A method and system for measuring the three-dimensional morphology of metal hydrophobic surfaces based on white light microinterference

Abstract

The present invention relates to a method and system for measuring the three-dimensional topography of a metal hydrophobic surface based on white light microinterference, which belongs to the field of precision measurement, comprising: first measuring a sample, scanning the sample surface, and synchronously collecting a sequence of white light interference images containing surface profile information; using a bicubic interpolation algorithm to interpolate the collected white light interference pattern group to construct a high-resolution interference image sequence; subsequently, the time-frequency domain interference signal is analyzed by fast Fourier transform, and noise interference is effectively suppressed by combining filtering technology to accurately extract the envelope curve of the interference signal; and then the envelope peak is Gaussian fitted and the peak coordinates are located using the least squares method, and finally a high-precision three-dimensional surface topography is reconstructed. The present invention complements the advantages of the bicubic interpolation algorithm and the fast Fourier transform method, significantly improving the lateral resolution while maintaining the longitudinal resolution, and providing an effective technical means for the accurate characterization of the three-dimensional topography of the metal hydrophobic surface structure.

Description

Technical Field

[0001] The present invention relates to a method and system for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference, and belongs to the technical field of precision measurement. Background Art

[0002] Hydrophobic metal surfaces hold a crucial position in the field of functional materials and engineering. Their primary application is in self-cleaning intelligent surface technology, offering innovative solutions for marine equipment corrosion protection and spacecraft de-icing, with profound implications for energy conservation, emission reduction, and the development of biomedical devices. The geometric precision of their surface microstructures directly determines the stability and durability of their hydrophobic properties. Therefore, precise characterization of the three-dimensional morphology of hydrophobic metal surfaces is of critical scientific and engineering significance.

[0003] White light micro-interference technology, with its non-contact, large field of view, and high vertical resolution, can achieve higher-precision quantitative measurement of micro-nano-level surface roughness and three-dimensional morphological features, making it an indispensable detection method in the field of ultra-precision detection. However, due to the diffraction limit, the lateral resolution of existing equipment is generally limited to half a wavelength, making it difficult to accurately capture the key morphological features of the subwavelength scale in micro-nano structures. During the detection process, it is affected by objective factors such as light source non-uniformity and environmental vibration, which can cause distortion of the interference signal, resulting in errors in the detection of the envelope peak position, thereby affecting the accuracy of the three-dimensional morphology measurement. These technical defects restrict the accurate evaluation of hydrophobic surface performance and process optimization. Existing detection methods are difficult to meet the needs of accurate correlation analysis between microstructure morphology and functional characteristics. Summary of the Invention

[0004] In response to the above-mentioned defects or improvement needs of the prior art, the present invention provides a method for measuring the morphology of metal hydrophobic surfaces based on white light microscopy interferometry, the purpose of which is to improve the lateral resolution while suppressing the interference of environmental noise on the envelope peak positioning, thereby realizing high-precision morphology measurement of metal hydrophobic surfaces based on white light microscopy interferometry.

[0005] The technical solutions of the present invention are as follows:

[0006] The present invention proposes a method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference, comprising the following steps:

[0007] S1. Operate the white light micro-interference system to measure the sample, use the piezoelectric ceramic (PZT) nanopositioning actuator to longitudinally scan the sample surface, and synchronously collect a sequence of white light interference images containing surface profile information;

[0008] Preferably, the white light microscopic interference system includes a platform, on which the object to be measured is placed, and a CCD, an imaging mirror, a spectrometer, a piezoelectric ceramic PZT, and a Mirau interference microscope objective are arranged from top to bottom. A light source and a collimating mirror are provided on one side of the spectrometer. The PZT is connected to the computer through a PZT controller, and the CCD is connected to the computer. The light emitted by the light source is reflected by the spectrometer and enters the Mirau interference microscope objective. In the objective, the light is divided into reference light and measurement light through a thin film spectrometer. The measurement light is transmitted and returned after reflection from the sample, and the reference light is reflected by the spectrometer. After reflection, the two beams of light are recombined in the objective and interfere with each other. The interfered light beam finally passes through the imaging mirror and is received by the CCD to form an image.

[0009] Preferably, for any pixel in the image, the interference light intensity distribution can be expressed as:

[0010] (1)

[0011] Where, I bg is the background light intensity, g ( z - h ) is the Gaussian envelope of the white light interference signal, γ is the fringe visibility, λ0 is the central wavelength of the light source, z is the coordinate position, h is the height information of the test surface, α add is the additional phase caused by reflection.

