Film thickness real-time measurement method, device, equipment and storage medium

Abstract

This application discloses a method, apparatus, device, and storage medium for real-time measurement of thin film thickness, relating to the field of thin film thickness measurement technology. The method includes: acquiring a two-dimensional interferometric image of the thin film under test at the current scanning position in real time; determining the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image; determining the power peak value of the interference spectral signals of each row of the two-dimensional interferometric image based on the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image; determining the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interferometric image based on the power peak value of the interference spectral signals of each row of the two-dimensional interferometric image; and determining the thickness distribution of the thin film under test at the current scanning position based on the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interferometric image. Through the above method, the real-time resolution throughput of thin film thickness during line scan measurement is significantly improved, and invalid measurement signals are effectively distinguished, thereby improving the robustness of the measurement system and the reliability of the resolution results.

Description

Technical Field

[0001] This application relates to the field of thin film thickness measurement technology, and in particular to methods, apparatus, equipment and storage media for real-time measurement of thin film thickness. Background Technology

[0002] Currently, in the OLED (Organic Light-Emitting Diode) encapsulation film deposition process, real-time online measurement of the encapsulation film thickness is required. In particular, when detecting the edge morphology of the encapsulation film, the inherent width of the edge morphology presents challenges due to the demands for a wide measurement range, large sample size, and high real-time performance. Traditional analytical methods utilize FFT (Fast Fourier Transform) executed on a CPU (Central Processing Unit), but the processing speed is insufficient to meet the high-speed, real-time feedback requirements of thin-film production lines. Furthermore, FFT calculations struggle to handle non-uniform sampled signals, requiring interpolation, and are prone to misjudgment of interference signals from invalid areas such as exposed substrates, stains, and scratches.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, device, and storage medium for real-time measurement of thin film thickness, aiming to solve the technical problem in the prior art that it is difficult to quickly and accurately analyze the large amount of data collected when measuring thin film thickness by line scanning.

[0005] To achieve the above objectives, this application provides a method for real-time measurement of thin film thickness, the method comprising: The two-dimensional interference image of the thin film under test at the current scanning position is acquired in real time, and the key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency are calculated in parallel. Based on the key statistical indices of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency, the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image is determined. Based on the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image, the power peak value of each row of the interference spectral signal of the two-dimensional interference image is determined; Based on the power peak value of each row of the interference spectral signal of the two-dimensional interference image, the effective thickness corresponding to each row of the interference spectral signal of the two-dimensional interference image is determined; Based on the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image, the thickness distribution of the thin film under test at the current scanning position is determined.

[0006] In one embodiment, the key statistical indicators include signal projection and correction statistics. The step of acquiring the two-dimensional interferometric image of the thin film under test at the current scanning position in real time and calculating the key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image in the relative wavenumber domain frequency includes: The two-dimensional interference image of the thin film under test at the current scanning position is acquired in real time, and the trigonometric function values ​​of each row of the interference spectrum signal of the two-dimensional interference image at the relative wavenumber domain frequency are calculated in parallel. Based on the trigonometric function values ​​of each row of the interference spectral signal of the two-dimensional interferometric image at the relative wavenumber domain frequency and the weights corresponding to the trigonometric function values, the weighted trigonometric statistics of each row of the interference spectral signal of the two-dimensional interferometric image are calculated in parallel. Based on the weighted triangular statistics of the interference spectral signals of each row of the two-dimensional interference image, the signal projection of the interference spectral signals of each row of the two-dimensional interference image is calculated in parallel. The mean influence error in the weighted triangular statistics of each row of interference spectral signals in the two-dimensional interference image is corrected to obtain the corrected statistics.

[0007] In one embodiment, the step of determining the normalized power spectrum of each row of the two-dimensional interferometric image based on key statistical indices of the interferometric spectral signals in the relative wavenumber domain includes: Based on the interference spectral signals of each row of the two-dimensional interference image and the weights corresponding to the interference spectral signals, the weighted variance of the interference spectral signals of each row of the two-dimensional interference image is calculated in parallel. Obtain the correspondence between key statistical indicators, weighted variance, and normalized power spectrum; Based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency, the weighted variance of the interference spectral signals of each row of the two-dimensional interferometric image, and the corresponding relationship, the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image is determined.

[0008] In one embodiment, the step of determining the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image based on the power peak value of each row of interference spectral signals includes: The relative wavenumber frequency corresponding to the power peak of each row of the interference spectral signal of the two-dimensional interference image is taken as the measured thickness corresponding to each row of the interference spectral signal of the two-dimensional interference image; When the power peak value of the interference spectrum signal corresponding to the measured thickness is greater than or equal to the reliability threshold, the measured thickness is taken as the effective thickness.

[0009] In one embodiment, the method further includes: The number of samples is determined based on the number of pixels in the horizontal direction of the two-dimensional interference image; Based on the number of samples, a reliability threshold is determined.

[0010] In one embodiment, the method further includes: The power peaks of the interference spectral signals in each row of the two-dimensional interference image and the power values ​​within a preset range of the power peaks are removed to obtain the normalized power spectrum evaluation power value of the interference spectral signals in each row of the two-dimensional interference image. The median power is determined from the evaluation frequency values ​​of the normalized power spectrum of each row of the interference spectral signal in the two-dimensional interference image; Based on the median power of the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image and a preset relative significance threshold, the reliability threshold of each row of the interference spectral signal of the two-dimensional interference image is determined.

