Method and system for accurately measuring surface roughness of object

Abstract

The invention provides a method and system for accurately measuring the surface roughness of an object, and the method comprises the steps: S1, scanning the surface of a sample with a particle beam through experimental equipment, and collecting an experimental diffraction pattern; calculating a simulation standard diffraction pattern according to the crystal type; s2, registering the experimental diffraction pattern with a standard diffraction pattern to obtain a crystal orientation angle and a coordinate value of a projection center corresponding to the experimental diffraction pattern, forming a lattice point network with uniform intervals on the surface of the sample by adopting uniform lattice point hypothesis and linear fitting of all projection centers, and obtaining the crystal orientation angle of the experimental diffraction pattern by adopting a four-parameter integrated registration method. And calculating each diffraction picture to obtain fluctuation information of the surface of the sample. The invention provides the method for measuring the surface roughness of the sample by using the particle diffraction technology, the measurement precision is higher and reaches the micron level, and the method is non-contact measurement and has smaller influence on the surface of the sample.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of image processing and the field of microscopy, in particular, to a method and system for accurately measuring the roughness of an object surface. BACKGROUND

[0002] Scanning electron microscope (SEM) is a versatile instrument. The electron backscatter diffraction (EBSD) technique, which is based on SEM, is compact and can quickly provide information about crystal type, orientation, grain size, deformation degree, etc. It is widely used in the fields of materials and geology. The advantages of EBSD technique also include non-destructive, easy automation, high resolution, high speed and rich results. This specification takes the electron backscatter diffraction technique as an example to introduce a new application of particle diffraction technique, i.e. measuring the surface roughness of a crystal sample.

[0003] The surface roughness of a workpiece is generally formed by the processing method used and other factors, such as the friction between the tool and the surface of the workpiece during processing. Surface roughness has a wide range of effects, and it is closely related to the fitting properties, wear resistance, fatigue strength, contact stiffness, vibration and noise of mechanical parts, and has an important influence on the service life, aesthetics and reliability of mechanical products. In addition, the roughness of a scientific experimental sample will also affect the measurement results, for example, inaccurate roughness data will cause errors in plane stress.

[0004] In the electron backscatter diffraction technique, the electron beam is accelerated and shot into the surface of the sample. After complex interaction with the atoms constituting the sample, part of the electrons are finally shot out of the surface of the sample, and the angle of electron emission and the spacing between the crystal planes of the sample meet the Bragg diffraction equation, thereby forming a characteristic electron diffraction pattern on the screen, also known as a Kikuchi pattern or diffraction pattern. Please refer to patent document CN105651792A for a scanning electron microscope transmission electron Kikuchi diffraction device and analysis method.

[0005] The position and direction of the Kikuchi pattern are most closely related to six parameters, which are the crystal direction angle representing the relative rotation of the crystal coordinate system and the sample coordinate system, and the three-dimensional space coordinates of the action volume relative to the screen (i.e. the projection center, see Figure 1 The recently emerging integrated digital image correlation (IDIC) technique for electron backscatter diffraction (EBSD) calibration provides an accurate method for measuring the crystal direction and the position of the projection center, and also creates the possibility for a new method for measuring the surface roughness of an object.

[0006] There are some mature roughness measurement methods, but such methods are greatly affected by the wavelength of light, and have limited spatial resolution, such as confocal microscopy. Compared with scanning electron microscopy (SEM), atomic force microscopy (AFM) has small imaging range, slow speed, and is greatly affected by the probe, and the scanning error cannot be ignored. In addition, some newer measurement methods include focused ion beam tomography, which is simple and intuitive in principle, but is a lossy measurement and time-consuming. The gray scale distribution of the BSE images collected by multiple detectors also shows roughness, but this method cannot be quantified. In addition to crystallographic orientation, EBSD can also reveal other information about the sample surface, such as roughness. For example, the background gray scale analysis of electron diffraction patterns can reflect the surface roughness. This method has been successfully tested on a spherical object, but further verification is still needed on more conventional surface variations. In plastic deformation, crystal rotation measured by a series of EBSD can also predict roughness changes. However, this method is not sensitive to fluctuations caused by dislocation slip because they do not involve crystal rotation. Therefore, a method for accurately measuring the surface roughness of an object by scanning electron microscopy is valuable. SUMMARY

[0007] In view of the defects in the prior art, the purpose of the present application is to provide a method and system for accurately measuring the surface roughness of an object.

[0008] According to the method for accurately measuring the surface roughness of an object provided by the present application, the method comprises the following steps:

[0009] Step S1: Scanning the sample surface by the experimental equipment with a particle beam, and collecting experimental diffraction patterns; calculating a simulated standard diffraction pattern according to the crystal type;

[0010] Step S2: Registering the experimental diffraction patterns with the standard diffraction patterns to obtain the crystal orientation angle and the projection center coordinate value corresponding to the experimental diffraction patterns, assuming a uniform grid point, linearly fitting all the projection centers to form a grid point network with uniform spacing on the sample surface, and calculating the fluctuation information of the sample surface by using a four-parameter integrated registration method for each diffraction picture.

[0011] Preferably, in the step S2:

[0012] The obtained projection center coordinates are normalized, the multiple projection centers of the experimental diffraction patterns scanned in the entire diffraction experiment are collected, the projection centers are uniformly fitted according to the geometric relationship of the scanning experiment, all the projection centers are assumed to form a grid point network with uniform spacing on the sample surface, and linear fitting is performed:

[0013] X L = dX + eY + f, Y L = gX + iY + j, Z L = kX + lY + m

[0014] wherein X and Y are the transverse and longitudinal indices of the diffraction pattern, X L ,Y L ,Z L are the linearized projection center coordinate values, d, e, f, g, i, j, k, l, m are fitting parameters obtained using a fitting algorithm; Z * -Z L is the surface roughness of the sample at the (X, Y) position;

[0015] On the basis of the normalized projection center coordinate values, according to the geometric relationship including the sample tilt angle, the detector tilt angle and the particle beam direction, the sample roughness h is established in relation to Y * -Y L and Z * -Z L , and the six parameters of the sought crystal orientation angle and the coordinate values are reduced to four parameters of the crystal orientation angle and the roughness:

[0016] Z * =Z L +δZ * =Z L +h

[0017] Y * =Y L +δY * =Y L +h tanα

[0018] wherein Y * ,Z * are the projection center coordinates in the sample coordinate system, δ represents the change of a physical quantity, and α is the tilt angle of the sample relative to the incident electron beam.

