Peak extraction method, thickness measurement method and equipment

Abstract

The present invention provides a peak extraction method, a thickness measurement method and an apparatus. They are applied to the field of high-precision measurement. The method comprises: acquiring a frame of spectral signals of a wafer; performing peak extraction on the spectral signals of the current frame according to a preset intensity threshold; when a peak is extracted, determining the peak value of the peak as the main peak peak value; obtaining a thickness guess value; using a thickness equation to reversely solve the thickness guess value and the main peak peak value to obtain the secondary peak peak value; using the main peak peak value and the secondary peak peak value as the initial guess values of a double-peak pseudo Voigt fitting equation, fitting the spectral signals of the current frame, and obtaining the main peak peak value and the secondary peak peak value of the spectral signals of the current frame. The present invention successfully solves the problem that the initial guess is missing and the secondary peak position is difficult to accurately identify due to the proximity of two peaks, and can accurately fit the main peak peak value and the secondary peak peak value of a frame of spectral signals.

Description

Technical Field

[0001] The present invention relates to the field of high-precision measurement, and in particular to a peak extraction method, a thickness measurement method and equipment. Background Art

[0002] In modern scientific research and industrial applications, spectral analysis technology, with its powerful capabilities, is widely used in areas such as material property analysis, chemical composition identification, and thickness measurement, including wafers. In this area, precise knowledge of the thickness of each wafer layer is crucial for controlling semiconductor device performance. Spectral analysis can achieve high-precision wafer thickness measurement by analyzing the reflection spectrum.

[0003] Spectral analysis technology, with its high precision and reliability, has become a key tool for accurate wafer thickness measurement. Traditional spectral analysis typically extracts the peaks of the wafer surface spectrum to obtain the required information. Spectral analysis can accurately separate and identify the peak information within the spectrum, thereby precisely determining the thickness of each wafer layer. This not only helps ensure wafer quality but also provides a strong basis for optimizing the manufacturing process, driving wafer manufacturing to a higher level.

[0004] However, existing peak extraction methods have significant drawbacks. When two peaks in a spectral signal are close together, these methods are susceptible to interference from adjacent peaks, making it difficult to accurately determine the position of the second peak (which is smaller than the first), leading to significant deviations in the analysis results. Summary of the Invention

[0005] In view of this, the present invention provides a peak extraction method, comprising:

[0006] Acquire a frame of spectrum signal from the wafer;

[0007] Perform peak extraction on the current frame spectral signal according to a preset intensity threshold;

[0008] When a peak is extracted, the peak value is determined to be the main peak peak;

[0009] Get the thickness guess;

[0010] The secondary peak value is obtained by reversely solving the thickness equation based on the thickness guess value and the primary peak value;

[0011] The main peak value and the secondary peak value are used as initial guess values of the bimodal pseudo Voigt fitting equation, and the current frame spectral signal is fitted to obtain the main peak value and the secondary peak value of the current frame spectral signal.

[0012] Optionally, when two peaks are extracted, the peak values of the two peaks are determined to be the main peak peak value and the secondary peak peak value, respectively;

[0013] The main peak value and the secondary peak value are used as initial guess values of the bimodal pseudo Voigt fitting equation, and the current frame spectral signal is fitted to obtain the main peak value and the secondary peak value of the current frame spectral signal.

[0014] Optionally, the thickness equation is:

[0015] ;

[0016] in, Indicates thickness, The main peak value, is the sub-peak-to-peak value, 、 、 、 、 、 、 、 These are the parameter results obtained by fitting the measurement data of the translation stage and spectrometer.

[0017] Optionally, using the main peak peak value and the secondary peak peak value as initial guess values of a bimodal pseudo Voigt fitting equation to fit the current frame spectral signal includes:

[0018] The main peak peak value, the secondary peak peak value and preset parameters are used as initial guess values of the bimodal pseudo Voigt fitting equation to fit the current frame spectral signal, wherein the preset parameters include the intensity maximum value of the spectral signal, the proportion of Gaussian signals in the spectral signal and the width of the peak in the spectral signal;

[0019] Wherein, the bimodal pseudo Voigt fitting equation is:

[0020] ;

[0021] in, Indicates the intensity of any wavelength in the current frame spectrum signal. and Indicates the maximum intensity of the spectral signal, and Indicates the proportion of Gaussian signals in the spectral signal, and represents the main peak and secondary peak in the spectral signal, and represents the width of the peak in the spectral signal, is the wavelength independent variable in the current frame spectrum signal.