[0011] In one embodiment, the step of acquiring a two-dimensional interference image of the thin film under test at the current scanning position in real time and calculating the key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency in parallel further includes: Based on the material refractive index and process thickness range of the thin film under test, the relative wavenumber domain frequency search range is calculated. The relative wavenumber domain frequency search range is discretized to obtain the relative wavenumber domain frequency.

[0012] Furthermore, to achieve the above objectives, this application also proposes a real-time film thickness measurement device, which includes: The power spectrum calculation module is used to acquire the two-dimensional interference image of the thin film under test at the current scanning position in real time, and to calculate the key statistical indicators of the interference spectrum signal of each row of the two-dimensional interference image in the relative wavenumber domain frequency in parallel. The power spectrum calculation module is also used to determine the normalized power spectrum of each row of the two-dimensional interferometric image based on the key statistical indicators of the interferometric spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency. The reliability assessment module is used to determine the power peak value of each row of the interference spectral signal of the two-dimensional interference image based on the normalized power spectrum of each row of the interference spectral signal. The reliability assessment module is also used to determine the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image based on the power peak value of each row of interference spectral signals in the two-dimensional interference image; The film thickness output module is used to determine the thickness distribution of the film under test at the current scanning position based on the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interference image.

[0013] In addition, to achieve the above objectives, this application also proposes a real-time film thickness measurement device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the real-time film thickness measurement method described above.

[0014] In addition, to achieve the above objectives, the present invention also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the real-time film thickness measurement method described above.

[0015] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the real-time film thickness measurement method described above.

[0016] This application provides a real-time method for measuring thin film thickness. It acquires a two-dimensional interferometric image of the thin film under test at the current scanning position in real time, and calculates key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency in parallel. Based on these key statistical indicators, the normalized power spectrum of each row of the interference spectral signals is determined. Based on the normalized power spectrum, the peak power of each row of the interference spectral signals is determined. Based on the peak power, the effective thickness corresponding to each row of the interference spectral signals is determined. Based on the effective thickness, the thickness distribution of the thin film under test at the current scanning position is determined. This application acquires measurement signals in real time and processes them in parallel, significantly improving the real-time throughput of thin film thickness analysis during line scan measurement. It ensures the real-time performance of the measurement, effectively distinguishes invalid measurement signals, improves the robustness of the measurement, and enhances the reliability of the analysis results. This solves the technical problem of difficulty in quickly and accurately analyzing large amounts of acquired data when measuring thin film thickness via line scan. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating Embodiment 1 of the real-time film thickness measurement method of this application; Figure 2 This is a schematic diagram of the overall architecture of the real-time film thickness measurement method provided in Embodiment 1 of this application; Figure 3 A schematic diagram of a line scanning measurement device for a real-time film thickness measurement method provided in Embodiment 1 of this application; Figure 4 This is a schematic diagram of the multi-threaded asynchronous processing architecture of the real-time film thickness measurement method provided in Embodiment 1 of this application; Figure 5 A schematic diagram of the GPU processing flow of the real-time thin film thickness measurement method provided in Embodiment 1 of this application; Figure 6 This is a flowchart illustrating Embodiment 2 of the real-time film thickness measurement method of this application; Figure 7 This is a schematic diagram of a two-dimensional interferometric image of the real-time film thickness measurement method provided in Embodiment 2 of this application; Figure 8 This is a schematic diagram of the interference spectrum signal of the real-time film thickness measurement method provided in Embodiment 2 of this application; Figure 9 A normalized power spectrum diagram of the real-time film thickness measurement method provided in Embodiment 2 of this application; Figure 10 This is a schematic diagram of the module structure of the real-time film thickness measurement device according to an embodiment of this application; Figure 11 This is a schematic diagram of the device structure of the hardware operating environment involved in the real-time film thickness measurement method in the embodiments of this application.

[0020] Explanation of icon numbers: 100. Imaging module; 200. Imaging spectrometer; 300. Thin film under test; 101. Illumination module; 102. Imaging lens; 201. Entrance slit; 202. Collimating lens; 203. Grating; 204. Focusing lens; 205. Detector.

[0021] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0024] The main solution of this application embodiment is as follows: Real-time acquisition of a two-dimensional interferometric image of the thin film under test at the current scanning position; parallel calculation of key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency; determination of the normalized power spectrum of each row of the interference spectral signals of the two-dimensional interferometric image based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency; determination of the peak power of each row of the interference spectral signals of the two-dimensional interferometric image based on the normalized power spectrum of each row of the interference spectral signals of the two-dimensional interferometric image; determination of the effective thickness corresponding to each row of the interference spectral signals of the two-dimensional interferometric image based on the peak power of each row of the interference spectral signals of the two-dimensional interferometric image; and determination of the thickness distribution of the thin film under test at the current scanning position based on the effective thickness corresponding to each row of the interference spectral signals of the two-dimensional interferometric image.

[0025] Currently, traditional analytical methods utilize FFT to execute on the CPU, but the processing speed is insufficient to meet the high-speed real-time feedback requirements of thin film production lines. Furthermore, FFT calculations struggle to handle non-uniform sampling signals, requiring interpolation processing. Moreover, interference signals from invalid areas such as exposed substrates, stains, and scratches can easily lead to misjudgments.

