Michelson interferometer and micro part morphology detection method

Abstract

The invention discloses a Michelson interferometer and a micro device morphology detection method. The interferometer comprises two interference light paths. In the first interference light path, a light beam of a first light source is split by a first beam splitter, one light beam is reflected to an object to be tested, the other light beam is transmitted to a first test reflector, the two light beams are respectively returned to the first beam splitter for interference, and a first image acquisition system receives a first interference image; in the second interference light path, the light beam of the second light source is split by a second beam splitter, one beam is reflected to the calibration reflector, the other beam is transmitted to a second test reflector, the two beams are respectively returned to the second beam splitter for interference, and a second image acquisition system receives a second interference image; the two interference light paths share the same piezoelectric ceramic, and the piezoelectric ceramic controls the displacement of the first test reflector and the second test reflector. According to the invention, the first interference image can be corrected based on the second interference image, image restoration is carried out based on the corrected first interference image, and the surface topography of the to-be-measured object is obtained.

Description

Technical Field

[0001] This application relates to the field of optical measurement technologies, and in particular, to a Michelson interferometer and a method for detecting the morphology of micro-components. Background Art

[0002] Piezoelectric ceramics are precision devices that generate micro-displacement creep controlled by voltage. Affected by changes in external factors such as temperature and vibration, the elongation may change from a linear relationship to a non-linear relationship with the change of voltage, thus affecting the step movement length in the Michelson interference system, and further affecting the phase difference of the interference image of the object to be measured obtained by the image acquisition system. Most of the existing optical path interference measurement systems for detecting the morphology of micro-devices using piezoelectric ceramic controllers only use a piezoelectric ceramic controller's micro-nano rotary table to achieve 360° manual rotation and an adjustable tilt table, reducing external interference from the piezoelectric ceramic structure. However, real-time data feedback and error analysis cannot be performed during use, resulting in a low accuracy of the interference image of the object to be measured obtained. Summary of the Invention

[0003] To solve the deficiencies of the prior art, the following technical solutions are adopted in this application: In a first aspect, a Michelson interferometer provided by this application includes: A first Michelson interference optical path, including a first light source, a workbench, a first beam splitter, a first test mirror, and a first image acquisition system. The workbench is used to place the object to be measured. The beam emitted by the first light source is split by the first beam splitter. One beam is reflected onto the surface of the object to be measured, and the other beam is transmitted to the first test mirror. The two beams are reflected back respectively after passing through the object to be measured and the first test mirror, and interfere at the first beam splitter. The first image acquisition system receives the first interference image; A second Michelson interference optical path, including a second light source, a calibration mirror, a second beam splitter, a second test mirror, and a second image acquisition system. The beam emitted by the second light source is split by the second beam splitter. One beam is reflected onto the surface of the calibration mirror, and the other beam is transmitted to the second test mirror. The two beams are reflected back respectively after passing through the calibration mirror and the second test mirror, and interfere at the second beam splitter. The second image acquisition system receives the second interference image; The first Michelson interference optical path and the second Michelson interference optical path share the same piezoelectric ceramic, and the piezoelectric ceramic is configured to control the displacement of the first test mirror and the second test mirror.

[0004] In summary, a Michelson interferometer provided by the present application shares the same piezoelectric ceramic in the first Michelson interference optical path and the second Michelson interference optical path, ensuring the displacement synchronization of the first Michelson interference optical path as the measurement system and the second Michelson interference optical path as the calibration system, enabling the phase change of the second interference image obtained by the second Michelson interference optical path to accurately reflect the actual phase data of the first Michelson interference optical path. Based on the obtained second interference image, the first interference image is corrected, and image restoration is performed based on the corrected first interference image, finally obtaining the accurate surface topography of the object to be measured, realizing real-time data feedback and error calibration during the detection process, and improving the accuracy and reliability of the topography detection of micro-devices.

[0005] Further, the second light source is configured as a helium-neon laser to eliminate the dispersion effect in the second Michelson interference optical path; The Michelson interferometer further includes a processing module, which is configured to perform phase analysis on the second interference image by the principal component analysis method to obtain a wrapped phase map. The wrapped phase map includes the wrapped phases of different pixel points of the second interference image, and perform phase unwrapping on the wrapped phase map by the path tracking method to obtain the true absolute phases of different pixel points; Based on the true absolute phases, the processing module performs phase compensation on the first interference image, regenerates a uniform interference image, and performs image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured.

[0006] Further, the processing module performing phase analysis on the second interference image by the principal component analysis method includes: Based on multiple second interference images collected by the second image acquisition system, an original data matrix is constructed; Subtract the background light intensity from the original data matrix to obtain an alternating current component matrix of the interference fringes; Perform singular value decomposition on the alternating current component matrix, Based on the singular value decomposition result, principal components are selected. The residual of the background light intensity is selected as the first principal component, the spatial distribution of the cosine component of the phase information is selected as the second principal component, and the spatial distribution of the sine component of the phase information is selected as the third principal component, Vectorize the selected principal components, and obtain the wrapped phase map based on the vectorized result.

[0007] Further, the processing module performing phase unwrapping on the wrapped phase map by the path tracking method includes: Perform quality assessment on the availability of pixel points in the wrapped phase diagram, obtain the quality factors of pixel points in different regions of the wrapped phase diagram, and generate a quality map based on the quality factors; Construct a priority queue for different regions of the wrapped phase diagram based on the quality factors. According to the priority queue, preferentially perform iterative unwrapping on regions with higher priorities to obtain the true absolute phase of each pixel point in different regions.