[0022] Optionally, the secondary peak-to-peak value is obtained by reversely solving the thickness equation based on the thickness guess value and the primary peak value, including:

[0023] Get wavelength interval;

[0024] Calculate the secondary peak predicted peak value according to the wavelength interval and the main peak peak value;

[0025] The thickness is calculated based on the main peak peak value and the secondary peak predicted peak value using the thickness equation. The wavelength interval is continuously updated based on the difference between the thickness guess value and the thickness, and then the secondary peak predicted peak value is updated until the difference between the thickness guess value and the thickness is less than the preset convergence threshold, and the secondary peak peak value that meets the accuracy requirements is obtained.

[0026] Optionally, before performing peak extraction on the current frame spectral signal according to a preset intensity threshold, the method further includes:

[0027] Acquiring background spectral signals originating from measurement conditions;

[0028] Subtracting the background spectrum signal from the current frame spectrum signal of the wafer to obtain a true spectrum signal of the wafer in the current frame;

[0029] Performing main peak judgment on the real spectrum signal;

[0030] If there is a main peak, the real spectrum signal is smoothed according to a preset smoothing intensity;

[0031] If there is no main peak, the peak extraction of the current frame spectrum signal is stopped.

[0032] A second aspect of the present invention provides a thickness measurement method, comprising:

[0033] Obtain the main peak value and the secondary peak value using any of the methods described above;

[0034] The thickness of the wafer in the current frame is calculated according to the main peak-to-peak value and the secondary peak-to-peak value.

[0035] The third aspect of the present invention provides a peak extraction device, which includes: a processor and a memory connected to the processor; wherein the memory stores instructions that can be executed by the processor, and the instructions are executed by the processor to enable the processor to perform the peak extraction method as described in any one of the above items.

[0036] A fourth aspect of the present invention provides a thickness measuring device, comprising: a processor and a memory connected to the processor; wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor to enable the processor to perform the thickness measurement method as described above.

[0037] A fifth aspect of the present invention provides a thinning machine, characterized in that it is used to thin a wafer and perform any one of the above methods during the thinning process.

[0038] When only one frame of spectral signal is obtained, the present invention uses a preset intensity threshold to perform peak extraction. When only one peak is extracted, it indicates that the distance between the main and secondary peaks is small and the secondary peak is covered by the main peak. Therefore, it is necessary to find the position of the secondary peak. Specifically, the peak value of the peak can be set as the peak value of the main peak and a preset thickness guess value can be obtained. The secondary peak peak value is obtained by reversely solving the thickness equation, and this is used as an initial guess. The double-peak pseudo Voigt fitting equation is used to accurately fit the frame of spectral signal. This successfully solves the problem of missing initial guesses when there is only one frame of spectral signal and the problem that the secondary peak position is difficult to accurately identify due to the proximity of two peaks. The main peak peak value and the secondary peak peak value of a frame of spectral signal can be accurately fitted.

[0039] When two peaks are extracted from a frame of spectral signal of a wafer, the present invention can directly use the two peaks as the initial guess of the double-peak pseudo Voigt fitting equation to fit the frame of spectral signal, effectively solving the problem of missing initial guess when there is only one frame of spectral signal, and can more accurately fit the main peak peak value and secondary peak peak value in a frame of spectral signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 is a flow chart of a peak extraction method in an embodiment of the present invention;

[0042] Figure 2 is a flow chart of another peak extraction method in an embodiment of the present invention;

[0043] Figure 3 This is a spectrum signal diagram when a peak is extracted in an embodiment of the present invention;

[0044] Figure 4 This is a spectrum signal diagram when two peaks are extracted in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0047] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components; wireless connections or wired connections. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0048] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0049] like Figure 1 As shown, an embodiment of the present invention provides a peak extraction method, which is executed by an electronic device such as a computer or a server, and specifically includes:

[0050] S1, obtain a frame of spectrum signal from the wafer.