[0026] This application provides a solution that acquires measurement signals in real time and processes them in parallel, significantly improving the real-time resolution throughput of film thickness during line scan measurement, ensuring the real-time performance of the measurement, effectively distinguishing invalid measurement signals, improving the robustness of the measurement and the reliability of the resolution results, and solving the technical problem of difficulty in quickly and accurately resolving the large amount of data acquired when measuring film thickness by line scan.

[0027] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or a real-time film thickness measurement device capable of performing the above functions. This embodiment does not specifically limit the scope of the embodiment. The following uses a real-time film thickness measurement device as an example to describe this embodiment and the following embodiments.

[0028] This application provides a method for real-time measurement of thin film thickness, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the real-time film thickness measurement method of this application.

[0029] In this embodiment, the real-time film thickness measurement method includes steps S10~S50: Step S10: Real-time acquisition of a two-dimensional interference image of the thin film under test at the current scanning position, and parallel calculation of key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency. It should be noted that the film under test is the film whose thickness is currently being measured, and the current scanning position is the position where a line scan is currently being performed. (Reference) Figure 2 In this embodiment, the line scan measurement device is used to acquire two-dimensional interferometric images along the motion direction in real time; the multi-threaded control unit realizes asynchronous pipelined control processing for data acquisition, processing, and storage; the parallel computing unit performs non-uniform signal spectrum analysis to resolve the film thickness; and the result output and storage unit realizes the functions of outputting and storing measurement results. The parallel computing unit can employ a parallel processor, such as a GPU (Graphics Processing Unit), but this embodiment does not specifically limit its use.

[0030] Additionally, it should be noted that the reference Figure 3 The line scanning measurement device includes an imaging module 100 and an imaging spectrometer 200. The imaging module 100 collects and guides the measurement light signal generated at the thin film 300 under test into the imaging spectrometer 200, where it is received by the detector 205 and a measurement signal is generated. The imaging module 100 consists of an illumination module 101 and an imaging lens 102. The illumination module 101 provides an illumination source for detection, such as an LED or halogen lamp, which matches the measurement spectral range of the imaging spectrometer 200. In this embodiment, the illumination module 101 is built-in as coaxial illumination. The imaging lens 102 can be a dual telecentric lens, which can reduce the difficulty of off-axis field-of-view correction. Furthermore, it uses a line scanning objective lens, with a single measurement width of L1, corresponding to the measurement range of width L1 on the thin film 300 under test. The interference spectral signal generated within the test range of width L1 in the thin film 300 is transmitted through the imaging lens 101 into the entrance slit 201 of the imaging spectrometer 200. The length L2 of the entrance slit 201 matches L1 and is related to the magnification of the imaging lens 101. In this embodiment, the measurement signal (interference spectral signal) entering the entrance slit 201 passes through the collimating lens 202, grating 203, and focusing lens 204 inside the imaging spectrometer 200, and is then received by the detector 205 and converted into an electrical signal. The detector can be a CMOS (Complementary Metal-Oxide Semiconductor) or CCD (Charge Coupled Device) array detector. Finally, the test range of width L1 on the thin film 300 can form an image with spectral data in a single measurement, i.e., a two-dimensional interference image with an image size of W×H, where H corresponds to the scanning width of the line scanning measurement device, and W corresponds to the wavelength, i.e., the spectral dimension.

[0031] It is understandable that the scanning measurement device is based on non-contact thin film thickness measurement using white light spectral interferometry. Its basic principle is that a broadband light source, after being reflected from the upper and lower surfaces of the thin film under test, forms an interference spectral signal, the intensity distribution of which can be simplified as follows:

[0032] In the formula, This indicates the thickness of the film being measured. This represents the refractive index of the material of the thin film under test. Indicates wavelength. Indicates the initial phase. Indicates the ratio of incident light intensity to background light intensity. Let the pixel index represent the visual function. The relationship between the pixel index and wavelength in the imaging spectrometer within the line scan measurement device is non-linear, resulting in a non-uniformly sampled signal in the final measurement. Let the pixel index... Then the phase term in the intensity distribution can be transformed into a linear form, as shown below:

[0033] In the formula, Indicates phase, Indicates wavelength. Indicates the initial phase. This represents the refractive index of the thin film under test. It can be seen that the interference signal is periodic in the wavenumber domain, and the periodicity... Therefore, by finding the dominant frequency in the wavenumber domain... The thickness of the thin film under test can then be determined by inversion, as shown below:

[0034] In the formula, This indicates the thickness of the film being measured. This represents the refractive index of the material of the thin film under test. This indicates the main frequency. This method supports non-uniform sampling signals. Therefore, resampling is unnecessary, avoiding the errors and delays caused by interpolation required in traditional FFT. Furthermore, based on the material's refractive index... The range of process thickness can limit the range of search frequency, reducing the amount of computation.

[0035] It should be understood that, reference Figure 4 This embodiment adopts a multi-threaded asynchronous processing architecture to realize measurement data acquisition, GPU processing and result storage, mainly including initialization, measurement data acquisition thread, CPU and GPU interaction thread and measurement result storage thread.