[0008] Further, when performing phase unwrapping, the processing module is further configured such that if the height and phase relationship of the object to be measured satisfy: then add a curvature constraint to the height of the object to be measured. The curvature constraint is expressed by the following formula: ; In the formula, λ represents the wavelength of the second light source, h ( x , y ) represents the height of the object to be measured at the coordinate ( x , y ), represents the true absolute phase of the pixel point ( x , y ), and k represents the curvature constraint.

[0009] Further, the processing module performs phase compensation on the first interference image in the first Michelson interference optical path based on the true absolute phase to regenerate a uniform interference image, including: Calculate the phase compensation values of different pixel points according to the true absolute phase of each pixel point through the following formula: ; In the formula, is the standard displacement of the piezoelectric ceramic controller, , is the actual displacement of the piezoelectric ceramic, λ represents the wavelength of the second light source, represents the true absolute phase of the pixel point, Based on the phase compensation values, perform phase compensation on the pixel points at the corresponding coordinates in the first interference image to regenerate a uniform interference image.

[0010] Further, the processing module performs phase compensation on the pixel points at the corresponding coordinates in the first interference image through the following formula: ; In the formula, represents the gray value of the compensated pixel point, represents the DC component of the background light intensity in the first Michelson interference optical path, represents the modulation amplitude of the first Michelson interference optical path, represents the gray value of the pixel points of the uncompensated first interference image, represents the standard displacement of the piezoelectric ceramic controller.

[0011] Further, the processing module is further configured to: generate interference curves of different pixel points based on each corresponding pixel point in multiple uniform interference images, select some of the interference curves as normal interference curves, and generate a reference distribution based on the selected normal interference curves; adopt a two-sample normality test to screen out interference curves with the same or similar curve distribution as the reference distribution from the remaining interference curves, generate a new data set, and perform image restoration based on the new data set to obtain the surface topography of the object to be measured.

[0012] Further, the first light source is configured as white light.

[0013] In a second aspect, the present application further provides a method for detecting the topography of a micro-device. The method applies the above-mentioned Michelson interferometer, and the method includes the following steps: Perform phase analysis on the second interference image through the principal component analysis method to obtain a wrapped phase map. The wrapped phase map includes the wrapped phases of different pixel points of the second interference image, and perform phase unwrapping on the wrapped phase map through the path tracking method to obtain the true absolute phases of different pixel points; Based on the true absolute phases, perform phase compensation on the first interference image, regenerate a uniform interference image, and perform image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured. Description of the Drawings

[0014] Figure 1 is a schematic structural diagram of a Michelson interferometer provided by an embodiment of the present application; Figure 2 is a flowchart of the steps for the processing module in the Michelson interferometer provided by an embodiment of the present application to obtain the surface topography of the object to be measured; Figure 3 is a flowchart of the steps for the processing module in the Michelson interferometer provided by an embodiment of the present application to obtain a wrapped phase map; Figure 4 is a flowchart of the steps for the processing module in the Michelson interferometer provided by an embodiment of the present application to obtain the true absolute phases of different pixel points; Figure 5 is a flowchart of the steps for the processing module in the Michelson interferometer provided by an embodiment of the present application to regenerate a uniform interference image; Figure 6The flowchart of the steps for the processing module in the Michelson interferometer provided by an embodiment of the present application to perform image restoration based on the regenerated uniform interference image; Figure 7 The schematic diagram of the interference curve of normal pixel points in the Michelson interferometer provided by an embodiment of the present application; Figure 8 The schematic diagram of the interference curve of noise pixel points in the Michelson interferometer provided by an embodiment of the present application; Figure 9 The schematic diagram of fitting the interference curve with a quadratic Gaussian function in the Michelson interferometer provided by an embodiment of the present application; Figure 10 The flowchart of the steps of the method for detecting the morphology of a micro-device provided by an embodiment of the present application. Detailed implementation manners

[0015] The following will describe the present application in detail with reference to the specific implementation manners shown in the drawings. However, these implementation manners do not limit the present application, and any structural, method, or functional transformation made by those of ordinary skill in the art based on these implementation manners is included in the protection scope of the present application.

[0016] To solve the deficiencies of the prior art, in a first aspect, as Figure 1 shown, the present application provides a Michelson interferometer 100, which includes a first Michelson interference optical path 11, a second Michelson interference optical path 12, and a piezoelectric ceramic 13. Among them, the first Michelson interference optical path 11 includes a first light source 111, a workbench 112, a first beam splitter 113, a first test mirror 114, and a first image acquisition system 115. The workbench 112 is used to place the object to be measured. The light beam emitted by the first light source 111 is split by the first beam splitter 113. One beam is reflected to the surface of the object to be measured, and the other beam is transmitted to the first test mirror 114. The two beams of light are reflected back respectively after passing through the object to be measured and the first test mirror 114, and interfere at the first beam splitter 113. The first image acquisition system 115 receives the first interference image.

[0017] The second Michelson interference optical path 12 includes a second light source 121, a calibration mirror 122, a second beam splitter 123, a second test mirror 124, and a second image acquisition system 125. The light beam emitted by the second light source 121 is split by the second beam splitter 123. One beam is reflected onto the surface of the calibration mirror 122, and the other beam is transmitted to the second test mirror 124. The two beams of light are reflected back by the calibration mirror 122 and the second test mirror 124 respectively, and interfere at the second beam splitter 123. The second image acquisition system 125 receives the second interference image. The first Michelson interference optical path 11 and the second Michelson interference optical path 12 share the same piezoelectric ceramic 13, and the piezoelectric ceramic 13 is configured to control the displacements of the first test mirror 114 and the second test mirror 124.