[0051] Use a spectrometer to collect the wafer's spectral signal in real time, or collect spectral signals over a period of time. Select a single frame of spectral signals. This embodiment only performs peak extraction when there is only one frame of spectral signals. The spectral signal is plotted on the horizontal axis as wavelength or pixel, and on the vertical axis as intensity.

[0052] S2, extracting the peak of the spectrum signal of the current frame according to a preset intensity threshold, and determining whether it is a peak; when a peak is extracted, executing step S3.

[0053] The preset intensity threshold is an empirical value. You can select the corresponding empirical value according to the experiment type. For example, if all experiments are spectral confocal, the same set of threshold empirical values can be used.

[0054] S3, determining the peak value of the peak as the main peak peak value.

[0055] The wavelength at the center of the peak is defined as the main peak peak value.

[0056] S4, obtaining a thickness guess value.

[0057] The thickness guess value can be obtained in many ways, such as: empirical values obtained from multiple measurements or experiments, approximate thickness parameters measured by other contact measurement methods, and an approximate initial thickness value added to the wafer in the initial frame.

[0058] S5, use the thickness equation to reversely solve the secondary peak value based on the thickness guess value and the main peak value.

[0059] If only one peak is extracted, it means that the distance between the primary and secondary peaks is small and the secondary peak is covered by the primary peak. A relatively accurate secondary peak value can be reversely solved by using the thickness guess value.

[0060] S6, using the main peak peak value and the secondary peak peak value as initial guess values of the bimodal pseudo Voigt fitting equation, fitting the current frame spectral signal, and obtaining the main peak peak value and the secondary peak peak value of the current frame spectral signal.

[0061] The bimodal pseudo-Voigt fitting equation can be used to simultaneously fit two peaks in a spectral signal. This method not only avoids interference from adjacent peaks but also properly fits regions where the spectral derivative is constantly less than 0. The introduction of the bimodal pseudo-Voigt fitting equation makes fitting results more accurate and stable. Furthermore, because the fitting probability of the bimodal pseudo-Voigt fitting equation depends on the signal's center of symmetry (peak), the peak positions of the primary and secondary peaks of the true spectral signal can be used to accurately fit the spectral signal for that frame. The resulting fitted equation then yields the true positions of the primary and secondary peaks of the current spectral frame.

[0062] In the spectral signal analysis of this embodiment, when there is only one frame of spectral signal, if it is directly processed, it may face the problem of no initial guess and difficulty in accurately identifying the secondary peak position when the two peaks are close. Specifically, by using a preset intensity threshold to extract the peak of the frame of spectral signal, when only one peak is extracted, it indicates that the distance between the main and secondary peaks is small and the secondary peak is covered by the main peak. Therefore, it is necessary to find the secondary peak position. Specifically, the peak value can be set as the main peak peak value and a pre-set thickness guess value can be obtained. The secondary peak peak value is obtained by reversely solving the thickness equation and using this as the initial guess. The double-peak pseudo Voigt fitting equation is used to accurately fit the frame of spectral signal, successfully solving the problem of missing initial guess when there is only one frame of spectral signal and difficulty in accurately identifying the secondary peak position due to the proximity of two peaks. The main peak peak value and the secondary peak peak value of a frame of spectral signal can be accurately fitted.

[0063] like Figure 2 As shown, when determining the number of peaks in step S2, if two peaks are extracted, step S7 is executed:

[0064] S7, determining the peak values of the two peaks as the main peak peak value and the secondary peak peak value, respectively.

[0065] When two peaks were extracted, the first peak was taken as the main peak and the second peak as the secondary peak.

[0066] S8, using the main peak peak value and the secondary peak peak value as initial guess values of the bimodal pseudo Voigt fitting equation, fitting the current frame spectral signal, and obtaining the main peak peak value and the secondary peak peak value of the current frame spectral signal.