[0036] During initialization, relevant hardware needs to be initialized, such as setting detector connection and signal acquisition parameters, and setting illumination source intensity; GPU memory needs to be configured, for example, by preloading background image data. This involves allocating memory for intermediate variables and acquiring image signals, among other things; it also requires configuring calculation-related parameters, such as the reliability threshold. The refractive index of the thin film to be tested Process thickness range Wavelength array The wavenumber domain frequency search range is calculated based on the process thickness range and the refractive index of the thin film under test. It is discretized into a frequency grid. The discretized frequency grid spacing can typically be set from nanometers to tens of nanometers, and the wavelength array can be preprocessed and converted into a wavenumber domain array. , To further improve computational efficiency, this embodiment converts the wavelength array into a relative wavenumber domain array. , At this point, the a priori process thickness range relative wavenumber domain frequency search range One-to-one correspondence; weights need to be configured, which can be uniform weights or adaptive weights based on signal-to-noise ratio; three independent threads are started, namely the measurement data acquisition thread, the CPU and GPU interaction thread, and the measurement result storage thread.

[0037] The measurement data acquisition thread continuously acquires two-dimensional interferometric images from the line scan measurement device and adds them to the processing queue Q1. Queue Q1 has a first-in, first-out (FIFO) characteristic, ensuring that the acquired images can be processed sequentially. If a stop command is received, acquisition stops, Q1 is marked as finished, no more data is added, and the process waits for subsequent processing to complete. The buffering provided by queue Q1 tolerates short processing delays, allowing for continuous acquisition independent of processing speed.

[0038] The CPU-GPU interaction thread continuously retrieves 2D interference images from queue Q1, transmits them to the GPU for data processing, and retrieves the processing results from the GPU, adding them to queue Q2. If queue Q1 finishes its task and is empty, Q2 is marked as complete, and no new processing results are added to Q2; the thread then waits for the storage task to complete. This thread enables efficient collaboration between the CPU and GPU, ensuring ordered output results through queue Q2.

[0039] The measurement result storage thread reads the thickness results from Q2, records and stores them in a preset format (e.g., CSV, JSON), and pushes the current thickness analysis results to the monitoring interface, control system, or performs remote data transmission as needed. The thread terminates if queue Q2 is marked as complete and there is no remaining data. The measurement result storage thread is independent of the processing flow, ensuring that results are not lost. It relies on the characteristics of queues Q1 and Q2 to ensure the orderly output of thickness analysis results.

[0040] It should be noted that this can be expanded into multiple Q1 queues, each corresponding to a different detector channel, to support multiple line scan measurement devices. Furthermore, multiple parallel computing units can be set up to process the data separately, further improving the throughput of processed data.

[0041] In one feasible implementation, before step S10, the following steps may be included: calculating the relative wavenumber domain frequency search range based on the material refractive index and process thickness range of the thin film to be tested; and discretizing the relative wavenumber domain frequency search range to obtain the relative wavenumber domain frequency.

[0042] Understandably, before performing thickness analysis, it is necessary to determine the refractive index of the thin film being measured. and process thickness range The search range of frequencies in the relative wavenumber domain is calculated in advance, i.e., the relative wavenumber domain frequency search range. ,in, , , This represents the lower limit of the process thickness range. This represents the upper limit of the process thickness range. This represents the lower limit of the relative wavenumber domain frequency search range. This represents the upper limit of the relative wavenumber domain frequency search range.

[0043] It should be understood that discretizing the relative wavenumber domain frequency search range yields multiple discrete relative wavenumber domain frequencies.

[0044] In one feasible implementation, step S10 may include steps S101 to S104: Step S101: Acquire the two-dimensional interference image of the thin film under test at the current scanning position in real time, and calculate the trigonometric function values ​​of the interference spectral signals of each row of the two-dimensional interference image in the relative wavenumber domain frequency in parallel. It should be noted that the parallel computing unit (GPU) acquires the two-dimensional interferometric image from the line scan measurement device via the CPU. Among them, row index Corresponding spatial location, i.e., scan width, column index Corresponding wavelength In other words, the spectral dimension. The data in a two-dimensional interferometric image can essentially be considered as an interferometric spectral signal. Before processing the interferometric spectral signal, it can be normalized using the background intensity, as shown below:

[0045] In the formula, This represents the normalized interference spectrum signal, i.e., the normalized signal. This represents the original interference spectrum signal of a two-dimensional interference image. Indicates background intensity.

[0046] It is understandable that the trigonometric function values ​​include cosine and sinine trigonometric function values. The cosine and sinine trigonometric function values ​​of each row of the interferometric spectrum signal are calculated in parallel at each relative wavenumber frequency. For the second row of the two-dimensional interferometric image... The calculation formula for the horizontal interferometric spectral signal is shown below:

[0047]

[0048] In the formula, , representing the in the relative wavenumber field array One value, Indicates the first A relative wavenumber domain frequency, Indicates the first The i-th relative wavenumber domain frequency at the i-th frequency The column's sine trigonometric function values, Indicates the first The i-th relative wavenumber domain frequency at the i-th frequency The column's cosine trigonometric function values.