[0018] Specifically, in the first Michelson interference optical path 11, the workbench 112 ensures that the object to be measured remains in a fixed position during the measurement process. The first light source 111 is used to emit a light beam. The emitted light beam is split into two beams by the first beam splitter 113. One beam is reflected onto the surface of the object to be measured on the workbench 112, and the other beam is transmitted to the first test mirror 114. The first test mirror 114 is connected to the piezoelectric ceramic 13. By controlling the voltage, the piezoelectric ceramic 13 generates a small displacement, thereby controlling the first test mirror 114 to perform a small displacement, and thus changing the optical path difference of the reference optical path. After the two beams of light from the first light source 111 are reflected by the object to be measured and the first test mirror 114 respectively, they return to the first beam splitter 113 to recombine and interfere, forming interference fringes. The first image acquisition system 115 (such as a CCD grayscale camera) takes a picture of the surface of the object to be measured to obtain the first interference image. Based on the first interference image, subsequently, the gray values of the pixel points at the same position in different interference images are extracted to form an interference curve, which is used to analyze the relative height values of the pixel points, providing a data basis for the surface topography detection of the object to be measured. Optionally, the resolution of the first interference image in the embodiment of the present application is 1344×564 pixels.

[0019] In the second Michelson interference optical path 12, after the light beam emitted by the second light source 121 is split by the second beam splitter 123, one beam is reflected onto the surface of the calibration mirror 122, and the other beam is transmitted to the second test mirror 124. The second test mirror 124 is connected to the piezoelectric ceramic 13. By controlling the voltage, the piezoelectric ceramic 13 generates a small displacement, thereby controlling the second test mirror 124 to perform a small displacement, and thus changing the optical path difference of the reference optical path. The two reflected light beams from the second light source 121 are reflected back by the calibration mirror 122 and the second test mirror 124 respectively, and interfere at the second beam splitter 123, forming interference fringes. The second image acquisition system 125 (such as a CCD grayscale camera) takes a picture to obtain the second interference image, and the second interference image provides calibration data for subsequent phase compensation of the first interference image.

[0020] Further, the first test mirror 114 of the first Michelson interference optical path 11 and the second test mirror 124 of the second Michelson interference optical path 12 share the same piezoelectric ceramic 13. The driving mechanism of the piezoelectric ceramic 13 is based on the inverse piezoelectric effect: when a voltage is applied, the piezoelectric ceramic 13 deforms, thereby pushing the first test mirror 114 and the second test mirror 124 to move synchronously, synchronously changing the optical path difference between the two optical paths.

[0021] According to the above description, a Michelson interferometer provided by the present application ensures the displacement synchronization of the first Michelson interference optical path as the measurement system and the second Michelson interference optical path as the calibration system by sharing the same piezoelectric ceramic between the first Michelson interference optical path and the second Michelson interference optical path, enabling the phase change of the second interference image obtained by the second Michelson interference optical path to accurately reflect the actual phase data of the first Michelson interference optical path. Based on the obtained second interference image, the first interference image is corrected, and image restoration is performed based on the corrected first interference image, finally obtaining the accurate surface topography of the object to be measured, realizing real-time data feedback and error calibration during the detection process, and improving the accuracy and reliability of the surface topography detection of micro-devices.

[0022] As an optional implementation manner, the first light source is configured as a white light source. White light has a large dispersion, which is convenient for obtaining interference information by positioning the zero optical path difference position. The second light source uses a helium-neon laser with a wavelength of 632.8 nm. The helium-neon laser has the characteristics of monochromaticity and high coherence. Without considering the dispersion effect, the phase can be directly calculated, eliminating the dispersion effect in the second Michelson interference optical path and avoiding the complex process of positioning the zero optical path difference position in white light interference.

[0023] As an optional implementation manner, the Michelson interferometer provided by the present application further includes a processing module. The processing module obtains the surface topography of the object to be measured through the following steps, as Figure 2 shown, specifically including the following steps: Step S101, perform phase analysis on the second interference image through principal component analysis to obtain a wrapped phase map, and the wrapped phase map includes the wrapped phases of different pixel points of the second interference image.

[0024] Step S102, perform phase unwrapping on the wrapped phase map through the path tracking method to obtain the true absolute phases of different pixel points.

[0025] Step S103, the processing module performs phase compensation on the first interference image based on the true absolute phases to regenerate a uniform interference image.

[0026] Step S104, perform image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured.

[0027] Specifically, in step S101, a background image without light interference is captured in advance, and the background light intensity is obtained by analyzing the light intensity value. The wrapped phase information is extracted from the second interference image by the principal component analysis method. A matrix is formed by stacking multiple second interference images collected when the piezoelectric ceramic drives the second test mirror to move. The background light intensity obtained in advance is subtracted from this matrix to obtain a matrix containing the AC component of the interference fringes. Principal component analysis is performed on the matrix containing the AC component of the interference fringes to separate different principal components, and finally a wrapped phase map is generated through vectorization processing. The wrapped phase map includes the wrapped phases of different pixel points in the second interference image, providing the original data basis for subsequent phase unwrapping.

[0028] After obtaining the wrapped phase map, in step S102, the path tracking method is used to perform phase unwrapping on the wrapped phase map. The phase quality of the pixel points in the wrapped phase map is evaluated and sorted according to the quality evaluation results. The image regions with higher quality values are preferentially unwrapped. By unwrapping the wrapped phase region by region, the true absolute phases of different pixel points in the wrapped phase map are obtained. The true absolute phase can reflect the actual wrapped phase situation with uneven phase differences, laying a foundation for compensating and calibrating the phase.