[0019] Preferably, the experimental diffraction pattern is registered with the standard diffraction pattern, the difference between the two is characterized by a mean square error objective function during the registration process, the crystal orientation angle and the surface roughness of the object are taken as the parameters P to be optimized, and the objective function is minimized until convergence to obtain the corrected parameters;

[0020] In the registration step, the objective function Θ is

[0021]

[0022] wherein ROI is the pattern region to be registered, ω(x) is the weight of pixel x of the diffraction pattern in the registration process, g(x) is the two-dimensional projection picture of the standard diffraction pattern G(u), g(x) = G[u(x, P)], and f(x) is the experimental diffraction pattern collected in the particle diffraction experiment;

[0023] The partial derivatives of the objective function with respect to the parameters are calculated:

[0024]

[0025] where P collectively represents the four parameters, i.e. the crystal orientation and the surface roughness of the object, u is the coordinate of the standard diffraction pattern projected on the equatorial plane by a sphere, is the gradient of the standard diffraction pattern projected on the u space; i is the serial number of the parameter;

[0026] The projection center after the fixed normalization processing is fixed, and the Euler angle and the sample roughness are taken as the target parameters to re-register.

[0027] Preferably, the experimental diffraction pattern is registered with the standard diffraction pattern, and the difference between the standard diffraction pattern and the experimental diffraction pattern is characterized by a mean square error in the registration process; the registration algorithm is divided into two kinds, i.e. a six-parameter method and a four-parameter method, and the calibrated parameters are and wherein is the crystal orientation, (x * ,y * ,z * ) is the projection center of the diffraction pattern, h is related to the surface roughness of the object, and the target function is minimized until convergence to obtain the corrected Euler angle and the surface roughness of the object;

[0028] (x * ,y * ,z * ) and h have a geometric relationship, which will be described in detail below:

[0029] The coordinates of the EBSD detector reference system are marked as (x, y, z), and the coordinates of the sample reference system are marked as (X, Y, Z); in the detector reference system, the coordinates of the projection center PC are (x * ,y * ,z * ); in the sample reference system, the coordinates of PC are (X * ,Y * ,Z * ); the mutual conversion of (x, y, z) and (X, Y, Z) is completed by rigid movement of three-dimensional space:

[0030] (X,Y,Z) T =Q β (x,y,z) T

[0031] wherein Q β is a rotation matrix, and β represents the tilt angle of the sample relative to the EBSD probe; Q β The specific expression is as follows:

[0032]

[0033] The fluctuation of the registered PC coordinates is related to the surface roughness of the sample. When the EBSD acquisition is performed by scanning the electron beam, the sample surface flatness in the ideal state meets the preset standard, and the obtained pattern projection center coordinate values (X * ,Y * ,Z * ) are linearly and uniformly distributed; when the actual sample surface has roughness variation, when the electron beam is targeted at the point (X L ,Y L ,0), the electron beam is intercepted by the sample surface at (X * ,Y * ,Z * ); (X * ,Y * ,Z * ) is obtained by linearly converting (x * ,y * ,z * ):

[0034] (X * ,Y * ,Z * ) T =Q β (x * ,y * ,z * ) T

[0035] H(X,Y) represents the roughness function of the sample, taking X and Y as parameters; the slope of the surface roughness of the sample is limited, H is constant within a δY * distance, and is approximated as follows:

[0036]

[0037] wherein X L ,Y L are defined as follows: collect the projection centers of the experimental diffraction pattern scanned in the entire diffraction experiment, and perform uniform grid normalization processing on the projection centers according to the scanning geometry; the uniform grid fitting means that all projection centers are assumed to form a grid network with uniform spacing on the sample surface, and the projection center coordinate values are linearly fitted to minimize ∑(X * -X L ) 2 , ∑(Y * -Y L ) 2 , ∑(Z * -Z L ) 2 ; let

[0038] Re-registering with the crystal orientation angle as a variable, the total number of parameters of the integrated registration method is reduced to four

[0039] Variable α, X L , Y L , Z L Obtained by preliminary registration by IDIC-EBSD, and the parameter list of the four-parameter method is Two variables are less than the IDIC-EBSD registration method of six parameters.

[0040] Preferably, the registration step is repeated: the projection center obtained by linear fitting is fixed, and the crystal orientation angle and the sample surface roughness are re-registered and calculated as variables;

[0041] The experimental diffraction pattern includes a Kikuchi map collected by an electron backscattering diffraction (EBSD) scan, and the standard diffraction pattern includes a Kikuchi standard diffraction pattern obtained according to a crystal structure simulation;

[0042] The registration step establishes a mathematical relationship between the parameters and the projection coordinates of the experimental diffraction pattern on the standard diffraction pattern, and uses an algorithm to minimize the objective function;

[0043] The forward accumulation Gauss-Newton algorithm is used to optimize the objective function, a linear equation set is established, and the change amount {δP} of each iteration of the parameter is provided:

[0044] [M]{δP}={γ}

[0045] The expression of the Hessian matrix [M] in each iteration element M ij is as follows:

[0046]

[0047] Wherein, ψ is the Jacobian matrix of the coordinate u on the equatorial plane after spherical projection on each parameter:

[0048]

[0049] The expression of each element in {γ} is as follows:

[0050]

[0051] {δP} is the change amount of each parameter in each iteration process, and the calculation is ended when it is lower than the set value, otherwise the next iteration is performed:

[0052] {P (n)}={P (n-1)}+{δP(n)}。

[0053] According to the present application, a system for precisely measuring the surface roughness of an object is provided, and the method for precisely measuring the surface roughness of an object is executed, comprising:

[0054] a pattern acquisition module, which acquires an experimental diffraction pattern of a crystal obtained by particle diffraction, and acquires a standard diffraction pattern corresponding to the crystal;

[0055] a six-parameter registration module, which registers the standard diffraction pattern and the experimental diffraction pattern, and in the registration process, a target function is used to represent the difference between the standard diffraction pattern and the experimental diffraction pattern, and the coordinates of the projection center and the Euler angles are used as the parameters to be sought, and the target function is minimized to converge, so as to obtain the corrected projection center and Euler angles;

[0056] a normalization module, which performs uniform grid fitting normalization processing on the coordinates of the diffraction image projection center, so as to obtain the sample surface roughness;

[0057] a four-parameter registration module, which establishes a geometric relationship between the sample roughness and the fluctuation of the diffraction image projection center, and uses the Euler angles and the sample surface roughness as the four parameters to be sought, and registers the simulated standard diffraction pattern and the experimental diffraction pattern, so as to obtain the surface roughness data with improved accuracy.