[0049] Step S102: Based on the trigonometric function values ​​of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency and the weights corresponding to the trigonometric function values, the weighted trigonometric statistics of the interference spectral signals of each row of the two-dimensional interference image are calculated in parallel. It should be noted that the weighted trigonometric statistics are the correlation statistics obtained by weighting the trigonometric function values. They include four statistics: the first weighted statistic, the second weighted statistic, the third weighted statistic, and the fourth weighted statistic. In this embodiment, the weighted trigonometric statistics for each row of the interferometric spectral signal at each relative wavenumber domain frequency are calculated in parallel. For the second row of the two-dimensional interferometric image... The calculation formula for the horizontal interferometric spectral signal is shown below:

[0050]

[0051] In the formula, , , , The first The first, second, third, and fourth weighted statistics at each relative wavenumber frequency. and For the first Trigonometric function values ​​in the relative wavenumber domain frequency domain The weights corresponding to the trigonometric function values ​​(can be set during initialization).

[0052] Step S103: Based on the weighted triangular statistics of the interference spectral signals of each row of the two-dimensional interference image, calculate the signal projection of the interference spectral signals of each row of the two-dimensional interference image in parallel. It should be noted that the key statistical indicators are the important data involved in calculating the normalized power spectrum. In this embodiment, the key statistical indicators include the signal projection quantity and the correction statistics.

[0053] It is understandable that the signal projection quantity, i.e., the weighted triangular statistics, is the data obtained after projection. For the second two-dimensional interferometric image... The calculation formula for the horizontal interferometric spectral signal is shown below:

[0054]

[0055] In the formula, For the first The projection quantity corresponding to the first weighted statistic at each relative wavenumber domain frequency. For the first The projection quantity corresponding to the second weighted statistic at each relative wavenumber domain frequency. This represents the normalized interference spectrum signal.

[0056] Step S104: Correct the mean influence error in the weighted triangular statistics of each row of interference spectral signals of the two-dimensional interference image to obtain the corrected statistics.

[0057] Understandably, the correction statistic is the statistic obtained after eliminating the influence of the mean, including the first correction statistic, the second correction statistic, and the third correction statistic. For a two-dimensional interferometric image... The calculation formula for the horizontal interferometric spectral signal is shown below:

[0058]

[0059]

[0060] In the formula, , , The first The first, second, and third correction statistics at relative wavenumber domain frequencies. , , , The first The first, second, third, and fourth weighted statistics at each relative wavenumber domain frequency.

[0061] Step S20: Based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency, determine the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interference image; In one feasible implementation, step S20 may include steps S201 to S203: Step S201: Based on the interference spectral signals of each row of the two-dimensional interference image and the weights corresponding to the interference spectral signals, calculate the weighted variance of the interference spectral signals of each row of the two-dimensional interference image in parallel. It should be noted that after obtaining the two-dimensional interferometric image, some statistics can be pre-calculated, such as weighted mean, weighted bias, and weighted variance.

[0062] It is understandable that this embodiment calculates the weighted mean, weighted bias, and weighted variance of each row of the interference spectral signal in parallel. For the second row of the two-dimensional interference image... The calculation formula for the horizontal interferometric spectral signal is shown below:

[0063]

[0064]

[0065] In the formula, This represents the weighted average. Indicates weighted bias. Indicates the weighted variance. The weights corresponding to the interference spectrum signals (can be set during initialization). This represents the normalized interference spectrum signal. This represents the number of pixels in the horizontal direction of a two-dimensional interference image, i.e., the number of sampling points in the spectral channel, with each pixel corresponding to a wavelength.

[0066] Step S202: Obtain the correspondence between key statistical indicators, weighted variance, and normalized power spectrum; It should be noted that the correspondence between key statistical indicators, weighted variance, and normalized power spectrum, i.e., the calculation formula for normalized power spectrum, is as follows:

[0067] In the formula, Represents the normalized power spectrum. Indicates the weighted variance. , , These are the first, second, and third revised statistics, respectively. and For signal projection quantity, For discriminant, .

[0068] Step S203: Based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency, the weighted variance of the interference spectral signals of each row of the two-dimensional interference image, and the corresponding relationship, determine the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interference image.

[0069] Understandably, by substituting the relevant data into the correspondence between the key statistical indicators, weighted variance, and normalized power spectrum mentioned above, the normalized power spectrum of each row of the interference spectrum signal in the two-dimensional interference image can be calculated.

[0070] It should be understood that when When the normalized power spectrum is zero, it is recorded as 0 to avoid division by zero; when When the power spectrum is less than the set threshold (e.g., 1e-8), the normalized power spectrum is recorded as 0 to avoid calculation accuracy errors caused by an excessively small denominator.

[0071] Step S30: Based on the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image, determine the power peak value of each row of the interference spectral signal of the two-dimensional interference image; It should be noted that the maximum power value in the normalized power spectrum is the peak power. In specific implementations, in... Search maximum value This corresponds to the peak power.

[0072] Step S40: Based on the power peak values ​​of the interference spectral signals of each row of the two-dimensional interference image, determine the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interference image; It is understandable that this embodiment uses a relative wavenumber domain array. , At this point, the film thickness obtained through analysis / measurement can be considered as... The corresponding frequency value Effective thickness refers to a reliable value determined after a reliability assessment of the film thickness obtained through analysis / measurement.

[0073] Step S50: Based on the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image, determine the thickness distribution of the film under test at the current scanning position.

[0074] It should be noted that the width can be obtained from the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image. The distribution of film thickness within the range, i.e., the thickness distribution of the film under test at the current scanning position. When scanning continuously, it can be expanded to form a two-dimensional thickness map.