[0029] Based on the true absolute phases of different pixel points obtained, in step S103, phase compensation is performed on the first interference image to correct the possible phase distortion in the image, eliminate the non-uniformity of the phase distribution, regularize the interference fringes, and generate an interference image with a uniform phase distribution, providing data for subsequent surface topography restoration. After regenerating the uniform interference image, in step S104, the interference curves of each pixel point are extracted from the uniform interference image. A certain number of interference curves are selected as the reference distribution, and the statistical differences between the remaining curves and the reference distribution are calculated. The interference curves with the same or similar curve distributions as the reference distribution are screened, and then the image is restored to obtain the surface topography of the object to be measured, realizing high-precision detection of the surface of micro-devices.

[0030] By performing phase analysis on the second interference image through the principal component analysis method, a wrapped phase map including the wrapped phases of different pixel points in the second interference image is obtained. Then, the path tracking method is used to perform phase unwrapping on the wrapped phase map to obtain the true absolute phases of the pixel points. Furthermore, the phase of the first interference image is compensated to correct the measurement error and improve the measurement accuracy and stability of the Michelson interferometer.

[0031] As an alternative implementation, as Figure 3 shown, in step S101, the processing module performs phase analysis on the second interference image through the principal component analysis method to obtain the wrapped phase map, and further includes the following steps: Step S201, based on multiple second interference images collected by the second image acquisition system, construct an original data matrix.

[0032] Step S202: Subtract the background light intensity from the original data matrix to obtain the alternating current component matrix of the interference fringes.

[0033] Step S203: Perform singular value decomposition on the alternating current component matrix.

[0034] Step S204: Based on the singular value decomposition result, perform principal component selection. Select the residual of the background light intensity as the first principal component, the spatial distribution of the cosine component of the phase information as the second principal component, and the spatial distribution of the sine component of the phase information as the third principal component.

[0035] Step S205: Vectorize the selected principal components and obtain the wrapped phase diagram based on the vectorized result.

[0036] Specifically, in step S201, based on multiple second interference images collected by the second image acquisition system, a data matrix is constructed. Exemplarily, the piezoelectric ceramic moves from top to bottom, and the second image acquisition system takes and collects a total of 125 second interference images. Stack the 125 second interference images to form the original data matrix. In the embodiment of the present application, the expression of the original data matrix is as follows: (1); In the formula, D represents the original data matrix, R represents the set of real numbers, and M represents the number of pixels of the interference image. In the embodiment of the present application, the number of pixels M is 758016.

[0037] After the construction of the original data matrix is completed, in step S202, subtract the background light intensity from the original data matrix, separate the effective information containing the interference fringes from the original data matrix, and obtain the alternating current component matrix. In the embodiment of the present application, the expression of the alternating current component matrix is as follows: (2); In the formula, D represents the original data matrix; represents the background light intensity, and D0 represents the alternating current component matrix.

[0038] After obtaining the alternating current component matrix, in step S203, perform singular value decomposition on the alternating current component matrix, decompose the alternating current component matrix into the product of three matrices, decompose the complex interference signal into independent principal components, and provide a mathematical basis for phase information separation. The expression for performing singular value decomposition on the alternating current component matrix is as follows: (3); In the formula, U represents the left singular vector matrix. The spatial pattern of the left singular vector matrix U is that the column vectors are orthogonal, which is the characteristic distribution of the interference image; S represents the diagonal matrix. The diagonal matrix S is used to reflect the energy distribution, and the diagonal elements are singular values. The diagonal elements of the diagonal matrix S can reflect the energy; V represents the right singular vector matrix. The temporal pattern of the right singular vector matrix V is that the column vectors are orthogonal, and the column vectors of the right singular vector matrix V represent the evolution during the phase shift process.

[0039] Based on the singular value decomposition of the AC component matrix, in step S204, principal component selection is performed according to the decomposition result. Among them, the residual of the background light intensity is selected as the first principal component, the spatial distribution of the cosine component of the phase information is selected as the second principal component, and the spatial distribution of the sine component of the phase information is selected as the third principal component.

[0040] After completing the principal component selection, in step S205, the selected principal components are vectorized. Among them, the first principal component is the residual of the background light intensity, and its singular value is close to 0. The actual contribution of the first principal component can be ignored, and there is no need to perform vectorization processing on the first principal component. The second principal component and the third principal component are vectorized, and the vectorization expression is as follows: (4); In the formula, represents the spatial distribution of the second principal component U2, represents the spatial distribution of the third principal component U3, and vec represents vectorization.

[0041] Exemplarily, a matrix is expanded into a column vector in column-major order to facilitate efficient data processing in phase calculation. For example: (5); In the formula, represents the spatial distribution of the second principal component U2.

[0042] By vectorization processing, the second principal component and the third principal component matrices are expanded into column vectors by rows. Each column vector of the second principal component and the third principal component respectively corresponds to the cosine and sine values of the phase of each pixel point. The phase value of each pixel point is calculated through the arctangent function, so as to obtain the wrapped phase map. Each pixel value in the wrapped phase map represents the phase information of the corresponding position, and the wrapped phase situation with uneven phase differences is reflected through the phase information of each pixel point. Further, when the flat mirror of the Michelson interferometer moves towards the light source direction to reduce the optical path difference, a negative sign is introduced into the arctangent function to compensate the phase value. In the embodiments of the present application, the expression of the arctangent function is as follows: (6); In the formula, It represents the wrapped phase, U2 represents the second principal component, and U3 represents the third principal component.