[0058] Preferably, the obtained projection center coordinates are subjected to normalization processing, and a plurality of projection centers of the experimental diffraction pattern scanned in the entire diffraction experiment are collected, and the projection centers are subjected to uniform grid fitting according to the geometric relationship of the scanning experiment, and the uniform grid assumes that all the projection centers form a grid network with uniform spacing on the sample surface, and linear fitting is performed:

[0059] X L =dX+eY+f,Y L =gX+iY+j,Z L =kX+lY+m

[0060] In the formula, X and Y are the horizontal and vertical numbers of the diffraction pattern, X L ,Y L ,Z L are the projection center coordinate values after linearization processing, and d, e, f, g, i, j, k, l, and m are fitting parameters obtained by using a fitting algorithm; and Z * -Z L is the surface roughness of the sample at the (X, Y) position;

[0061] On the basis of the normalization processing on the projection center coordinate values, the sample roughness h is established according to the geometric relationship including the sample inclination angle, the detector inclination angle, and the particle beam direction, and Y * -YL and Z * -Z L By the connection of the two, the six parameters of the sought crystal orientation angle and the coordinate value are reduced to four parameters of the crystal orientation angle and the roughness:

[0062] Z * = Z L + δZ * = Z L + h

[0063] Y * = Y L + δY * = Y L + h tan α

[0064] wherein Y * , Z * are the projection center coordinates in the sample coordinate system, δ represents the change of the physical quantity, and α is the tilt angle of the sample relative to the incident electron beam.

[0065] Preferably, the experimental diffraction pattern is aligned with the standard diffraction pattern, the difference between the two is characterized by a mean square error objective function during the alignment process, the crystal orientation angle and the object surface roughness are taken as the parameters P to be optimized, and the objective function is minimized until convergence to obtain the corrected parameters;

[0066] In the alignment step, the objective function Θ is

[0067]

[0068] In the formula, ROI is the pattern area to be aligned, ω(x) is the weight of pixel x of the diffraction pattern in the alignment process, g(x) is the two-dimensional projection picture of the standard diffraction pattern G(u), g(x) = G[u(x, P)], and f(x) is the experimental diffraction pattern collected by the particle diffraction experiment;

[0069] The partial derivative of the objective function with respect to each parameter is calculated:

[0070]

[0071] In the formula, P collectively represents the four parameters, i.e., the crystal orientation angle and the object surface roughness, u is the coordinate of the standard diffraction pattern projected on the equatorial plane by the spherical projection, is the gradient of the standard diffraction pattern after the spherical projection in the u space; and i is the serial number of the parameter.

[0072] The projection center after the normalization processing is fixed, and the Euler angle and the sample roughness are taken as the target parameters to perform the alignment again.

[0073] Preferably, the experimental diffraction pattern is registered with the standard diffraction pattern, and the difference between the standard diffraction pattern and the experimental diffraction pattern is characterized by the mean square error during the registration process; there are two registration algorithms, the six-parameter method and the four-parameter method, and the calibrated parameters are and in is the crystal orientation angle, (x * ,y * ,z * ) is the projection center of the diffraction pattern, h is related to the surface roughness of the object, and the objective function is minimized until convergence to obtain the corrected Euler angles and the surface roughness of the object;

[0074] (x * ,y * ,z * ) and h have a geometric relationship, which will be described in detail below:

[0075] The coordinates of the EBSD detector reference system are (x, y, z), and the coordinates of the sample reference system are (X, Y, Z). In the detector reference system, the coordinates of the projection center PC are (x * ,y * ,z * ); In the sample reference system, the coordinates of PC are (X * ,Y * ,Z * ); the conversion between (x,y,z) and (X,Y,Z) is completed using rigid body movement in three-dimensional space:

[0076] (X,Y,Z) T =Q β (x,y,z) T

[0077] Among them, Q β is the rotation matrix, β represents the tilt angle of the sample relative to the EBSD probe; Q β The specific expression is as follows:

[0078]

[0079] The fluctuation of the PC coordinates after registration is related to the surface roughness of the sample. When EBSD is collected by scanning electron beam, the surface flatness of the sample meets the preset standard under the preset ideal state, and the obtained pattern projection center coordinate value (X * ,Y * ,Z * ) is linearly and uniformly distributed; when the roughness of the actual sample surface varies, when the electron beam is at a point (X L ,Y L ,0) as the target, the electron beam is at (X * ,Y* ,Z * ) are trapped by the sample surface; (X * ,Y * ,Z * ) are obtained by linear transformation of (x * ,y * ,z * )

[0080] (X * ,Y * ,Z * ) T = Q β (x * ,y * ,z * ) T

[0081] H(X,Y) represents the roughness function of the sample, taking X and Y as parameters; the slope of the surface roughness of the sample is limited, within the distance of δY * , is constant, and is approximated as follows:

[0082]

[0083] wherein X L ,Y L are defined as follows: collect the projection centers of the experimental diffraction pattern scanned by the entire diffraction experiment, and perform uniform grid normalization processing on the projection centers according to the scanning geometry; uniform grid fitting refers to assuming that all projection centers form a grid network with uniform spacing on the sample surface, and linearly fitting the projection center coordinate values to minimize ∑(X * -X L ) 2 , ∑(Y * -Y L ) 2 , and ∑(Z * -Z L ) 2 ; let

[0084] Combining the crystal direction angle as a variable, the total number of parameters of the integrated registration method is reduced to four

[0085] The variables α, X L ,Y L ,Z L are obtained through preliminary registration by IDIC-EBSD, and the parameter list of the four-parameter method is Two variables are less than the IDIC-EBSD registration method with six parameters.

