

[0055] in, is the systematic error generated by the discretization process in step S2, is the unwrapped phase distribution obtained after removing this systematic error.

[0056] Preferably, step S7 comprises the following steps:

[0057] Using the phase distribution obtained after removing the system error Calculate the surface shape H(x,y) and its PV value after eliminating the system error;

[0058] The formula for the surface shape after eliminating systematic errors is as follows:

[0059]

[0060] Among them, H(x, y) is the surface shape after eliminating systematic errors, is the unwrapped phase distribution obtained after removing this systematic error, and λ is the laser wavelength of the used laser interferometer;

[0061] The formula for calculating the PV value is:

[0062] PV = max(H(x, y)) - min(H(x, y)) (10),

[0063] Among them, H(x, y) is the surface shape after eliminating systematic errors;

[0064] Compare its PV with the numerical value M obtained by multiplying the number of interference fringes by 1 / 2 wavelength. When PV < M, then use H(x, y) as the interferometric detection result of the flatness of the discontinuous surface of the semiconductor chuck; when PV > M, re - perform the effective data screening process described in step S1, or perform erosion processing on the discrete binary phase data described in step S3, and re - perform phase unwrapping to complete the interferometric detection of the flatness of the discontinuous surface of the semiconductor chuck.

[0065] The present invention has the following technical effects:

[0066] 1. Use a single - wavelength laser plane interferometer to efficiently and accurately complete data acquisition of the discontinuous surface of the semiconductor chuck. Through the idea that the phase data at the phase mutation truncation of two layers after three - dimensional stacking of binary - discretized phases is close in distance, use three - dimensional morphological methods to simultaneously complete phase unwrapping of a large number of discontinuous surfaces, so as to obtain the three - dimensional shape information of the object surface with high efficiency and high precision. By eliminating systematic errors and performing rationality inspection and processing, realize accurate and rapid interferometric detection of the flatness of the discontinuous surface of the semiconductor chuck.

[0067] 2. Can simultaneously process the detection of a large number of discontinuous surfaces, can perform large - range accurate and rapid detection of the flatness of the discontinuous surface of the semiconductor chuck, and has the characteristics of high correct rate, strong stability, high detection precision, high detection efficiency, and large detection range. There is no need to splice measurement data during the detection process. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 is a flowchart of the method for interferometric detection of the flatness of the discontinuous surface of the semiconductor chuck proposed by the present invention;

[0069] Figure 2 are 9 interference images collected by the interferometer camera;

[0070] Figure 3 is the binary effective data screening matrix;

[0071] Figure 4 is the discontinuous surface wrapping phase calculated by the nine-step averaging method;

[0072] Figure 5 It is a three-dimensional binary matrix obtained by discrete binarization of data;

[0073] Figure 6 is the matrix obtained by stacking the binary discretized phase matrices;

[0074] Figure 7 is the initial unwrapped phase map;

[0075] Figure 8 It is the system phase error caused by the discretization operation;

[0076] Fig. 9 It is the flatness interference detection surface after eliminating the system error. DETAILED DESCRIPTION

[0077] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings.

[0078] The present invention uses a single-wavelength laser plane interferometer based on the interference principle to perform flatness interferometry on the discontinuous surface of a semiconductor chuck with a diameter of 298 mm, using a HeNe laser with a wavelength of 632.8 nm as a light source. The flatness interferometry detection method for the discontinuous surface of a semiconductor chuck, such as Figure 1 As shown, the specific steps include:

[0079] S1: Screen valid data points; obtain nine interference images of the discontinuous surface of the semiconductor chuck with M×N pixels and a phase difference of π / 2 between each image and the previous image by a single-wavelength laser plane interferometer, such as Figure 2 As shown, the phase data information to be processed is generated by grayscale processing, and the effective data points are screened by setting a threshold for the brightness change, and a binary effective data screening matrix is ​​established, as shown in Figure 3 As shown, the white data points represent 1 and the black data points represent 0;

[0080] The brightness change calculation formula is as follows:

[0081] D(x,y)=max(I(x,y))-min(i(x,y)) (1),

[0082] Among them, (x, y) is the coordinate of the pixel point, i(x, y) is the brightness of the pixel point, and D(x, y) is the extreme value of the brightness change of the pixel point in the nine phase images;

[0083] The calculation formula of the binary effective data screening matrix is ​​as follows:

[0084]

[0085] Among them, e(x,y) is the binary screening matrix, and F is the brightness change screening threshold;

[0086] The effective data point screening calculation formula is as follows:

[0087] E i (x,y)=I i (x,y)·e(x,y),i=1,2,…,9 (3),

[0088] Among them, E i (x, y) is the brightness of the effective data point after screening, I i (x, y) is the brightness of the effective pixel after filtering.

[0089] S2: Discontinuous surface phase calculation; the selected data points are used through the nine-step averaging method to obtain the wrapped phase data. The results are as follows Figure 4 As shown;

[0090] The formula for calculating the package phase data is as follows:

[0091]

[0092] in, is the wrapped phase data, E i (x, y)i=1, 2, ..., 9 is the brightness of the effective data points after screening obtained in step S1.

[0093] S3: Data discretization and binarization: discretize the data calculated by the wrapped phase into three-dimensional space and binarize it to obtain a binarized three-dimensional matrix;

[0094] The wrapped phase data is binarized to obtain a binarized phase matrix. The binarized phase matrix data is divided into l layers, i.e., each layer has a height of 2π / l, and is binarized and discretized into a three-dimensional data space, with valid data points being 1 and invalid data points being 0, to obtain a three-dimensional binarized matrix BW(x, y, z), as shown in Figure 5 As shown, black represents valid data point 1 and white represents invalid data point 0.

[0095] S4: Data stacking, morphological expansion and connection; stack the binary discretized phase matrix to obtain a three-dimensional binary matrix BW1 (x, y, z) and connect it through morphological three-dimensional expansion to generate several connected bodies;

[0096] The calculation formula for generating several connected bodies is as follows:

[0097]

[0098] Among them, S is a spherical structure element, and its radius determines the connectivity of the two stacked binary matrices; the generation process of BW2 is to place S at the coordinate point (x, y, z) of BW1. When the intersection of S and BW1 here is not an empty set, BW2(x, y, z) = 1; when the intersection of S and BW1 here is an empty set, BW2(x, y, z) = 0.

[0099] The superimposed data is as follows Figure 6 As shown, black represents valid data point 1 and white represents invalid data point 0.

[0100] S5: Connected body screening and inverse discretization: The largest connected body among several connected bodies is screened out by the number of valid data points it contains, and inverse discretization is performed to obtain the initial unwrapped phase;

[0101] The largest connected body is selected by the number of valid data points, and the initial unwrapped phase is obtained by inverse discretization operation;

[0102] The calculation formula of the largest connected body is as follows:

[0103]

[0104] Among them, BW3 is the largest connected body, |L i | is the number of valid data points;

[0105] The initial unwrapping phase calculation formula is as follows:

[0106]

[0107] in, is the initial unwrapped phase distribution obtained by inverse discretization operation.

[0108] The initial unwrapped phase is Figure 7 shown.

[0109] S6: System error elimination: Taking the wrapped phase of the binary effective data screening matrix established by the effective data points as the benchmark, the system phase error introduced in the data discrete binarization is calculated and eliminated from the initial unwrapped phase to obtain the unwrapped phase information, such as Figure 8As shown, its calculation formula is as follows:

[0110]

[0111] Wherein, is the systematic error generated in the discretization process in step S2, is the unwrapped phase distribution obtained after removing this systematic error.