[0043] Through the above principal component analysis method, the phase analysis of the second interference image is carried out to complete the conversion from the second interference image data to the wrapped phase diagram. The wrapped phase diagram reflects the phase jump caused by the nonlinearity of the actual displacement of the piezoelectric ceramic, providing key data for subsequent phase unwrapping and topography restoration.

[0044] As an alternative implementation, as Figure 4 shown, in step S102, the processing module performs phase unwrapping on the wrapped phase diagram through the path tracking method to obtain the true absolute phase of different pixel points, and further includes the following steps: Step S301, perform quality evaluation on the availability of pixel points in the wrapped phase diagram to obtain the quality factors of pixel points in different regions of the wrapped phase diagram, and generate a quality map based on the quality factors.

[0045] Step S302, construct a priority queue for different regions of the wrapped phase diagram based on the quality factors, and according to the priority queue, preferentially perform iterative unwrapping on regions with higher priorities to obtain the true absolute phase of each pixel point in different regions.

[0046] Specifically, based on the wrapped phase diagram, perform quality evaluation on the availability of pixel points in the wrapped phase diagram, assign quality factors to each pixel point in the wrapped phase diagram, calculate the variance of the phase gradient within the local region, and the smaller the variance, the smoother the phase change and the smaller the noise interference in this region, and the higher the quality factor. The expression for calculating the phase gradient variance is as follows: (7); In the formula, represents the gradient variance; represents the phase gradient; W represents the local region, and in the embodiment of the present application, the local region W is 25*25; represents the gradient mean within the local region W, serving as a reference quantity to measure the deviation degree of each pixel point.

[0047] Furthermore, the phase gradient is divided into the horizontal direction gradient and the vertical direction gradient .

[0048] The horizontal direction gradient has the following expression: (8); In the formula, represents the phase value of the pixel point (i, j+1), represents the phase value of the pixel point (i, j), and the pixel point (i, j + 1) is the right - hand neighborhood pixel point of the pixel point (i, j) in the matrix.

[0049] Vertical direction gradient The expression is as follows: (9); In the formula, represents the phase value of the pixel point (i + 1, j), represents the phase value of the pixel point (i, j), and the pixel point (i + 1, j) is the lower - hand neighborhood pixel point of the pixel point (i, j) in the matrix.

[0050] By calculating the gradient amplitude in formula (7), the change amount of the gradient amplitude in the local area can be reflected, and it can be judged whether there is data jump or noise influence while it is hot. For example, when detecting the end face of an optical fiber connector, there is a certain distance between the optical fiber ferrule and the connector end face, and a phase jump will occur here; or due to the presence of noise interference points such as water, dust, and oil stains that do not match the end - face material on the connector end face, a change in phase may be found. In the embodiment of the present application, the calculation expression of the gradient amplitude is as follows: (10); In the formula, represents the gradient amplitude, represents the horizontal direction gradient, represents the vertical direction gradient.

[0051] The quality factor of the pixel point is calculated through the phase - gradient variance, thereby generating a quality map. In the embodiment of the present application, the calculation expression of the quality factor is as follows: (11); In the formula, represents the quality factor; is a minimum value of the order of 1 / 1000000, which is used to protect the denominator from being zero to increase the reliability and stability of the data.

[0052] After obtaining the quality factors of the pixel points in different regions of the wrapped phase diagram, a priority queue for different regions of the wrapped phase diagram is constructed based on the quality factors. According to the priority queue, the smaller the phase gradient variance of a region, the higher its quality value, and the unwrapping process is preferentially performed to obtain the true absolute phases of the pixel points in different regions. During the unwrapping process, starting from the pixel points in the high-quality region, the phase difference between adjacent pixels is calculated point by point, and by adding a correction term of an integer multiple of 2π, the wrapped phase is expanded into a continuous true absolute phase. Through the above processing method, the regions with high reliability are preferentially processed and gradually extended to the low-quality regions, and finally the true absolute phase of the entire wrapped phase diagram is obtained, effectively solving the problem that the traditional path tracking method is vulnerable to noise and improving the stability and accuracy of phase unwrapping.

[0053] In the embodiment of the present application, the expression of the true absolute phase is as follows: (12); In the formula, represents the true absolute phase of the pixel point (x, y) obtained by unwrapping; represents the wrapped phase value of the pixel point (x, y) before unwrapping; k is an integer, and .

[0054] Select the value of k such that the phase is between -π and π. The calculation formula of the integer k is: (13); In the formula, represents the reference pixel that has been unwrapped, and the pixel point is the neighboring pixel of the previously processed pixel point (x, y) and is used as a known quantity to guide the unwrapping; represents the wrapped phase value of the pixel point (x, y), and the range is [-π, π] or [0, 2π]; represents the pixel point 's wrapped phase value, and the pixel point is the neighboring pixel of the pixel point (x, y).

[0055] According to the priority queue, the regions with higher priorities are preferentially iteratively unwrapped, and it is set to unwrap along the path within the region, so as to obtain the true absolute phases of the pixel points in different regions. The phase needs to satisfy: (14); In the formula, represents the true absolute phase; represents the reference phase that has been unwrapped; represents the wrapped phase value of the pixel point (x, y); represents the wrapped phase value of the neighboring pixel of the pixel point (x, y).

[0056] Further, as an alternative implementation, the processing module is configured to: when performing phase unwrapping on the wrapped phase diagram, if the height-phase relationship of the object to be measured satisfies: (15); In the formula, λ represents the wavelength of the second light source, h(x, y) represents the height of the object to be measured at the coordinate (x, y), represents the true absolute phase of the pixel point (x, y).