[0075] In the specific implementation, refer to Figure 5 The GPU preprocesses the input data, pre-calculates statistics, calculates the normalized power spectrum, and outputs the effective thickness.

[0076] This embodiment provides a real-time thin film thickness measurement method. It acquires a two-dimensional interferometric image of the thin film under test at the current scanning position in real time, and calculates key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency in parallel. Based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency, it determines the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image. Based on the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image, it determines the peak power of the interference spectral signals of each row of the two-dimensional interferometric image. Based on the peak power of the interference spectral signals of each row of the two-dimensional interferometric image, it determines the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interferometric image. Based on the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interferometric image, it determines the thickness distribution of the thin film under test at the current scanning position. This embodiment acquires the measurement signal in real time and processes the measurement signal in parallel, significantly improving the real-time resolution throughput of thin film thickness during line scan measurement, ensuring the real-time performance of the measurement, effectively distinguishing invalid measurement signals, and improving the robustness of the measurement and the reliability of the resolution results.

[0077] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 Step S40 may include steps S401 to S402: Step S401: The relative wavenumber domain frequency corresponding to the power peak of each row of the interference spectral signal of the two-dimensional interference image is taken as the measured thickness corresponding to each row of the interference spectral signal of the two-dimensional interference image. It should be noted that the measured thickness refers to the film thickness obtained through analysis / measurement. In this embodiment, the measured thickness can be considered as... The corresponding relative wavenumber domain frequency .

[0078] Step S402: When the power peak value of the interference spectrum signal corresponding to the measured thickness is greater than or equal to the reliability threshold, the measured thickness is taken as the effective thickness.

[0079] Understandably, the reliability threshold This is a threshold set in this embodiment for evaluating the reliability of the measured thickness. If the thickness is not accurately measured, it indicates that the film thickness obtained from parsing the current row of data is unreliable, and the current measurement thickness is marked as invalid (e.g., return -1). If the measured film thickness meets the reliability requirements, then the current measured thickness is considered to be the effective thickness.

[0080] It should be understood that reliability thresholds can be set in different ways.

[0081] In one feasible implementation, the step of determining the reliability threshold may include: determining the number of samples based on the number of horizontal pixels in the two-dimensional interferometric image; and determining the reliability threshold based on the number of samples.

[0082] It should be noted that the number of pixels in the horizontal direction of a two-dimensional interference image is the number of pixels contained in each row of the two-dimensional interference image in the horizontal direction. Each pixel corresponds to a wavelength, and the number of samples is the number of sampling points in the spectral channel. The number of pixels in the horizontal direction of a two-dimensional interference image is equal to the number of samples.

[0083] Understandably, this can be determined based on the number of samples. Determine the corresponding absolute intensity threshold The absolute strength threshold is used as the reliability threshold. For example, if... ,but It can be 0.05~0.1, if ,but It can be 0.03~0.06. Real interference fringes are usually very strong, often accounting for 10%~50% or even more of the total energy. If the peak value is less than 5%, it means the contrast is too low and unreliable.

[0084] In another feasible implementation, the step of determining the reliability threshold may include: removing the power peaks of each row of the interference spectral signal of the two-dimensional interferometric image and the power values ​​within a preset range of the power peaks to obtain the evaluation power value of the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interferometric image; determining the corresponding power median from the evaluation frequency values ​​of the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interferometric image; and determining the reliability threshold of each row of the interference spectral signal of the two-dimensional interferometric image based on the power median of the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interferometric image and a preset relative significance threshold.

[0085] It should be noted that the relative significance threshold can be used as a basis. A reliability threshold is set. In practical implementation, the thickness measurement can be marked as valid if the following formula is met:

[0086] In the formula, Peak power The relative significance threshold, This represents the median power.

[0087] It is understandable that the preset range is the pre-defined range adjacent to the power peak. The evaluated power value refers to the power value remaining after removing the power peak and the power values ​​within its range, which can be used to evaluate the median. The power median is the median among the evaluated power values. The preset relative significance threshold is the relative significance threshold preset in this embodiment. Since the actual signal peak should be much higher than the background noise level, the preset relative significance threshold can be 4 to 6. If the peak is only slightly higher than the background, such as 1.5 times, it is likely a noise spike. The median power and the preset relative significance threshold are multiplied together to obtain the reliability threshold.

[0088] Furthermore, the reliability threshold can also be set as an adaptive threshold. For example, it can be combined with the absolute strength threshold. With relative significance threshold Set a reliability threshold, and set an absolute strength threshold. As the first reliability threshold, the relative significance threshold The product of the first reliability threshold and the median power is used as the second reliability threshold. The first reliability threshold and the second reliability threshold are weighted and then weighted to calculate the final reliability threshold. The weights can be set according to the number of samples and the median power, but this embodiment does not make specific limitations on them.

[0089] It should be understood that by using the reliability threshold, invalid interference signals from areas such as exposed substrates, stains, and scratches can be effectively removed, thereby improving the reliability of the film thickness calculation results.