[0086] Preferably, the registration step is repeated: fixing the projection center of the linear fitting, recalculating the misorientation and the sample surface roughness as variables;

[0087] The experimental diffraction pattern comprises a Kikuchi map acquired by an electron backscatter diffraction (EBSD) scan, and the standard diffraction pattern comprises a Kikuchi standard diffraction pattern obtained according to a crystal structure simulation;

[0088] The registration step establishes a mathematical relationship between the parameters and the projection coordinates of the experimental diffraction pattern on the standard diffraction pattern, and uses an algorithm to minimize the objective function;

[0089] The objective function is optimized by using a forward accumulation Gauss-Newton algorithm to form a linear equation group, and to provide a change amount {delta P} of each iteration of the parameters:

[0090] [M]{delta P}={gamma}

[0091] The expression of the Hessian matrix [M] in each iteration is as follows: ij

[0092]

[0093] Wherein, the Jacobian matrix of each parameter with respect to the coordinate u on the equatorial plane by the spherical projection is:

[0094]

[0095] The expression of each element in {gamma} is as follows:

[0096]

[0097] {delta P} is the change amount of each parameter in each iteration process, and the calculation is ended when it is lower than a set value, otherwise the next iteration is performed:

[0098] {P (n)}={P (n-1)}+{delta P (n)}.

[0099] Compared with the prior art, the present application has the following beneficial effects:

[0100] 1. The present application provides a method for measuring the surface roughness of a sample by particle diffraction technology, which has high measurement accuracy, reaches micron level, and is a non-contact measurement, which has less influence on the sample surface;

[0101] 2. The data required by the method can be generally obtained when measuring the crystal orientation and stress state of the sample surface, and the surface roughness information is obtained without increasing additional workload; ​

[0102] 3. The spatial resolution is high, reaching 30-50nm, which is significantly better than roughness measurement based on optics. BRIEF DESCRIPTION OF DRAWINGS

[0103] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments thereof, when read in conjunction with the accompanying drawings:

[0104] Figure 1 Fig. 1 is a schematic diagram of the geometry of EBSD experiment and projection center coordinates (x * ,y * ,z * );

[0105] Figure 2 Fig. 2 is a schematic diagram of the relationship between sample roughness and pattern projection center coordinates;

[0106] Figure 3 Fig. 3 is a macrograph (right) and microscope observation (left) of a sample;

[0107] Figure 4 Fig. 4 is the projection center of each point obtained by the six-parameter integrated registration algorithm;

[0108] Figure 5 Fig. 5 is a point cloud diagram of the projection center of each point obtained by the six-parameter integrated registration algorithm;

[0109] Figure 6 Fig. 6 is the fluctuation of the projection center coordinates;

[0110] Figure 7 Fig. 7 is the measurement result of the surface fluctuation of a high platform. (Left) six-parameter method. (Right) four-parameter method;

[0111] Figure 8 Fig. 8 is the measurement result of the surface fluctuation of a low platform by the four-parameter method;

[0112] Figure 9 Fig. 9 is a scanning electron microscope observation diagram of a rough surface of a silicon wafer prepared by indentation (left);

[0113] Figure 10 Fig. 10 is the surface roughness of a silicon wafer measured by a confocal optical microscope (left) and a scanning electron microscope EBSD (right), with the unit of microns. DETAILED DESCRIPTION

[0114] The present application will be described in detail below with specific embodiments. The following examples will help those skilled in the art to further understand the present application, but do not limit the present application in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present application. These all belong to the protection scope of the present application.

[0115] Embodiment 1:

[0116] The present application provides a method, system and medium for accurately measuring the surface roughness of an object. Surface roughness has a wide range of effects, and is closely related to the fitting properties, wear resistance, fatigue strength, contact stiffness, vibration and noise of mechanical parts, and has an important influence on the service life, aesthetics and reliability of mechanical products. In addition, the roughness of a scientific experiment sample will also affect the measurement results, for example, inaccurate roughness data will cause errors in plane stress.

[0117] According to the method for accurately measuring the surface roughness of an object provided by the present application, as shown in Figures 1-10 , comprising:

[0118] By using experimental equipment such as an electron microscope, the sample surface is scanned with a particle beam, a series of diffraction patterns are collected, and then the standard diffraction patterns obtained by calculation simulation are matched, so as to obtain the crystal direction angle and the projection center coordinate value corresponding to each experimental diffraction pattern. The projection center coordinate value corresponding to each diffraction pattern can reveal the fluctuation information of the sample surface.

[0119] Pattern acquisition step: the experimental diffraction pattern of the crystal sample obtained by particle diffraction, and the simulated standard diffraction pattern calculated according to the type of crystal;

[0120] Matching step: matching the standard diffraction pattern with the experimental diffraction pattern, and using mean square error to represent the difference between the standard diffraction pattern and the experimental diffraction pattern during the matching process. The matching algorithm is divided into two kinds, six-parameter method and four-parameter method, and the calibrated parameters are and Among them is the crystal direction angle, (x * ,y * ,z * ) is the projection center of the diffraction pattern, h is related to the surface roughness of the object, and the objective function is minimized until convergence, to obtain the corrected Euler angle and the surface roughness of the object.

[0121] (x * ,y * ,z * ) and h have a simple geometric relationship, which will be described in detail below:

[0122] Figure 1 The geometric projection of EBSD and the reference system used are shown in the figure. The coordinates of the EBSD detector reference system are (x, y, z), and the coordinates of the sample reference system are (X, Y, Z). In the detector reference system, the coordinates of the projection center (PC) are (x * ,y * ,z *); In the sample reference system, the coordinates of PC are (X * ,Y * ,Z * The conversion between (x,y,z) and (X,Y,Z) can be completed by moving the rigid body in three-dimensional space:

[0123] (X,Y,Z) T =Q β (x,y,z) T

[0124] where Q β is the rotation matrix, and β represents the tilt angle of the sample relative to the EBSD probe. When the EBSD probe is placed vertically, β and Figure 2 The sample inclination angle α is the same as in the experiment, but the EBSD probe is usually tilted within 10° during the experiment. β The specific expression is as follows:

[0125]