[0012] S2. Use the bicubic interpolation algorithm to interpolate the collected white light interferogram group to construct a high-resolution interference image sequence, specifically including:

[0013] Establish the coordinate mapping relationship between the pixel points in the target image B (the number of pixels is M*N) and the original image A (the number of pixels is m*n), according to the scaling factor K = M / m Determine the target pixel P ( X , Y ) in the original image ( x + u , y + v ), where x, y represent the integer part, and u, v represent the decimal part;

[0014] Select ( x + u , y + v ) around 16 pixels a ( i , j ) as interpolation primitives,i , j =0,1,2,3, calculate the weights of 16 pixels based on the BiCubic function. The expression of the BiCubic function is:

[0015] (2)

[0016] Among them, the parameter r represents the distance from the pixel to point P;

[0017] Calculate the horizontal and vertical coordinate weights of the pixel points respectively, and add up the 16 pixels to get the pixel value of the target image B(X,Y):

[0018] (3)

[0019] in, a ij is the value of the pixel in the original image, W ( i ) is the horizontal axis weight, W ( j ) is the vertical axis weight.

[0020] S3. Analyze and filter the interference signal in the time domain and frequency domain using the Fourier transform method to extract the envelope curve of the interference signal, specifically including:

[0021] The expression of white light interference signal is shown in formula (1);

[0022] right I ( z ) performs fast Fourier transform to filter out DC background noise and obtain only the AC part of the information carrying the height information of the sample to be measured. Its spectrum is decomposed into:

[0023] (4)

[0024] Where δ(k) represents the impulse function, G(k) is the Fourier transform of g(zh), h is the height information of the test surface, j is the imaginary unit, * represents convolution, the spatial angular frequency k=2π / z, and 4π / λ0 represents the carrier angular frequency of the signal;

[0025] Extract the positive frequency part of the spectrum and move it back to the center of the amplitude-frequency curve, and obtain the interference signal after removing the background noise signal through inverse Fourier transform. , that is, the envelope curve, its expression is:

[0026] (5).

[0027] S4. Determine the envelope peak position by least squares Gaussian fitting based on the envelope curve, and then calculate the sample morphology characteristics to achieve high-precision morphology measurement.

[0028] Specifically include:

[0029] S41, establish the envelope peak Gaussian model, use the nonlinear least squares algorithm to fit the envelope curve to the Gaussian function, and construct the Gaussian function f ( z - z 0), the expression is:

[0030] (6)

[0031] Where A is the amplitude, σ is the half-height width, z is the coordinate position, z 0 is the envelope peak position;

[0032] S42, iteratively optimize the parameters, obtain the envelope peak position, and optimize {A, z 0, σ} parameter set to minimize the residual sum of squares. The residual formula is:

[0033] (7)

[0034] Where, n is the number of points in the envelope curve (i.e. the number of images in the image sequence), The envelope curve obtained by Fourier transform method is s The value of a point, f ( z s ) is the Gaussian envelope curve fitted in the first s The value of a point;

[0035] S43, optimize the z The value 0, that is, the envelope peak position, is substituted into the space-height conversion matrix calibrated by the system:

[0036] h =C· z 0 (8)

[0037] Where C is the scaling factor, which represents the peak position z 0 and test surface height data h The mapping relationship between them is used to obtain the three-dimensional morphology coordinate data, generate the sample morphology, and complete the high-precision measurement of the hydrophobic surface morphology.

[0038] The present invention is a three-dimensional morphology measurement method for metal hydrophobic surfaces based on white light microinterference. By complementing the advantages of bicubic interpolation and fast Fourier transform, the original white light interference grayscale image is super-resolution processed, significantly improving the lateral resolution while maintaining the vertical resolution. The envelope peak position is extracted by applying fast Fourier transform to the interference signal, and then the morphology height information is calculated to achieve high-precision morphology measurement, providing an effective technical means for the accurate characterization of the three-dimensional morphology of metal hydrophobic surface structures.

[0039] A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps of the method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference as described in the first aspect of the present invention.

[0040] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference as described in the first aspect of the present invention are implemented.

[0041] The beneficial effects of the present invention are:

[0042] 1. The present invention combines bicubic interpolation with white light microscopy to effectively improve lateral resolution and obtain more lateral detail information of the sample.