[0057] Then, a curvature constraint is added to the height of the object to be measured to limit the second derivative of the surface height of the object to be measured and avoid drastic phase oscillations caused by noise or abnormal data. The curvature constraint is expressed by the following formula: (16); In the formula, k represents the curvature constraint, h represents the height of the pixel point, x represents the abscissa value of the pixel point, and y represents the ordinate value of the pixel point.

[0058] By combining the priority of the quality map and the curvature constraint, the wrapped phase is gradually converted into the true absolute phase reflecting the actual optical path difference, accurately reflecting the actual displacement phase of the calibration system, and providing accurate calibration parameters for subsequent phase compensation.

[0059] As an alternative implementation, as Figure 5 shown, in step S103, the processing module performs phase compensation on the first interference image in the first Michelson interference optical cable based on the true absolute phase to regenerate a uniform interference image, and further includes the following steps: Step S401, according to the true absolute phase of each pixel point, calculate the phase compensation value of different pixel points through the following formula: (17); In the formula, is the standard displacement of the piezoelectric ceramic controller, and , is the actual displacement of the piezoelectric ceramic, λ represents the wavelength of the second light source, represents the true absolute phase of the pixel point, represents the phase compensation value.

[0060] During the phase compensation process, the displacement manually set by the piezoelectric ceramic controller is used as the standard quantity. The actual displacement is not fixed and is reflected by an uneven phase difference. Therefore, subtracting the standard displacement from the true absolute phase of the pixel can obtain the phase compensation value. Moreover, the displacement directions of the first Michelson interference optical path and the second Michelson interference optical path are opposite, so the phase compensation shows an opposite relationship. By calculating the phase compensation value of each pixel, phase compensation is performed on each pixel to eliminate the phase error of the pixel.

[0061] Step S402: Based on the phase compensation value, perform phase compensation on the pixel corresponding to the coordinate in the first interference image to regenerate a uniform interference image. Specifically, since the light source wavelengths of the first Michelson interference optical path and the second Michelson interference optical path are different, the uncorrected phase is extracted from the envelope of the first Michelson interference optical path. In the phase compensation calculation of the pixel corresponding to the coordinate in the first interference image, the error caused by the phase shift in the envelope extraction and the phase compensation value are introduced, so as to update the phase parameter of the modulation amplitude of the first Michelson interference optical path and regenerate a uniform interference image.

[0062] As an alternative implementation, the processing module performs phase compensation on the pixel corresponding to the coordinate in the first interference image through the following formula: (18); In the formula, represents the gray value of the compensated pixel, represents the DC component of the background light intensity in the first Michelson interference optical path, represents the modulation amplitude of the first Michelson interference optical path, represents the gray value of the pixel in the uncompensated first interference image, represents the standard displacement of the piezoelectric ceramic controller.

[0063] As an alternative implementation, as Figure 6 shown, in step S104, the processing module performs image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured, and further includes the following steps: Step S501: Generate interference curves of different pixels based on the pixels corresponding to each other in multiple uniform interference images.

[0064] Step S502: Select some of the interference curves as normal interference curves and generate a reference distribution based on the selected normal interference curves.

[0065] Step S503: Use the two-sample normality test to screen out the interference curves whose curve distributions are the same as or similar to the reference distribution from the remaining interference curves, generate a new data set, and perform image restoration based on the new data set to obtain the surface topography of the object to be measured.

[0066] Specifically, in step S501, multiple uniform interference images are analyzed, and the gray value sequences of each pixel point are extracted from the regenerated uniform interference images to generate interference curves of different pixel points. The interference curves can reflect the gray modulation caused by the change in optical path difference during the displacement of the piezoelectric ceramic, and the peak value of its envelope corresponds to the zero optical path difference position. Exemplarily, the resolution of the uniform interference image is 1344*564, with a total of 758016 pixel points, so there are 758016 interference curves. Exemplarily, the interference curve of a normal pixel point is as shown in Figure 7 shown, and the interference curve of a noise pixel point is as shown in Figure 8 shown. In the figure, the abscissa represents the moving distance, and the ordinate represents the gray value.

[0067] After generating the interference curves of different pixel points, in step S502, regions with clear interference fringes, high contrast, and no obvious noise are selected, and the interference curves corresponding to these regions are extracted as normal interference curves, and a reference distribution is generated based on the selected normal interference curves. Exemplarily, 1000 interference fringes are selected from 758016 interference curves as normal interference curves, and the remaining 757016 interference curves are used as the curves to be measured. Set the actual light intensity value of the normal interference curve to , where (j = 1, 2, 3...1000), and the predicted model light intensity value is obtained by performing Gaussian fitting on 1000 normal interference curves. The quadratic Gaussian function fits the interference curve as shown in Figure 9 shown, and the maximum point of the envelope is the zero optical path difference position. Calculate the residual between the actual light intensity value and the predicted model light intensity value of the normal interference curve, and the calculation expression is as follows: (19); In the formula, represents the actual light intensity value of the normal interference curve, represents the predicted model light intensity value, represents the residual.

[0068] Mix the 125 data points on each of the 1000 normal interference curves into a large set as the reference residual distribution set, and the capacity of the reference residual distribution set is 1000*125 = 125000. Further, after sorting all the data from small to large, a reference distribution is generated, and the expression of the reference distribution is as follows: (20); In the formula, represents the reference distribution, represents the reference residual distribution set the i-th sample in, I represents the light intensity value.