[0112] Step 7: Rationality test and processing;

[0113] Using the unwrapped phase distribution obtained after removing the systematic error calculate the surface profile H(x,y) after eliminating the systematic error, as Fig. 9 shown, and then calculate its PV value;

[0114] The calculation formula of the surface profile after eliminating the systematic error is as follows:

[0115]

[0116] Wherein, H(x,y) is the surface profile after eliminating the systematic error, is the unwrapped phase distribution obtained after removing this systematic error, and λ is the laser wavelength of the used laser interferometer;

[0117] The calculation formula of the PV value is:

[0118] PV = max(H(x,y)) - min(H(x,y)) (10),

[0119] Wherein, H(x,y) is the surface profile after eliminating the systematic error;

[0120] Compare its PV with the numerical value M obtained by multiplying the number of interference fringes by 1 / 2 wavelength. When PV < M, then take H(x,y) as the flatness interference detection result of the discontinuous surface of the semiconductor chuck; when PV > M, re-perform the effective data screening process described in step S1, or perform erosion processing on the discretized binary phase data described in step S3, and re-perform phase unwrapping to complete the flatness interference detection of the discontinuous surface of the semiconductor chuck.

[0121] The full name of the PV value is the "peak valley" value, that is, the peak valley value, which is the difference between the maximum coordinate value and the minimum coordinate value of the surface profile data H(x,y). PV is a commonly used index for measuring the flatness of the measured surface in interference measurement.

[0122] In this embodiment, the calculated PV value is 1222.4 nm, the M value is 2214.8 nm, and PV < M. Therefore, the flatness interference detection measurement data of the discontinuous surface of the semiconductor chuck is valid, and H(x, y) is the flatness interference detection result of the discontinuous surface of the semiconductor chuck.

[0123] The present invention solves the technical problem that when the existing single-wavelength laser plane interferometer detects the flatness of a discontinuous surface, phase analysis errors will occur and the flatness of the discontinuous surface cannot be detected, and achieves the technical effect of accurately and quickly detecting the flatness of the discontinuous surface of the semiconductor chuck over a large range.

[0124] Any of the above-described methods or steps can be stored as computer instructions or programs in various types of computer memories, and the computer instructions or programs are recognized by various types of computer processors, thereby implementing any of the above methods or steps.

[0125] The embodiments described above are only used to describe the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for interferometric detection of the flatness of a non-continuous surface of a semiconductor chuck, characterized in that: The steps include: S1: Screening valid data points; obtaining the interference image of the discontinuous surface of the semiconductor chuck by a single-wavelength laser plane interferometer, generating the phase data information to be processed by grayscale processing, and screening the valid data points by setting a threshold for the brightness change, retaining the screened valid data points, and establishing a binary valid data screening matrix for the valid data points; S2: Discontinuous surface phase calculation: The wrapped phase of the valid data points is calculated by the nine-step averaging method; S3: Data discretization and binarization; The data calculated by the wrapped phase is discretized into three-dimensional space and binarized to obtain a binarized three-dimensional matrix; S4: Data stacking, morphological expansion and connection: stacking the binary three-dimensional matrix multiple times in a three-dimensional coordinate system, and performing three-dimensional morphological expansion and connection on the valid data points of the stacked binary three-dimensional matrix to form a number of connected bodies; S5: Connected body screening and inverse discretization: The largest connected body among several connected bodies is screened out by the number of valid data points it contains, and inverse discretization is performed to obtain the initial unwrapped phase; S6: System error elimination; Taking the wrapped phase of the binarized effective data screening matrix established by the effective data points as the benchmark, the systematic phase error introduced in the data discrete binarization is calculated and eliminated from the initial unwrapped phase to obtain the unwrapped phase; S7: Reasonableness check and processing; the flatness of the discontinuous surface of the semiconductor chuck is obtained by unwrapping the phase calculation, and the number of bright or dark fringes in the interference pattern of the laser interferometer is used as the standard for reasonableness check; when the result is reasonable, the flatness detection result obtained by unwrapping the phase is used as the flatness detection result of the discontinuous surface of the semiconductor chuck; when the data is unreasonable, the data is re-screened or the binary three-dimensional matrix is ​​corroded, the phase is re-unwrapped, and the flatness detection result is recalculated.