[0067] This embodiment precisely determines the center positions of the primary and secondary peaks when two peaks are extracted from a single-frame spectral signal. These two peaks can be used directly as initial guesses for the bimodal pseudo-Voigt fitting equation to fit the spectral signal for that frame. This effectively solves the problem of missing initial guesses when only one frame is available, and allows for more accurate fitting of the primary and secondary peaks within a single frame.

[0068] The thickness equation in step S5 is:

[0069] ;

[0070] in, Indicates thickness, The main peak value, is the sub-peak value, 、 、 、 、 、 、 、 These are the parameter results obtained by fitting the measurement data of the translation stage and spectrometer.

[0071] Substitute the center position of the main peak into the peak value of the main peak in the formula , and the thickness of the thickness guessed value into the formula , you can reversely solve the sub-peak-peak value .

[0072] Furthermore, in step S6, the peak value of the main peak and the peak value of the secondary peak are used as initial guess values of the bimodal pseudo Voigt fitting equation to fit the spectrum signal of the current frame, including:

[0073] The peak value of the main peak, the peak value of the secondary peak, and preset parameters are used as the initial guess values of the bimodal pseudo Voigt fitting equation to fit the spectral signal of the current frame. The preset parameters include the maximum intensity of the spectral signal, the proportion of Gaussian signals in the spectral signal, and the width of the peak in the spectral signal;

[0074] Wherein, the bimodal pseudo Voigt fitting equation is:

[0075] ;

[0076] in, Indicates the intensity of any wavelength in the current frame spectrum signal. and Indicates the maximum intensity of the spectral signal, and Indicates the proportion of Gaussian signals in the spectral signal, and represents the main peak and secondary peak in the spectral signal, and represents the width of the peak in the spectral signal, is the wavelength independent variable in the current frame spectrum signal.

[0077] When fitting the spectral signal of this frame, it is necessary to continuously fit the double-peak pseudo Voigt fitting equation according to the wavelength in the frame signal as the independent variable and the corresponding intensity until the spectral signal is successfully fitted. The fitting equation contains eight parameters, among which, and The accuracy of the spectral equation determines the probability of fitting the bimodal pseudo-Voigt fitting equation. By extracting the primary and secondary peak values of a spectral frame, the spectral signal of the first frame can be accurately and successfully fitted. The initial guesses for the remaining parameters can be fitted successfully with a high probability even if they deviate significantly from the actual values. Empirical values can be used directly, eliminating the need for specialized data analysis to estimate them.

[0078] The bimodal pseudo Voigt fitting equation in this embodiment includes the maximum value of the spectral signal intensity, the proportion of Gaussian signals, the peak value and the peak width, and continuously fits the wavelength in a frame of signal as the independent variable and its corresponding intensity. Since the accuracy of the two peak values plays a decisive role in the fitting probability among the eight parameters in the fitting equation, the frame of spectral signal can be accurately and successfully fitted by accurately extracting the center positions of the primary and secondary peaks of a frame of spectral signal. Moreover, even if the initial guess of the remaining parameters deviates greatly from the actual ones, there is a high probability of successful fitting, and the empirical values can be directly used without the need for special analysis and estimation of the data, thereby improving the efficiency and accuracy of fitting a frame of spectral signal.

[0079] In one embodiment, before step S2 extracts the peak of the current frame spectral signal according to the preset intensity threshold, the step further includes:

[0080] Acquires background spectral signals originating from the measurement conditions.

[0081] Specifically, the spectrometer can be used to collect signals from a thinning machine without a wafer placed thereon; or multiple groups of spectral signals from multiple samples under test can be collected, with each group of spectral signals being collected based on the same measurement conditions.

[0082] The sample being measured can be any substance. A spectrometer collects signals from the sample placed on the measuring table. Different samples are placed under the same measurement conditions to collect multiple sets of spectral signals. The background spectral signal is then extracted from these multiple sets of spectral signals, which includes an error that occurs in each set and is independent of the measurement conditions and sample. The measurement conditions encompass customizable input parameters such as specific light source intensity, wavelength range, measurement angle, ambient temperature and humidity, and resolution, ensuring diverse and representative data.

[0083] The background spectrum signal is subtracted from the current frame spectrum signal of the wafer to obtain the real spectrum signal of the wafer in the current frame.