[0043] 2. The present invention adopts a three-dimensional topography reconstruction method based on fast Fourier transform, which can effectively suppress stray noise signals and extract phases in the measurement of metal hydrophobic surfaces, thereby improving measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a schematic structural diagram of the white light interferometry system used in the present invention;

[0045] Figure 2 A flow chart of a method for measuring the hydrophobic surface morphology of metals based on white light microinterferometry provided in an embodiment of the present invention;

[0046] Figure 3 Schematic diagram of the bicubic interpolation process in the present invention;

[0047] Figure 4 A schematic diagram of the three-dimensional morphology after processing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] To facilitate understanding of the objectives, technical solutions, and advantages of the present invention, the present invention is further described below with reference to specific illustrations and examples. It should be understood that the specific examples described herein are intended only to illustrate the present invention and are not intended to limit it. Furthermore, the technical features involved in the various embodiments of the present invention described below may be combined as long as they do not conflict with each other.

[0049] Example 1

[0050] A method for measuring the three-dimensional morphology of metal hydrophobic surfaces based on white light microinterference, such as Figure 2 As shown, the following steps are included:

[0051] S1. Operate the white-light micro-interference system to measure the sample, use the piezoelectric ceramic (PZT) nanopositioning actuator to longitudinally scan the sample surface, and simultaneously acquire a sequence of white-light interferometry images containing surface profile information; including:

[0052] The interference image sequence P={p1,p2,…,pn} with three-dimensional information of the sample surface is obtained by using a white light interferometry system, where 1,2,…,n is the corresponding image sequence. The structure of the white light interferometry measurement system is as follows: Figure 1 As shown, the white light microscopic interference system includes a platform, on which the object to be measured is placed, and a CCD, an imaging mirror, a spectroscope, a piezoelectric ceramic PZT, and a Mirau interference microscope objective are arranged from top to bottom. A light source and a collimating mirror are provided on one side of the spectroscope. The PZT is connected to a computer through a PZT controller, and the CCD is connected to the computer. The light emitted by the light source is reflected by the spectroscope and enters the Mirau interference microscope objective. In the objective, the light is divided into reference light and measurement light by a thin film spectrometer. The measurement light is transmitted and returned after reflection by the sample, while the reference light is reflected by the spectrometer. After reflection, the two beams of light are recombined in the objective and interfere with each other. The interfered light beam finally passes through the imaging mirror and is received by the CCD to form an image.

[0053] For any pixel in the image, the interference light intensity distribution can be expressed as:

[0054] (1)

[0055] Where, I bg is the background light intensity, g ( z - h ) is the Gaussian envelope of the white light interference signal, γ is the fringe visibility, λ0 is the central wavelength of the light source, z is the coordinate position, h is the height information of the test surface, α add is the additional phase caused by reflection.

[0056] S2. Use the bicubic interpolation algorithm to interpolate the collected white light interferogram group to construct a high-resolution interference image sequence, specifically including:

[0057] S21, establish image mapping relationship:

[0058] Assume that the size of a single frame in the original acquired image sequence A is m×n pixels, and after the scaling factor K is multiplied, the target image sequence B (M×N pixels, K = M / m ). According to the scaling factor K = M / m Determine the target pixel P ( X , Y ) in the original image A ( x + u , y + v ), where x, y represent the integer part, and u, v represent the decimal part;

[0059] S22, construct the interpolation function:

[0060] like Figure 3 As shown, with the mapping point P as the center, select ( x + u , y + v ) 16 pixels around a ( i , j )( i , j =0,1,2,3) (4×4 neighborhood pixel matrix) is used as the interpolation primitive, and the weight of each pixel is calculated based on the bicubic interpolation (BiCubic) function. The weights of 16 pixels are calculated. The expression of the BiCubic function is:

[0061] (2)

[0062] Among them, the parameter r represents the distance from the pixel to point P.

[0063] S23, calculate the bidirectional weight, Figure 3 For the 16 neighborhood points shown, their pixel value contribution weights to the target pixel point P are calculated along the X and Y directions respectively. Based on the offset (u, v) in step S21, the row and column weight coefficient sets are calculated according to the neighborhood point row index i (i=0,1,2,3) in the horizontal and vertical directions:

[0064] Row weight coefficient set: {W(|0-(1+u)|), W(|1-(1+u)|), W(|2-(1+u)|), W(|3-(1+u)|)};

[0065] Column weight coefficient set: {W(|0-(1+v)|), W(|1-(1+v)|), W(|2-(1+v)|), W(|3-(1+v)|)};

[0066] Among them, each weight value is generated by the BiCubic function W(x), and finally forms a 4×4 two-dimensional weight matrix for pixel value reconstruction.