2. The method for detecting the flatness of a non-continuous surface of a semiconductor chuck according to claim 1, characterized in that: The step S1 comprises the following steps: Nine interference images with M×N pixels and a phase difference of π / 2 between each image and the previous image are obtained by a single-wavelength laser plane interferometer, and the phase data information to be processed is generated by grayscale processing, and the effective data points are screened by setting a threshold for the brightness change; The brightness change calculation formula is as follows: D(x,y)=max(I(x,y))-min(I(x,y)) (1), Among them, (x, y) is the coordinate of the pixel point, I(x, y) is the brightness of the pixel point, and D(x, y) is the extreme value of the brightness change of the pixel point in the nine phase images; The calculation formula of the binary effective data screening matrix is ​​as follows: Among them, e(x,y) is the binary screening matrix, and F is the brightness change screening threshold; The effective data point screening calculation formula is as follows: Among them, E i (x, y) is the brightness of the effective data point after screening, I i (x, y) is the brightness of the effective pixel after filtering.

3. The method for interferometric detection of the flatness of a non-continuous surface of a semiconductor chuck according to claim 2, characterized in that: The step S2 comprises the following steps: The filtered data points were used through the nine-step averaging method to obtain the wrapped phase data; The formula for calculating the package phase data is as follows: in, is the wrapped phase data, E i (x, y)i=1, 2, ..., 9 is the brightness of the effective data points after screening obtained in step S1.

4. The method for interferometric detection of the flatness of a non-continuous surface of a semiconductor chuck according to claim 3, characterized in that: The step S3 comprises the following steps: Perform binary discretization on the wrapped phase data to obtain a binary phase matrix; divide the binary phase matrix data into l layers, that is, the height of each layer is 2π / l, binaryize and discretize it into a three-dimensional data space, with valid data points being 1 and invalid data points being 0, to obtain a three-dimensional binary matrix BW(x, y, z).

5. The method for interferometric flatness detection of a non-continuous surface of a semiconductor chuck according to claim 4, characterized in that: Step S4 includes the following steps: Stack the binary discretized phase matrix to obtain a three-dimensional binary matrix BW1(x, y, z) and connect it through three-dimensional morphological dilation to generate a number of connected components; The formula for generating a number of connected components is as follows: Where S is a spherical structuring element, and its radius determines the connection of the stacked binary matrices in two layers; the generation process of BW2 is to place S at the coordinate point (x, y, z) of BW1. When the intersection of S and BW1 here is not an empty set, then BW2(x, y, z) = 1; when the intersection of S and BW1 here is an empty set, then BW2(x, y, z) = 0.

6. The method for interferometric flatness detection of a non-continuous surface of a semiconductor chuck according to claim 5, characterized in that: Step S5 includes the following steps: Select the largest connected component by the number of valid data points it contains, and perform inverse discretization operation to obtain the initial unwrapped phase; The formula for the largest connected component is as follows: Among them, BW3 is the largest connected body, |L i | is the number of valid data points; The formula for the initial unwrapped phase is as follows: in, is the initial unwrapped phase distribution obtained by inverse discretization operation.

7. The method for interferometric detection of the flatness of a non-continuous surface of a semiconductor chuck according to claim 6, characterized in that: Step S6 includes the following steps: Calculate the systematic error caused by the discretization operation and remove this error to obtain the unwrapped phase information, and its formula is as follows: in, is the systematic error generated by the discretization process in step S2, is the unwrapped phase distribution obtained after removing this systematic error.

8. The method for interferometric detection of the flatness of a non-continuous surface of a semiconductor chuck according to claim 7, characterized in that: Step S7 includes the following steps: Using the phase distribution obtained after removing the system error Calculate the surface shape H(x,y) and its PV value after eliminating the system error; The formula for the surface shape after eliminating the systematic error is as follows: Among them, H(x,y) is the surface shape after eliminating the system error, is the unwrapped phase distribution obtained after removing this systematic error, λ is the laser wavelength of the laser interferometer used; The formula for the PV value is: PV = max(H(x, y)) - min(H(x, y)) (10), Where H(x, y) is the surface shape after eliminating the systematic error; Compare its PV with the value M obtained by multiplying the number of interference fringes by 1 / 2 wavelength. When PV < M, then use H(x, y) as the flatness interference detection result of the discontinuous surface of the semiconductor chuck; when PV > M, re-perform the valid data screening process described in step S1, or perform erosion processing on the data discretized binary phase data described in step S3, and re-perform phase unwrapping to complete the flatness interference detection of the discontinuous surface of the semiconductor chuck.

Images