[0126] like Figure 2 As shown in Figure 2, the fluctuation of the PC coordinates after registration is related to the surface roughness of the sample. When EBSD is collected by scanning electron beam, the sample surface is ideally flat, and the coordinate value of the center of the pattern projection (X * ,Y * ,Z * ) is linearly and uniformly distributed. When the actual sample surface has roughness changes, when the electron beam is at point (X L ,Y L ,0) as the target, the electron beam is at (X * ,Y * ,Z * ) is intercepted by the sample surface. * ,Y * ,Z * ) can be obtained by * ,y * ,z * ) and perform linear transformation to obtain:

[0127] (X * ,Y * ,Z * ) T =Q β (x * ,y * ,z * ) T

[0128] H(X,Y) represents the roughness function of the sample, with X and Y as parameters. Assume that the slope of the surface roughness of the sample is finite, that is, In the case of δY * The distance can be approximated as a constant:

[0129]

[0130] Where X L ,Y L are defined as follows: Collect all the projection centers of the experimental diffraction pattern scanned in the whole diffraction experiment, and normalize the projection centers according to the scanning geometry. The uniform grid fitting means that all the projection centers are assumed to form a grid network with uniform spacing on the sample surface, and the projection center coordinate values are fitted linearly to minimize ∑(X * -X L ) 2 ,∑(Y * -Y L ) 2 ,∑(Z * -Z L ) 2 . Where X L =dX+eY+f,Y L =gX+iY+j,Z L =kX+lY+m, and X and Y in the formula are the horizontal and vertical numbers of the diffraction pattern, and d to m are parameters that can be optimized by a suitable optimization algorithm.

[0131] For convenience, the present application introduces a h variable to represent the sample surface roughness, and let The projection center is expressed as a function of h:

[0132] Z * =Z L +δZ * =Z L +h

[0133] Y * =Y L +δY * =Y L +htanα

[0134] Where Y * ,Z * are the projection center coordinates in the sample coordinate system, δ represents the change of a physical quantity, and α is the inclination angle of the sample, which is usually 70° in an electron backscattering diffraction (EBSD) experiment.

[0135] X * is independent of h. By combining the crystal direction angle as a variable for re-registration, the total number of parameters of the integrated registration method is reduced to four, i.e.

[0136] In the above equation, all variables α, XL , Y L , Z L can be obtained by the preliminary registration of IDIC-EBSD, and the parameter a can also be obtained from the EBSD acquisition hardware. Therefore, the parameter list of the four-parameter method is The six-parameter IDIC-EBSD registration method is reduced to four parameters, which can significantly improve the measurement accuracy of the surface roughness.

[0137] The optimal way of measuring the surface roughness of the sample based on the particle diffraction correction provided by the present application is as follows:

[0138] 1. Collect the particle diffraction pictures obtained by scanning, and simulate the standard diffraction pattern according to the crystal structure and Bragg diffraction principle.

[0139] 2. Use the six-parameter integrated registration method to calculate the corresponding of each diffraction picture. * * * * * *

[0140] 3. Use the uniform grid assumption to linearly fit all the projection centers on the sample surface to form a grid network with uniform spacing, and linearly fit (X * * * ) to (X L L L ).

[0141] 4. Fix (X L L L ) and other experimental parameters such as a and β, and use the four-parameter integrated registration method to calculate the corresponding

[0142] After completing steps 1 and 2, the surface roughness information of the sample can be obtained. After further completing steps 3 and 4, the measurement accuracy can be improved by two to three times.

[0143] Preferably, the method for accurately measuring the surface roughness of an object provided by the present application further comprises:

[0144] Projection center normalization step: Collect the multiple projection centers of the experimental diffraction pattern scanned in the entire diffraction experiment, and uniformly fit the projection centers according to the geometric relationship. ​​​​​​​​​​​​

[0145] Preferably, further comprising:

[0146] Repeating the registration step: fixing the projection center from the linear fitting, and recalculating the registration with only the orientation angles and sample surface roughness as variables.

[0147] Preferably, the experimental diffraction pattern comprises a Kikuchi map acquired by an electron backscatter diffraction (EBSD) scan, and the standard diffraction pattern comprises a Kikuchi standard diffraction pattern obtained from a crystal structure simulation.

[0148] Preferably, the registration step establishes a mathematical relationship between the parameters and the projection coordinates of the experimental diffraction pattern on the standard diffraction pattern, so that various algorithms can be used to minimize the objective function, including the Gauss-Newton algorithm.

[0149] Preferably, in the registration step, the objective function Θ is

[0150]

[0151] wherein ROI is the region of interest, ω(x) is the weight of pixel x of the experimental diffraction pattern, g(x) is a two-dimensional projection picture of the standard diffraction pattern G(u), g(x) = G[u(x, P)], and f(x) is the experimental diffraction pattern acquired by the EBSD scan.

[0152] The partial derivative of the objective function with respect to each parameter is calculated as:

[0153]

[0154] wherein P is used to uniformly represent the parameters, and in the six-parameter case and in the four-parameter case The optimization principles and registration processes of the six-parameter method and the four-parameter method are the same. u is the coordinate on the equatorial plane after spherical projection, is the gradient of the standard diffraction pattern after spherical projection in the u space.

[0155] A forward additive Gauss-Newton algorithm can be used to optimize this objective function, to form a linear equation system, and to provide the change amount {δP} of each iteration of the parameters:

[0156] [M]{δP} = {γ}

[0157] The expression of the Hessian matrix [M] in the element Mij in the n-1th iteration is:

[0158]

[0159] wherein ψ is the Jacobian matrix of the coordinate u on the equatorial plane after spherical projection with respect to each parameter:

[0160]

[0161] The expression of each element in the second term {γ} is:

[0162]

[0163] {δP} is the change of each parameter in each iteration process, and the calculation ends when it is lower than a set value, otherwise the next iteration is performed:

[0164] {P (n)}={P (n-1)}+{δP (n)}。

[0165] The system for correcting the projection center and Euler angle of a particle diffraction image according to the present application comprises:

[0166] The pattern acquisition module acquires an experimental diffraction pattern of a crystal obtained by particle diffraction, and acquires a standard diffraction pattern corresponding to the crystal;

[0167] The registration module one (six-parameter method) registers the standard diffraction pattern and the experimental diffraction pattern, and in the registration process, a target function is used to represent the difference between the standard diffraction pattern and the experimental diffraction pattern, the coordinates of the projection center and the Euler angle are the parameters to be sought, the target function is minimized to converge, and the corrected projection center and Euler angle are obtained.