[0067] S24, calculate the pixel value of (X, Y), and perform weighted superposition of 16 pixels to obtain the pixel value of the target image B(X, Y):

[0068] (3)

[0069] in, a ij is the value of the pixel in the original image, W ( i ) is the horizontal axis weight, W ( j ) is the vertical axis weight.

[0070] S3. Analyze and filter the interference signal in the time domain and frequency domain using the Fourier transform method to extract the envelope curve of the interference signal, specifically including:

[0071] The expression of white light interference signal is shown in formula (1).

[0072] S31, frequency domain signal decomposition, axial scanning interference signal I ( z ) performs fast Fourier transform to filter out DC background noise and obtain only the AC part of the information carrying the height information of the sample to be measured, and obtains the spectrum distribution, which is decomposed into:

[0073] (4)

[0074] Where δ(k) represents the impulse function, G(k) is the Fourier transform of g(zh), h is the height information of the test surface, j is the imaginary unit, * represents convolution, the spatial angular frequency k=2π / z, and 4π / λ0 represents the carrier angular frequency of the signal.

[0075] S32, frequency domain filtering and signal demodulation:

[0076] The positive frequency part of the spectrum of formula (4) is extracted by bandpass filter and moved back to the center of the amplitude-frequency curve, and the time domain envelope signal is reconstructed by inverse Fourier transform. , realize DC noise filtering and carrier phase demodulation, and remove the interference signal of background noise signal , that is, the envelope curve, its expression is:

[0077] (5).

[0078] S4. Determine the envelope peak position by least squares Gaussian fitting based on the envelope curve, and mathematically model the envelope waveform using a least squares Gaussian fitting algorithm based on nonlinear regression analysis; locate the envelope peak position coordinates by iteratively optimizing the amplitude, center position, and half-width of the Gaussian function; combine the system-calibrated space-height conversion matrix to convert the acquired peak position sequence into three-dimensional morphological coordinate data, and then generate the sample morphological features to achieve high-precision morphological measurement.

[0079] Specifically include:

[0080] S41, establish the envelope peak Gaussian model, use the nonlinear least squares algorithm to fit the envelope curve to the Gaussian function, and construct the Gaussian function f ( z - z 0), the expression is:

[0081] (6)

[0082] Where A is the amplitude, σ is the half-height width, z is the coordinate position, z 0 is the envelope peak position;

[0083] S42, iteratively optimize the parameters, obtain the envelope peak position, and optimize {A, z 0, σ} parameter set to minimize the residual sum of squares. The residual formula is:

[0084] (7)

[0085] Where, n is the number of points in the envelope curve (i.e. the number of images in the image sequence), The envelope curve obtained by Fourier transform method is s The value of a point, f ( z s ) is the Gaussian envelope curve fitted in the first s The value of a point;

[0086] S43, optimize the z The value 0, that is, the envelope peak position, is substituted into the space-height conversion matrix calibrated by the system:

[0087] h =C· z 0 (8)

[0088] Where C is the scaling factor, which represents the peak position z 0 and test surface height data h The mapping relationship between them is used to obtain the three-dimensional morphological coordinate data, generate the sample morphology, and complete the high-precision measurement of the hydrophobic surface morphology. Figure 4 shown.

[0089] The present invention is a three-dimensional morphology measurement method for metal hydrophobic surfaces based on white light microinterference. By complementing the advantages of bicubic interpolation and fast Fourier transform, the original white light interference grayscale image is super-resolution processed, significantly improving the lateral resolution while maintaining the vertical resolution. The envelope peak position is extracted by applying fast Fourier transform to the interference signal, and then the morphology height information is calculated to achieve high-precision morphology measurement, providing an effective technical means for the accurate characterization of the three-dimensional morphology of metal hydrophobic surface structures.

[0090] Example 2

[0091] A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps of the method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference as described in Example 1.

[0092] Example 3

[0093] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of the method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference as described in Example 1 are implemented.