[0069] Preprocess the remaining 757,016 curves to be measured using a two-sample permutation test. Calculate the residuals of the curves to be measured. Through the two-sample permutation test method, screen out the normal pixel points between the noise pixel points and the normal pixel points for feature extraction and other steps, which greatly reduces the amount of calculation data, thereby improving the data analysis speed. The residual calculation expression of the Kth curve to be measured is as follows: (21); In the formula, represents the actual light intensity value of the Kth curve to be measured, represents the modeled light intensity value of the Kth curve to be measured.

[0070] Based on the residuals of the Kth curve to be measured, establish a set , and the capacity of this set is 125. The empirical distribution function expression of the Kth curve to be measured is: (22); In the formula, represents the rth sample in the set .

[0071] Calculate the two-sample permutation test statistic for the residual set of the Kth curve to be measured and the reference residual distribution set . Its calculation expression is as follows: (23); In the formula, Z is the sorted set of the values of after removing duplicates; n1 is the capacity of the reference residual distribution set , and n1 is 125,000; n2 is the capacity of the residual set , and n2 is 125; W 2 represents the two-sample permutation test statistic.

[0072] Make a significance judgment on the remaining interference curves. Set the null hypothesis H0: The distribution of the interference curve to be measured is similar to or the same as the reference distribution, and it is a normal pixel point; the alternative hypothesis H1: The curve to be measured has a significant difference from the reference distribution, and it is a noise interference curve. Make a significance judgment on the interference curve to be measured. Set the significance level α = 0.05, and generate the critical value of the statistic through the Monte Carlo simulation method or by looking up the table.

[0073] If the two-sample permutation test statistic W 2 is greater than or equal to the critical value of the statistic , reject the original hypothesis H0, that is, the current curve is significantly different from the reference distribution, and it is the interference curve of noise pixel points; conversely, if the two-sample state test statistic W 2 is less than the critical value of the statistic , accept the original hypothesis H0, that is, the current curve is similar to or the same as the reference distribution, and it is the interference curve of normal noise points. Generate a new data set based on the interference curve that is the same as or similar to the reference distribution, and perform the analysis of topography restoration on the basis of this data set, and finally obtain the surface topography of the object to be measured.

[0074] According to the above description, a Michelson interferometer provided by the present application shares the same piezoelectric ceramic through the first Michelson interference optical path and the second Michelson interference optical path, ensuring the displacement synchronization of the first Michelson interference optical path as the measurement system and the second Michelson interference optical path as the calibration system, so that the phase change of the second interference image obtained by the second Michelson interference optical path can accurately reflect the actual phase data of the first Michelson interference optical path; perform phase analysis on the second interference image by the principal component analysis method to obtain a wrapped phase map including the wrapped phases of different pixel points of the second interference image, and perform phase unwrapping on the wrapped phase map by the path tracking method to obtain the true absolute phase of the pixel points, and then compensate the phase of the first interference image to correct the measurement error, perform image restoration based on the corrected first interference image, and finally obtain the accurate surface topography of the object to be measured, realizing real-time data feedback and error calibration during the detection process, and improving the accuracy and reliability of the topography detection of micro-devices.

[0075] In the second aspect, the present application also provides a method for detecting the topography of a micro-device, which is applied to the Michelson interferometer described above, as Figure 10 shown, the method includes the following steps: Step S601, perform phase analysis on the second interference image by the principal component analysis method to obtain a wrapped phase map, the wrapped phase map includes the wrapped phases of different pixel points of the second interference image, and perform phase unwrapping on the wrapped phase map by the path tracking method to obtain the true absolute phase of different pixel points.

[0076] Step S602, based on the true absolute phase, perform phase compensation on the first interference image, regenerate a uniform interference image, and perform image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured.

[0077] The method for detecting the morphology of the micro-device performs phase analysis on the second interference image through the principal component analysis method, obtains a wrapped phase map including the wrapped phases of different pixel points of the second interference image, and performs phase unwrapping on the wrapped phase map through the path tracking method to obtain the true absolute phase of the pixel points. Furthermore, the phase of the first interference image is compensated to correct the measurement error. Based on the corrected first interference image, image restoration is performed, and finally the accurate surface morphology of the object to be measured is obtained, so as to realize real-time data feedback and error calibration during the detection process, and improve the accuracy and reliability of the detection of the morphology of the micro-device.

[0078] It should be noted that the method for detecting the morphology of the micro-device is applied to the Michelson interferometer described above. Therefore, the specific limitations in the embodiments of the method for detecting the morphology of the micro-device can be referred to the limitations on the Michelson interferometer in the above text, and will not be elaborated here.

[0079] It can be understood that the term "exemplary" used in this document means "as an example, illustration, or description". Any embodiment described as "exemplary" is not necessarily superior to or better than other embodiments and / or does not exclude combining the features of other embodiments. It should be understood that certain features of the present application described in the context of separate embodiments can also be provided in a single embodiment by combination. Conversely, the various features of the present application described in the context of a single embodiment can also be provided separately or by any suitable combination or as any other described embodiment of the present application. In addition, "at least one" means one or more, and "a plurality" means two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not necessarily limit to be different.

[0080] The above-disclosed are only the preferred embodiments of the present application, but they are not intended to limit the scope of the rights of the present application. Those of ordinary skill in the art can understand that: within the spirit and scope of the present application and the appended claims, changes, modifications, substitutions, combinations, and simplifications should all be equivalent replacement methods and still fall within the scope covered by the invention.