[0084] Subtract the background noise signal from the current frame spectrum signal to reduce the interference of background error on the data and improve the accuracy of the signal.

[0085] Determine the main peak of the real spectrum signal;

[0086] If there is a main peak, the real spectrum signal is smoothed according to the preset smoothing intensity.

[0087] If there is no main peak, the peak extraction of the current frame spectrum signal is stopped.

[0088] Among them, the smoothing method can adopt low-pass filtering, wavelet transform, moving average, Savitzky-Golay filtering and other methods. The corresponding preset smoothing intensity is an empirical value. Different experimental types have a set of corresponding intensity empirical values. The specific empirical value can be selected according to the actual situation.

[0089] This embodiment effectively reduces the interference of background errors on the data by acquiring and subtracting the background spectral signal from the frame spectral signal, thereby improving the reliability and credibility of the entire spectral analysis results. Then, by determining the main peak, the spectral signal can be processed in a targeted manner, improving analysis efficiency and accuracy. When a main peak is present, smoothing is performed according to a preset smoothing intensity, which reduces noise interference, highlights the peak characteristics, and makes the spectral signal more accurate, providing reliable data for accurately extracting the peak center position. If a main peak is not present, the extraction is stopped, avoiding wasting computing resources and time.

[0090] The above embodiment determines the initial guess of the bimodal pseudo-Voigt fitting equation based on two situations, solving the problem of no accurate initial guess when only one frame of spectral signal is fitted. Moreover, the initial guess obtained in the above steps is highly accurate, thereby improving the accuracy of the bimodal pseudo-Voigt fitting equation in fitting the spectral signal, and thus obtaining the accurate positions of the two peak center values.

[0091] In addition, in step S5, the thickness equation is used to reversely solve the secondary peak value based on the thickness guess value and the primary peak value, which can also be:

[0092] Get the wavelength interval.

[0093] The secondary peak predicted peak value is calculated based on the wavelength interval and the main peak peak value.

[0094] The thickness equation is used to calculate the thickness based on the main peak peak value and the secondary peak predicted peak value. The wavelength interval is continuously updated according to the difference between the thickness guess value and the thickness, and then the secondary peak predicted peak value is updated until the difference between the thickness guess value and the thickness is less than the preset convergence threshold, and the secondary peak peak value that meets the accuracy requirements is obtained.

[0095] Specifically, assuming a small wavelength interval deltaw, the predicted secondary peak value w2' = w1 + deltaw, where w1 is the primary peak value. Substituting w1 and w2' into the thickness equation yields an inaccurate thickness calculation t1'. The value of w2' is continuously updated based on the difference between the thickness estimates t1 and t1', continuously searching and adjusting within the solution space. Each update results in a more accurate approximation of the secondary peak position, gradually narrowing the gap with the true secondary peak position. This process continues until the deviation between t1 and t1' falls below a preset convergence threshold (e.g., 1e-4). At this point, the value w2' can be considered a relatively accurate secondary peak location. w1 and w2' are the peak parameters of the bimodal pseudo-Voigt fitting equation. The specific wavelength interval update method can be applied to general optimization methods for arbitrary burst functions. This iterative update method, which seeks the data closest to the true secondary peak, significantly improves the accuracy of secondary peak peak determination.

[0096] The following are examples of the above embodiments:

[0097] The first frame of the wafer's spectral signal s1 and the background spectral signal s0 are acquired; the background spectral signal s0 is subtracted to obtain the background-removed true spectral signal s2; the true spectral signal s2 is then subjected to a main peak determination. If a main peak exists, the true spectral signal s2 is again subjected to a Savitzky-Golay filter to smooth it, obtaining a smoothed spectral signal s3; and the smoothed spectral signal s3 is then subjected to peak extraction.