Claims

1. A method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference, characterized in that: The steps include: S1. Operate the white light micro-interference system to measure the sample, use the piezoelectric ceramic nanopositioning actuator to longitudinally scan the sample surface, and synchronously collect a sequence of white light interference images containing surface profile information; For any pixel in the image, the interference light intensity distribution is expressed as: （1） Where, I bg is the background light intensity, g ( z - h ) is the Gaussian envelope of the white light interference signal, γ is the fringe visibility, λ0 is the central wavelength of the light source, z is the coordinate position, h is the height information of the test surface, α add is the additional phase caused by reflection; S2. Use bicubic interpolation algorithm to interpolate the collected white light interferogram group to construct a high-resolution interference image sequence; S3. Analyzing and filtering the interference signal in the time domain and frequency domain using the Fourier transform method to extract the envelope curve of the interference signal; The expression of white light interference signal is shown in formula (1); right I ( z ) performs fast Fourier transform to filter out DC background noise and obtain only the AC part of the information carrying the height information of the sample to be measured. Its spectrum is decomposed into: （4） Where δ(k) represents the impulse function, G(k) is the Fourier transform of g(zh), h is the height information of the test surface, j is the imaginary unit, * represents convolution, the spatial angular frequency k=2π / z, and 4π / λ0 represents the carrier angular frequency of the signal; The positive frequency part of the spectrum is extracted by a bandpass filter and moved back to the center of the amplitude-frequency curve. The interference signal with the background noise signal removed is obtained by inverse Fourier transform. , that is, the envelope curve, its expression is: （5）； S4. Determine the envelope peak position by least squares Gaussian fitting based on the envelope curve, and then calculate the sample morphology characteristics to achieve high-precision morphology measurement; Step S4 specifically includes: S41, establish the envelope peak Gaussian model, use the nonlinear least squares algorithm to fit the envelope curve to the Gaussian function, and construct the Gaussian function f ( z - z 0), the expression is: （6） Where A is the amplitude, σ is the half-height width, z is the coordinate position, z 0 is the envelope peak position; S42, iteratively optimize the parameters, obtain the envelope peak position, and optimize {A, z 0, σ} parameter set to minimize the residual sum of squares. The residual formula is: （7） Where, n is the number of points in the envelope curve, The envelope curve obtained by Fourier transform method is s The value of a point, f ( z s ) is the Gaussian envelope curve fitted in the first s The value of a point; S43, optimize the z The value 0, that is, the envelope peak position, is substituted into the space-height conversion matrix calibrated by the system: h =C· z 0（8） Where C is the scaling factor, which represents the peak position z 0 and test surface height data h The mapping relationship between them is used to obtain the three-dimensional morphology coordinate data, generate the sample morphology, and complete the high-precision measurement of the hydrophobic surface morphology.

2. The method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference according to claim 1, characterized in that: In step S1, the white light microscopy interferometry system includes a platform, on which the object to be measured is placed. A CCD, an imaging mirror, a spectroscope, a piezoelectric ceramic PZT, and a Mirau interferometry microscope objective are arranged from top to bottom. A light source and a collimator are provided on one side of the spectroscope. The PZT is connected to a computer through a PZT controller, and the CCD is connected to the computer.

3. The method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference according to claim 1, wherein: Step S2 specifically includes: Establish the coordinate mapping relationship between the target image B and the pixel points in the original image A. The number of pixels in the target image B is M*N, and the number of pixels in the original image A is m*n. According to the scaling factor K = M / m Determine the target pixel P ( X , Y ) in the original image ( x + u , y + v ), where x, y represent the integer part, and u, v represent the decimal part; Select ( x + u , y + v ) around 16 pixels a ( i , j ) as interpolation primitives, i , j =0,1,2,3, calculate the weights of 16 pixels based on the BiCubic function. The expression of the BiCubic function is: （2） Among them, the parameter r represents the distance from the pixel to point P; Calculate the horizontal and vertical coordinate weights of the pixel points respectively, and add up the 16 pixels to get the pixel value of the target image B(X,Y): （3） in, a ij is the value of the pixel in the original image, W ( i ) is the horizontal axis weight, W ( j ) is the vertical axis weight.

4. A computer-readable storage medium, characterized in that A program is stored thereon, and when the program is executed by a processor, the steps of the method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference as claimed in any one of claims 1 to 3 are implemented.

5. An electronic device, characterized in that: The invention comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for measuring the three-dimensional morphology of a metal hydrophobic surface based on white light microinterference as claimed in any one of claims 1 to 3 are implemented.

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