[0168] The normalization module performs normalization processing such as uniform grid fitting on the coordinates of the diffraction image projection center, so as to reduce the calculation error of the projection center, and in this process, the sample surface roughness can be obtained.

[0169] The registration module two (four-parameter method) establishes a geometric relationship between the sample roughness and the fluctuation of the diffraction image projection center, takes the Euler angle and the sample surface roughness as the four parameters to be sought, and registers the simulated standard diffraction pattern and the experimental diffraction pattern, so as to obtain surface roughness data with significantly improved precision.

[0170] The computer readable storage medium according to the present application stores a computer program, and the computer program is executed by a processor to implement the steps of measuring the sample surface roughness.

[0171] Table 1 relates to a parameter list

[0172]

[0173] Example 2:

[0174] Example 2 is a preferred example of Example 1, and is used to more specifically illustrate the present application.

[0175] Silicon wafer surface roughness measurement:

[0176] Several silicon wafer fragments were stacked and adhered together to make a sample containing surface undulation, as shown in Figure 3 This sample is large enough for a microscope and has a roughness difference of millimeter level. This sample can be used to verify the effect of the method of measuring roughness.

[0177] Figure 4 The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface.

[0178] Figure 5 The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface. * * * The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface.

[0179] Figure 6 The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface. * L * L * L * L * L * L The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface. Figure 2

[0180] Figure 7 The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface.

[0181] Figure 8 The six-parameter method shows the coordinates of the projection center of each pattern. The integrated registration algorithm successfully runs in the high and low areas of the sample, and the crystal orientation angle and the projection center coordinates are calibrated. However, there is a region in the middle of the high and low areas that cannot be successfully calculated, because in the case of a 70° sample tilt, this region is blocked by the high area and the electron beam cannot be scanned. This problem does not exist on a sample with a more gentle surface.

[0182] ​​​​​​​​​​​​​​Example 3:

[0183] Example 3 is a preferred example of Example 1 to illustrate the present application more specifically.

[0184] Silicon wafer surface roughness measurement:

[0185] The inventors made a tiny indentation on a silicon wafer using a Vickers hardness tester, but due to the brittleness of silicon, the surface of the silicon wafer near the indentation was damaged in a large area, forming a complex surface, as shown in FIG. 1. The sample surface is rough, and the inclination changes sharply, which can better characterize the roughness measurement accuracy and its limitations of the present application. Figure 9

[0186] Confocal optical microscope, scanning electron microscope EBSD technology of the present application are used to measure the surface roughness of the sample, and the results are shown in FIG. 2. It can be seen that the present application better measures the surface roughness of the lower half of the sample, reaching micron-level accuracy. The present application fails to successfully measure the roughness of the upper half of the sample, because the surface inclination of the upper half of the sample is negative, and the 70° inclination of the sample itself in the EBSD experiment makes it difficult for the electron beam to scan the sample surface, so the present application is suitable for measuring samples with a flat surface. Figure 10

[0187] Those skilled in the art know that in addition to implementing the system and each device, module and unit thereof provided by the present application in the form of pure computer readable program code, the same function can also be achieved by logically programming the method steps to make the system and each device, module and unit thereof provided by the present application in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers and embedded microcontrollers. Therefore, the system and each device, module and unit thereof provided by the present application can be considered as a hardware component, and the devices, modules and units included therein for achieving various functions can also be considered as structures within the hardware component; the devices, modules and units for achieving various functions can also be considered as both software modules for implementing methods and structures within hardware components.

[0188] The specific embodiments of the present application are described above. It should be understood that the present application is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essential content of the present application. The embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other without conflict.​​

Claims

1. A method of accurately measuring the roughness of a surface of an object, characterized by, Comprising: Step S1: scanning the sample surface by particle beam through experimental equipment, collecting experimental diffraction patterns; According to the crystal type, calculating the standard diffraction pattern simulation; Step S2: registering the experimental diffraction pattern with the standard diffraction pattern, obtaining the crystal direction angle and the projection center coordinate value corresponding to the experimental diffraction pattern, adopting the uniform grid assumption, linearly fitting all the projection centers to form a grid network with uniform spacing on the sample surface, using the four-parameter integrated registration method to calculate the sample surface relief information from each diffraction picture.

2. The method of accurately measuring surface roughness of an object according to claim 1, wherein, In the step S2: The obtained projection center coordinates are normalized, and the multiple projection centers of the experimental diffraction patterns scanned in the entire diffraction experiment are collected, the projection centers are uniformly fitted according to the geometric relationship of the scanning experiment, and the uniform grid assumption is that all the projection centers form a grid network with uniform spacing on the sample surface, which is linearly fitted: X L = dX + eY + f, Y L = gX + iY + j, Z L = kX + lY + m where X and Y are the transverse and longitudinal indices of the diffraction pattern, X L , Y L , Z L are the linearized projection center coordinate values, d, e, f, g, i, j, k, l, m are fitting parameters obtained using a fitting algorithm; Z * -Z L is the surface roughness of the sample at the (X, Y) position; On the basis of the normalization of the projection center coordinate values, the relationship between the sample roughness h and Y * -Y L and Z * -Z L is established according to the geometric relationships including the sample tilt angle, the detector tilt angle and the particle beam direction, and the six parameters of the sought crystal orientation angle and the coordinate values are reduced to four parameters of the crystal orientation angle and the roughness: Z * =Z L +δZ * =Z L +h Y * = Y L + δY * = Y L + h tan α where Y * , Z * are the coordinates of the projection center in the sample coordinate system, δ represents the change in the physical quantity, and α is the tilt angle of the sample relative to the incident electron beam.