[0098] like Figure 3 As shown, the horizontal axis represents wavelength and the vertical axis represents intensity. If the second peak is not identified, only one peak is extracted, and the wavelength of the main peak is 550.0nm. The blue curve in the figure is the true spectral signal s2, the red curve is the smoothed spectral signal s3, and the black dotted line position is the center position of the peak. Then set a thickness guess value of 100 microns, and substitute the wavelength 550.0 nanometers and the thickness guess value 100 microns into the thickness equation for reverse solution to obtain the guessed wavelength of the secondary peak of 552.8nm, which is the gray dotted line position in the figure; finally, substitute the wavelengths 550.0 and 552.8 into the double-peak pseudo Voigt fitting equation to fit the first frame of the spectral signal. After successful fitting, the main peak and secondary peak parameters obtained are the actual center positions of the main and secondary peaks, which are 549.9nm and 552.7nm respectively.

[0099] like Figure 4As shown, the abscissa represents wavelength, and the ordinate represents intensity. If two peaks are extracted, the wavelength of the primary peak is 550.0 nm, and the wavelength of the secondary peak is 554.7 nm. The blue curve in the figure represents the true spectral signal s2, the red curve represents the smoothed spectral signal s3, and the black dashed line represents the peak center. The wavelengths 550.0 and 554.7 are then substituted into the bimodal pseudo Voigt fitting equation to fit the first frame of the spectral signal. After a successful fit, the peak values of the primary and secondary peaks obtained are the actual center positions of the primary and secondary peaks, 549.9 nm and 554.9 nm, respectively.

[0100] Furthermore, in step S6, the peak value of the main peak and the peak value of the secondary peak are used as initial guess values of the bimodal pseudo Voigt fitting equation, and after fitting the spectrum signal of the current frame, the following steps are further included:

[0101] Obtain the fitting result of the bimodal pseudo Voigt fitting equation for the current frame spectral signal, and calculate the root mean square error between the fitting result and the current frame spectral signal;

[0102] Determine whether the root mean square error is less than a preset root mean square error;

[0103] If the root mean square error is less than the preset root mean square error, the two peaks in the fitting result are selected as the main peak-peak value and the secondary peak-peak value of the spectral signal of the current frame.

[0104] If the root mean square error is greater than the preset root mean square error, the initial guess is updated until the mean square error between the fitting result of the bimodal pseudoVoigt fitting equation for the current frame spectral signal and the current frame spectral signal is less than the preset mean square error, and the two peaks in the fitting result are selected as the main peak peak value and the secondary peak peak value of the current frame spectral signal;

[0105] The update times of the initial guess are recorded. When the update times exceed the preset update times and still fail to meet the root mean square error requirement, the current frame spectral signal is skipped and the next frame spectral signal is processed.

[0106] This embodiment re-evaluates the degree of difference between the fitting result and the original spectral signal by calculating the root mean square error between the fitting result and a frame of spectral signal. When the root mean square error is less than the preset value, it means that the difference between the fitting result and the original spectral signal is within an acceptable range, and the determined peak value can be guaranteed to have a high accuracy. When the root mean square error is greater than the preset value, it indicates that the current fitting effect is not good, and the initial guess needs to be updated to optimize the fit until the root mean square error meets the requirement, so as to obtain an actual peak value that is closer to the actual situation. At the same time, the number of updates of the initial guess is recorded. When the number of updates exceeds the preset number and the root mean square error requirement is still not met, the current frame spectral signal is skipped to process the next frame spectral signal, thereby avoiding excessive consumption of computing resources on spectral signals that are difficult to fit and improving the efficiency of the overall spectral signal processing.

[0107] An embodiment of the present invention further provides a thickness measurement method, which is executed by an electronic device such as a computer or a server, and specifically includes:

[0108] The peak value of the main peak and the secondary peak are obtained by using the peak extraction method described above;

[0109] Calculate the thickness of the wafer in the current frame based on the main peak peak value and the secondary peak peak value.

[0110] Specifically, the thickness of the wafer in the current frame can be calculated using the thickness equation.

[0111] This embodiment accurately obtains the main peak peak value and the secondary peak peak value through the above-mentioned peak extraction method, and then calculates the thickness of the wafer in the current frame through the thickness equation based on the obtained main peak peak value and the secondary peak peak value, thereby ensuring the accuracy of the wafer thickness calculation.

[0112] An embodiment of the present invention further provides a thinning machine for performing a thinning process on a wafer and executing any one of the peak extraction methods and thickness measurement methods described above during the thinning process.