[0090] For example, refer to Figure 7 , Figure 7 To acquire a two-dimensional interferometric image at a specific location, with H×W pixels, the horizontal direction represents the spectral dimension, with W pixels corresponding to a wavelength range of approximately 485nm~700nm, which can be obtained through calibration. The vertical direction corresponds to the measurement width L1, with H pixels. This means the range of L1 is divided into H measurements, implying that a single measurement requires extracting and resolving the film thickness at the corresponding measurement point from H rows of pixels. Assuming the two-dimensional interferometric image has 5120×4096 pixels, a single measurement requires processing 4096 spectral data points. In actual line scan measurements, the detector's acquisition speed exceeds 100 frames per second, resulting in approximately 400,000 data points needing to be resolved per second. (Reference) Figure 8 It shows from Figure 7 A single line of interference spectrum signal is extracted from the two-dimensional interference image. The horizontal axis is transformed from the wavelength domain to the wavenumber domain, exhibiting significant periodicity. The vertical axis represents the signal intensity. Analytical calculation of the film thickness yields results such as... Figure 9 The normalized power spectrum shown has the x-axis representing frequency (if a relative wavenumber domain array was used in the previous calculations, then the frequency equals the film thickness). If wavenumber domain arrays are used in the initial calculations, then the frequency equals the optical thickness. , The ordinate represents the material refractive index, and the ordinate represents the normalized power. Based on the process thickness range, the thickness of the film to be measured was set to 12μm~20μm, with a refractive index of 1.515. Analytical calculations were performed in the wavenumber domain, revealing a significant peak value greater than 0.5, corresponding to a frequency of 48.844. When the reliability threshold Q is set between 0.1 and 0.5 (verified based on experience and experimental testing), the analytical result is considered valid and reliable. The final film thickness at this point is... The analysis result is:

[0091] This embodiment provides a real-time thin film thickness measurement method. The relative wavenumber domain frequency corresponding to the power peak of the interference spectral signal in each row of a two-dimensional interferometric image is used as the measured thickness corresponding to that row. When the power peak of the interference spectral signal corresponding to the measured thickness is greater than or equal to a reliability threshold, the measured thickness is taken as the valid thickness. This embodiment acquires the measurement signal in real time and processes it in parallel, significantly improving the real-time resolution throughput of thin film thickness during line scan measurement, ensuring the real-time performance of the measurement. Furthermore, the reliability threshold effectively distinguishes invalid measurement signals, avoiding interference from invalid interference signals, and improving the robustness of the measurement and the reliability of the analytical results.

[0092] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the real-time film thickness measurement method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0093] This application also provides a real-time film thickness measurement device; please refer to... Figure 10 The real-time film thickness measurement device includes: The power spectrum calculation module 10 is used to acquire the two-dimensional interference image of the thin film under test at the current scanning position in real time, and to calculate the key statistical indicators of the interference spectrum signal of each row of the two-dimensional interference image in the relative wavenumber domain frequency in parallel. The power spectrum calculation module 10 is also used to determine the normalized power spectrum of each row of the two-dimensional interferometric image based on the key statistical indicators of the interferometric spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency. The reliability assessment module 20 is used to determine the power peak value of each row of the interference spectral signal of the two-dimensional interference image based on the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image; The reliability assessment module 20 is also used to determine the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image based on the power peak value of each row of interference spectral signals in the two-dimensional interference image; The film thickness output module 30 is used to determine the thickness distribution of the film under test at the current scanning position based on the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interference image.

[0094] In one feasible implementation, the power spectrum calculation module 10 is also used to acquire the two-dimensional interference image of the thin film under test at the current scanning position in real time, and to calculate the trigonometric function values ​​of each row of interference spectrum signal of the two-dimensional interference image in the relative wavenumber domain frequency in parallel. Based on the trigonometric function values ​​of each row of the interference spectral signal of the two-dimensional interferometric image at the relative wavenumber domain frequency and the weights corresponding to the trigonometric function values, the weighted trigonometric statistics of each row of the interference spectral signal of the two-dimensional interferometric image are calculated in parallel. Based on the weighted triangular statistics of the interference spectral signals of each row of the two-dimensional interference image, the signal projection of the interference spectral signals of each row of the two-dimensional interference image is calculated in parallel. The mean influence error in the weighted triangular statistics of each row of interference spectral signals in the two-dimensional interference image is corrected to obtain the corrected statistics.

[0095] In one feasible implementation, the power spectrum calculation module 10 is further configured to calculate the weighted variance of each row of the two-dimensional interference image based on the interference spectral signals of each row of the two-dimensional interference image and the weights corresponding to the interference spectral signals. Obtain the correspondence between key statistical indicators, weighted variance, and normalized power spectrum; Based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency, the weighted variance of the interference spectral signals of each row of the two-dimensional interferometric image, and the corresponding relationship, the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image is determined.

[0096] In one feasible implementation, the reliability assessment module 20 is further configured to use the relative wavenumber domain frequency corresponding to the power peak of each row of interference spectral signals of the two-dimensional interference image as the measurement thickness corresponding to each row of interference spectral signals of the two-dimensional interference image. When the power peak value of the interference spectrum signal corresponding to the measured thickness is greater than or equal to the reliability threshold, the measured thickness is taken as the effective thickness.

[0097] In one feasible implementation, the reliability assessment module 20 is further configured to determine the number of samples based on the number of horizontal pixels in the two-dimensional interferometric image; Based on the number of samples, a reliability threshold is determined.