3. The method for accurately measuring the surface roughness of an object according to claim 1, characterized in that: The experimental diffraction pattern is registered with the standard diffraction pattern, and the difference between the two is characterized by a mean square error objective function during the registration process, the crystal direction angle and the surface roughness of the object are taken as the parameters P to be optimized, and the objective function is minimized until convergence, so as to obtain the corrected parameters; In the registration step, the objective function Θ is In the formula, ROI is the pattern area to be registered, ω(x) is the weight of the pixel x of the diffraction pattern in the registration process, g(x) is the two-dimensional projection picture of the standard diffraction pattern G(u), g(x)=G[u(x, P)], and f(x) is the experimental diffraction pattern collected by the particle diffraction experiment; The partial derivatives of the objective function with respect to each parameter are calculated: where P collectively represents the four parameters, i.e. the crystal orientation angle and the object surface roughness, u is the coordinate of the standard diffraction pattern projected on the equatorial plane by a sphere, is the gradient of the standard diffraction pattern projected on the u space by a sphere; i is the serial number of the parameter; Fix the normalized projection center, and re-register the Euler angle and sample roughness as target parameters.

4. The method for accurately measuring the surface roughness of an object according to claim 3, characterized in that: The experimental diffraction pattern is aligned with a standard diffraction pattern, and the difference between the standard diffraction pattern and the experimental diffraction pattern is characterized by a mean square error during the alignment process; the alignment algorithm is divided into two kinds, a six-parameter method and a four-parameter method, and the calibrated parameters are and wherein is a crystal direction angle, (x * , y * , z * ) is a projection center of a diffraction pattern, h is related to the roughness of the object surface, and the objective function is minimized until convergence, so as to obtain the corrected Euler angle and the roughness of the object surface; (x * , y * , z * ) and h are in geometric relationship, which will be described in detail below: The coordinates of the EBSD detector as the reference system are marked as (x, y, z), and the coordinates of the sample as the reference system are marked as (X, Y, Z); in the detector reference system, the coordinates of the projection center PC are (x * , y * , z * ); in the sample reference system, the coordinates of PC are (X * , Y * , Z * ); the mutual conversion of (x, y, z) and (X, Y, Z) is completed by rigid body movement of three-dimensional space: (x, y, z) T = Q β (x, y, z) T where Q β is a rotation matrix, β represents the tilt angle of the sample relative to the EBSD probe; Q β The specific expression is as follows: The fluctuation of the registered PC coordinates is related to the surface roughness of the sample. When the EBSD acquisition is performed by scanning the electron beam, the sample surface flatness in the ideal state meets the preset standard, and the obtained pattern projection center coordinate values (X * , Y * , Z * ) are linearly and uniformly distributed; when the actual sample surface has roughness variation, when the electron beam is targeted at the point (X L , Y L , 0), the electron beam is intercepted by the sample surface at (X * , Y * , Z * ); (X * , Y * , Z * ) is obtained by linear conversion of (x * , y * , z * ): (X * , Y * , Z * ) T = Q β (x * , y * , z * ) T H(X, Y) represents a roughness function of the sample, with X and Y as parameters; the slope of the surface roughness of the sample is finite, within a distance of δY * is constant within a distance of δY, approximated as follows: wherein X L , Y L are defined as follows: collect a plurality of projection centers of the experimental diffraction pattern scanned throughout the diffraction experiment, and normalize the projection centers according to the scanning geometry in a uniform grid; uniform grid fitting means assuming that all the projection centers form a grid network with uniform spacing on the sample surface, fitting the projection center coordinate values linearly to minimize∑(X * -X L ) 2 ,∑(Y * -Y L ) 2 ,∑(Z * -Z L ) 2 ; let The total number of parameters of the integrated registration method is reduced to four by re-registering with the crystal orientation angle as a variable The variables a, X L , Y L , Z L The preliminary registration is obtained by IDIC-EBSD, where the parameter a is obtained from the EBSD acquisition hardware, and the parameter list of the four-parameter method is Two variables are less than the IDIC-EBSD registration method of six parameters.

5. The method for accurately measuring the surface roughness of an object according to claim 1, characterized in that: The registration step is repeated: fixing the projection center obtained by linear fitting, and re-registering and calculating the crystal direction angle and the sample surface roughness as variables; The experimental diffraction pattern includes a Kikuchi pattern collected by electron backscattered diffraction (EBSD) scanning, and the standard diffraction pattern includes a Kikuchi standard diffraction pattern simulated according to the crystal structure; The registration step establishes a mathematical relationship between the parameters and the projection coordinates of the experimental diffraction pattern on the standard diffraction pattern, and uses an algorithm to minimize the objective function; A forward accumulation Gauss-Newton algorithm is used to optimize the objective function, a linear equation set is established, and the change amount {δP} of each iteration of the parameters is provided: [M]{δP}={γ} The expression of the elements M of the matrix [M] at each iteration is: ij M = M + a * (b - M) Where ψ is the Jacobian matrix of the coordinates u projected on the equatorial plane with respect to each parameter: The expression of each element in {γ} is: {δP} is the change amount of each parameter in each iteration process, and the calculation is ended when it is less than a set value, otherwise the next iteration is performed: {P (n)}={P (n-1}+{δP (n)} 6. A system for accurately measuring the roughness of a surface of an object, the system comprising: The method for accurately measuring the surface roughness of an object according to any one of claims 1-5 is executed, comprising: The pattern acquisition module acquires an experimental diffraction pattern of a crystal obtained by particle diffraction and acquires a standard diffraction pattern corresponding to the crystal; The six-parameter registration module registers the standard diffraction pattern and the experimental diffraction pattern, and in the registration process, a target function is used to represent the difference between the standard diffraction pattern and the experimental diffraction pattern, the coordinates of the Euler angles and the projection center are taken as the parameters to be searched, and the target function is minimized until convergence to obtain the corrected projection center and Euler angles; The normalization module performs uniform grid fitting normalization processing on the coordinates of the diffraction image projection center to obtain the sample surface roughness; The four-parameter registration module establishes a geometric relationship between the sample roughness and the fluctuation of the diffraction image projection center, takes the Euler angles and the sample surface roughness as the four parameters to be searched, and registers the simulated standard diffraction pattern and the experimental diffraction pattern to obtain the surface roughness data with improved accuracy.