[0113] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0114] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0117] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A peak extraction method, characterized in that: include: Acquire a frame of spectrum signal from the wafer; Perform peak extraction on the current frame spectral signal according to a preset intensity threshold; When a peak is extracted, the peak value is determined to be the main peak peak; Get the thickness guess; The secondary peak value is obtained by reversely solving the thickness equation based on the thickness guess value and the primary peak value; The main peak value and the secondary peak value are used as initial guess values of the bimodal pseudo Voigt fitting equation, and the current frame spectral signal is fitted to obtain the main peak value and the secondary peak value of the current frame spectral signal.

2. The method according to claim 1, characterized in that When two peaks are extracted, the peak values of the two peaks are determined to be the main peak peak and the secondary peak peak respectively; The main peak value and the secondary peak value are used as initial guess values of the bimodal pseudo Voigt fitting equation, and the current frame spectral signal is fitted to obtain the main peak value and the secondary peak value of the current frame spectral signal.

3. The method according to claim 1, characterized in that The thickness equation is: ; in, Indicates thickness, The main peak value, is the sub-peak value, 、 、 、 、 、 、 、 These are the parameter results obtained by fitting the measurement data of the translation stage and spectrometer.

4. The method according to claim 1, wherein The peak value of the main peak and the peak value of the secondary peak are used as initial guess values of a bimodal pseudo Voigt fitting equation to fit the spectrum signal of the current frame, including: The main peak peak value, the secondary peak peak value and preset parameters are used as initial guess values of the bimodal pseudo Voigt fitting equation to fit the current frame spectral signal, wherein the preset parameters include the intensity maximum value of the spectral signal, the proportion of Gaussian signals in the spectral signal and the width of the peak in the spectral signal; Wherein, the bimodal pseudo Voigt fitting equation is: ; in, Indicates the intensity of any wavelength in the current frame spectrum signal. and Indicates the maximum intensity of the spectral signal, and Indicates the proportion of Gaussian signals in the spectral signal, and represents the main peak and secondary peak in the spectral signal, and represents the width of the peak in the spectral signal, is the wavelength independent variable in the current frame spectrum signal.

5. The method according to claim 1, wherein The secondary peak value is obtained by reversely solving the thickness guess value and the primary peak value using the thickness equation, including: Get wavelength interval; Calculate the secondary peak predicted peak value according to the wavelength interval and the main peak peak value; The thickness is calculated based on the main peak peak value and the secondary peak predicted peak value using the thickness equation. The wavelength interval is continuously updated based on the difference between the thickness guess value and the thickness, and then the secondary peak predicted peak value is updated until the difference between the thickness guess value and the thickness is less than the preset convergence threshold, and the secondary peak peak value that meets the accuracy requirements is obtained.

6. The method according to claim 1, characterized in that Before extracting the peak of the current frame spectrum signal according to the preset intensity threshold, the following steps are also included: Acquiring background spectral signals originating from measurement conditions; Subtracting the background spectrum signal from the current frame spectrum signal of the wafer to obtain a true spectrum signal of the wafer in the current frame; Performing main peak judgment on the real spectrum signal; If there is a main peak, the real spectrum signal is smoothed according to a preset smoothing intensity; If there is no main peak, the peak extraction of the current frame spectrum signal is stopped.

7. A thickness measurement method, characterized in that: include: Obtaining the main peak value and the secondary peak value using the method according to any one of claims 1 to 6; The thickness of the wafer in the current frame is calculated according to the main peak-to-peak value and the secondary peak-to-peak value.

8. A peak extraction device, characterized in that: include: A processor and a memory connected to the processor; wherein the memory stores instructions that can be executed by the processor, and the instructions are executed by the processor to enable the processor to perform the peak extraction method according to any one of claims 1 to 6.

9. A thickness measuring device, characterized in that: include: A processor and a memory connected to the processor; wherein the memory stores instructions that can be executed by the processor, and the instructions are executed by the processor to enable the processor to perform the thickness measurement method according to claim 7.

10. A thinning machine, characterized in that, Used to thin a wafer and perform the method according to any one of claims 1 to 7 during the thinning process.

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