Claims

1. A Michelson interferometer, characterized in that, The Michelson interferometer includes: A first Michelson interference optical path, including a first light source, a workbench, a first beam splitter, a first test mirror, and a first image acquisition system. The workbench is used to place the object to be measured. The beam emitted by the first light source is split by the first beam splitter. One beam is reflected onto the surface of the object to be measured, and the other beam is transmitted to the first test mirror. The two beams are reflected back respectively by the object to be measured and the first test mirror, and interfere at the first beam splitter. The first image acquisition system receives the first interference image. A second Michelson interference optical path, including a second light source, a calibration mirror, a second beam splitter, a second test mirror, and a second image acquisition system. The beam emitted by the second light source is split by the second beam splitter. One beam is reflected onto the surface of the calibration mirror, and the other beam is transmitted to the second test mirror. The two beams are reflected back respectively by the calibration mirror and the second test mirror, and interfere at the second beam splitter. The second image acquisition system receives the second interference image. The first Michelson interference optical path and the second Michelson interference optical path share the same piezoelectric ceramic, and the piezoelectric ceramic is configured to control the displacements of the first test mirror and the second test mirror.

2. The Michelson interferometer according to claim 1, wherein The second light source is configured as a helium-neon laser to eliminate the dispersion effect in the second Michelson interference optical path; The Michelson interferometer further includes a processing module, which is configured to perform phase analysis on the second interference image by principal component analysis to obtain a wrapped phase map. The wrapped phase map includes the wrapped phases of different pixel points of the second interference image, and perform phase unwrapping on the wrapped phase map by path tracking method to obtain the true absolute phases of different pixel points; Based on the true absolute phases, the processing module performs phase compensation on the first interference image, regenerates a uniform interference image, and performs image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured.

3. The Michelson interferometer according to claim 2, wherein The processing module performs phase analysis on the second interference image by principal component analysis, including: Based on multiple second interference images collected by the second image acquisition system, constructing an original data matrix; Subtracting the background light intensity from the original data matrix to obtain an alternating component matrix of the interference fringes; Performing singular value decomposition on the alternating component matrix, Based on the singular value decomposition result, performing principal component selection, selecting the residual of the background light intensity as the first principal component, the spatial distribution of the cosine component of the phase information as the second principal component, and the spatial distribution of the sine component of the phase information as the third principal component, Vectorizing the selected principal components, and obtaining the wrapped phase map based on the vectorized result.

4. The Michelson interferometer according to claim 3, wherein The processing module performs phase unwrapping on the wrapped phase map by path tracking method, including: Perform quality assessment on the availability of pixel points in the wrapped phase diagram, obtain the quality factors of pixel points in different regions of the wrapped phase diagram, and generate a quality map based on the quality factors; Construct a priority queue for different regions of the wrapped phase diagram based on the quality factors. According to the priority queue, preferentially perform iterative unwrapping on regions with higher priorities to obtain the true absolute phases of each pixel point in different regions.

5. The Michelson interferometer according to claim 4, characterized in that The processing module is further configured to, when performing phase unwrapping, if the height-phase relationship of the object to be measured satisfies: , add a curvature constraint to the height of the object to be measured, and the curvature constraint is represented by the following formula: ； where λ represents the wavelength of the second light source, h ( x , y ) represents the height of the object to be measured at the coordinate ( x , y ), represents the true absolute phase of the pixel point ( x , y ), and k represents the curvature constraint.

6. The Michelson interferometer according to claim 4, characterized in that The processing module performs phase compensation on the first interference image in the first Michelson interference optical path based on the true absolute phase to regenerate a uniform interference image, including: Calculate the phase compensation values of different pixel points through the following formula according to the true absolute phases of each pixel point: ； In the formula, is the standard displacement of the piezoelectric ceramic controller, , is the actual displacement of the piezoelectric ceramic, λ represents the wavelength of the second light source, represents the true absolute phase of the pixel point, Based on the phase compensation values, perform phase compensation on the pixel points at the corresponding coordinates in the first interference image to regenerate a uniform interference image.

7. The Michelson interferometer according to claim 6, characterized in that The processing module performs phase compensation on the pixel points at the corresponding coordinates in the first interference image through the following formula: ； In the formula, represents the gray value of the compensated pixel point, represents the DC component of the background light intensity in the first Michelson interference optical path, represents the modulation amplitude of the first Michelson interference optical path, represents the gray value of the pixel point of the uncompensated first interference image, represents the standard displacement of the piezoelectric ceramic controller.

8. The Michelson interferometer according to claim 7, characterized in that The processing module is further configured to: generate interference curves of different pixel points based on the corresponding pixel points in multiple uniform interference images, Select some of the interference curves as normal interference curves, and generate a reference distribution based on the selected normal interference curves; Adopt a two-sample normality test to screen out interference curves with curve distributions the same as or similar to the reference distribution from the remaining interference curves, generate a new data set, and perform image restoration based on the new data set to obtain the surface topography of the object to be measured.

9. The Michelson interferometer according to claim 1, characterized in that The first light source is configured as white light.

10. A method for detecting the morphology of a micro-device, characterized in that, The method applies the Michelson interferometer according to any one of claims 1 to 9, and the method includes the following steps: Perform phase analysis on the second interference image through principal component analysis to obtain a wrapped phase diagram, where the wrapped phase diagram includes the wrapped phases of different pixel points in the second interference image, and perform phase unwrapping on the wrapped phase diagram through a path tracking method to obtain the true absolute phases of different pixel points; Perform phase compensation on the first interference image based on the true absolute phase to regenerate a uniform interference image, and perform image restoration based on the regenerated uniform interference image to obtain the surface topography of the object to be measured.

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