7. The system for accurately measuring the surface roughness of an object according to claim 6, wherein: The obtained projection center coordinates are normalized, a plurality of projection centers of the experimental diffraction patterns scanned in the entire diffraction experiment are collected, the projection centers are uniformly fitted according to the geometric relationship of the scanning experiment, it is assumed that all the projection centers form a grid network with uniform spacing on the sample surface, and linear fitting is performed. X L = dX + eY + f, Y L = gX + iY + j, Z L = kX + lY + m where X and Y are the transverse and longitudinal indices of the diffraction pattern, X L , Y L , Z L are the linearized projection center coordinate values, d, e, f, g, i, j, k, l, m are fitting parameters obtained using a fitting algorithm; Z * -Z L is the surface roughness of the sample at the (X, Y) position; On the basis of the normalization of the projection center coordinate values, the relationship between the sample roughness h and Y * -Y L and Z * -Z L is established according to the geometric relationship including the sample tilt angle, the detector tilt angle and the particle beam direction, and the six parameters of the sought crystal orientation angle and the coordinate values are reduced to four parameters of the crystal orientation angle and the roughness. Z * = Z L + δZ * = Z L + h Y * = Y L + δY * = Y L + h tan α where Y * , Z * are the coordinates of the projection center in the sample coordinate system, δ represents the change in the physical quantity, and α is the tilt angle of the sample relative to the incident electron beam.

8. The system for accurately measuring the surface roughness of an object according to claim 6, wherein: The experimental diffraction pattern and the standard diffraction pattern are registered, and in the registration process, a mean square deviation target function is used to represent the difference between the two, the crystal orientation angle and the object surface roughness are taken as the parameters P to be optimized, and the target function is minimized until convergence to obtain the corrected parameters; In the registration step, the target function Θ is In the formula, ROI is the pattern area to be registered, ω(x) is the weight of the pixel x of the diffraction pattern in the registration process, g(x) is the two-dimensional projection picture of the standard diffraction pattern G(u), g(x) = G[u(x, P)], and f(x) is the experimental diffraction pattern collected in the particle diffraction experiment; The partial derivatives of the target function with respect to the parameters are calculated: where P collectively represents the four parameters, i.e. the crystal orientation angle and the object surface roughness, u is the coordinate of the standard diffraction pattern projected on the equatorial plane by a sphere, is the gradient of the standard diffraction pattern projected on the u space by a sphere; i is the serial number of the parameter; The projection center after normalization is fixed, and the Euler angles and the sample roughness are taken as the target parameters to perform registration again.

9. The system for accurately measuring the surface roughness of an object according to claim 8, wherein: The experimental diffraction pattern is aligned with a standard diffraction pattern, and the difference between the standard diffraction pattern and the experimental diffraction pattern is characterized by a mean square error during the alignment process; the alignment algorithm is divided into two kinds, a six-parameter method and a four-parameter method, and the calibrated parameters are and wherein is a crystal direction angle, (x * , y * , z * ) is a projection center of a diffraction pattern, h is related to the roughness of the object surface, and the objective function is minimized until convergence, so as to obtain the corrected Euler angle and the roughness of the object surface; (x * , y * , z * ) and h are in geometric relationship, which will be described in detail below: The coordinates of the EBSD detector as the reference system are marked as (x, y, z), and the coordinates of the sample as the reference system are marked as (X, Y, Z); in the detector reference system, the coordinates of the projection center PC are (x * , y * , z * ); in the sample reference system, the coordinates of PC are (X * , Y * , Z * ); the mutual conversion of (x, y, z) and (X, Y, Z) is completed by rigid movement of a three-dimensional space: (x, y, z) T = Q β (x, y, z) T where Q β is a rotation matrix, β represents the tilt angle of the sample relative to the EBSD probe; Q β The specific expression is as follows: The fluctuation of the registered PC coordinates is related to the surface roughness of the sample. When the EBSD acquisition is performed by scanning the electron beam, the sample surface flatness in the ideal state meets the preset standard, and the obtained pattern projection center coordinate values (X * , Y * , Z * ) are linearly and uniformly distributed. When the actual sample surface has roughness variation, when the electron beam is targeted at the point (X L , Y L , 0), the electron beam is intercepted by the sample surface at (X * , Y * , Z * ); (X * , Y * , Z * ) is obtained by linear conversion of (x * , y * , z * ): (X * , Y * , Z * ) T = Q β (x * , y * , z * ) T H(X, Y) represents a roughness function of the sample, with X and Y as parameters; the slope of the surface roughness of the sample is finite, within δY * is constant within a distance, which is approximated as follows: wherein X L , Y L are defined as follows: collect a set of projection centers of the experimental diffraction pattern scanned throughout the diffraction experiment, and normalize the projection centers according to the scanning geometry in a uniform grid; uniform grid fitting means assuming that all the projection centers form a grid network with uniform spacing on the sample surface, and fitting the projection center coordinate values with a line to minimize ∑(X * -X L ) 2 , ∑(Y * -Y L ) 2 , ∑(Z * -Z L ) 2 ; let The total number of parameters of the integrated registration method is reduced to four by re-registering with the crystal orientation angle as a variable The variables a, X L , Y L , Z L The preliminary registration is obtained by IDIC-EBSD, where the parameter a is obtained from the EBSD acquisition hardware, and the parameter list of the four-parameter method is Two variables are less than the IDIC-EBSD registration method of six parameters.

10. The system for accurately measuring the surface roughness of an object according to claim 6, wherein: The registration step is repeated: the projection center obtained by linear fitting is fixed, and the crystal orientation angle and the sample surface roughness are taken as variables to perform registration calculation again; The experimental diffraction pattern includes a Kikuchi pattern collected by electron backscatter diffraction (EBSD) scanning, and the standard diffraction pattern includes a Kikuchi standard diffraction pattern obtained according to crystal structure simulation; The registration step establishes a mathematical relationship between the parameters and the projection coordinates of the experimental diffraction pattern on the standard diffraction pattern, and an algorithm is used to minimize the target function; A forward accumulation Gauss-Newton algorithm is used to optimize the target function, a linear equation set is established, and the change amount {δP} of each iteration of the parameters is provided: [M]{δP}={γ} The expression of the elements M of the matrix [M] at each iteration is: ii M = M + (M - M) Among them, ψ is the Jacobian matrix of the coordinate u projected on the equatorial plane to each parameter: The expressions of each element in {γ} are: {δP} is the change in each parameter during each iteration. When it is lower than the set value, the calculation ends, otherwise the next iteration is performed: {P (n) }={P (n-1) }+{δP (n) }。

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