[0098] In one feasible implementation, the reliability assessment module 20 is further configured to remove the power peaks of the interference spectral signals of each row of the two-dimensional interference image and the power values ​​within a preset range of the power peaks, so as to obtain the normalized power spectrum assessment power value of the interference spectral signals of each row of the two-dimensional interference image. The median power is determined from the evaluation frequency values ​​of the normalized power spectrum of each row of the interference spectral signal in the two-dimensional interference image; Based on the median power of the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image and a preset relative significance threshold, the reliability threshold of each row of the interference spectral signal of the two-dimensional interference image is determined.

[0099] In one feasible implementation, the power spectrum calculation module 10 is further used to calculate the relative wavenumber domain frequency search range based on the material refractive index and process thickness range of the thin film under test. The relative wavenumber domain frequency search range is discretized to obtain the relative wavenumber domain frequency.

[0100] The real-time film thickness measurement device provided in this application, employing the real-time film thickness measurement method described in the above embodiments, can solve the technical problem of difficulty in quickly and accurately analyzing the large amount of data collected when measuring film thickness via line scanning. Compared with the prior art, the beneficial effects of the real-time film thickness measurement device provided in this application are the same as those of the real-time film thickness measurement method provided in the above embodiments, and other technical features in the real-time film thickness measurement device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0101] This application provides a real-time film thickness measurement device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the real-time film thickness measurement method in Embodiment 1 above.

[0102] The following is for reference. Figure 11 The diagram illustrates a structural schematic suitable for implementing a real-time film thickness measurement device according to embodiments of this application. The real-time film thickness measurement device in embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 11 The real-time film thickness measurement device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0103] like Figure 11As shown, the real-time film thickness measurement device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in ROM (Read Only Memory) 1002 or a program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the real-time film thickness measurement device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touch screens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. The communication device 1009 allows the real-time film thickness measurement device to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows a real-time film thickness measurement device with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0104] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0105] The real-time film thickness measurement device provided in this application, employing the real-time film thickness measurement method described in the above embodiments, can solve the technical problem of difficulty in quickly and accurately analyzing the large amount of data collected when measuring film thickness via line scanning. Compared with the prior art, the beneficial effects of the real-time film thickness measurement device provided in this application are the same as those of the real-time film thickness measurement method provided in the above embodiments, and other technical features of this real-time film thickness measurement device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0106] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0107] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0108] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the real-time film thickness measurement method in the above embodiments.

[0109] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0110] The aforementioned computer-readable storage medium may be included in the real-time film thickness measurement device; or it may exist independently and not be assembled into the real-time film thickness measurement device.

[0111] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the real-time film thickness measurement device, the device causes the following: real-time acquisition of a two-dimensional interferometric image of the film under test at the current scanning position; parallel calculation of key statistical indicators of the interferometric spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency; determination of the normalized power spectrum of each row of the interferometric spectral signals of the two-dimensional interferometric image based on the key statistical indicators of the interferometric spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency; determination of the power peak value of each row of the interferometric spectral signals of the two-dimensional interferometric image based on the normalized power spectrum of each row of the interferometric spectral signals of the two-dimensional interferometric image; determination of the effective thickness corresponding to each row of the interferometric spectral signals of the two-dimensional interferometric image based on the power peak value of each row of the interferometric spectral signals of the two-dimensional interferometric image; and determination of the thickness distribution of the film under test at the current scanning position based on the effective thickness corresponding to each row of the interferometric spectral signals of the two-dimensional interferometric image.

[0112] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0114] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0115] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described real-time film thickness measurement method. This solves the technical problem of difficulty in quickly and accurately parsing the large amount of data collected when measuring film thickness via line scanning. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the real-time film thickness measurement method provided in the above embodiments, and will not be repeated here.

[0116] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the real-time film thickness measurement method described above.

[0117] The computer program product provided in this application can solve the technical problem of difficulty in quickly and accurately analyzing the large amount of data collected when measuring film thickness by line scanning. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the real-time film thickness measurement method provided in the above embodiments, and will not be repeated here.

[0118] The above are only some embodiments of this application and do not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for real-time measurement of thin film thickness, characterized in that, The method includes: The two-dimensional interference image of the thin film under test at the current scanning position is acquired in real time, and the key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image at the relative wavenumber domain frequency are calculated in parallel. Based on the key statistical indices of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency, the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image is determined. Based on the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image, the power peak value of each row of the interference spectral signal of the two-dimensional interference image is determined; Based on the power peak value of each row of the interference spectral signal of the two-dimensional interference image, the effective thickness corresponding to each row of the interference spectral signal of the two-dimensional interference image is determined; Based on the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image, the thickness distribution of the thin film under test at the current scanning position is determined.

2. The method as described in claim 1, characterized in that, The key statistical indicators include signal projection and correction statistics. The steps of acquiring the two-dimensional interferometric image of the thin film under test at the current scanning position in real time and calculating the key statistical indicators of the interferometric spectral signals of each row of the two-dimensional interferometric image in the relative wavenumber domain frequency include: The two-dimensional interference image of the thin film under test at the current scanning position is acquired in real time, and the trigonometric function values ​​of each row of the interference spectrum signal of the two-dimensional interference image at the relative wavenumber domain frequency are calculated in parallel. Based on the trigonometric function values ​​of each row of the interference spectral signal of the two-dimensional interference image at the relative wavenumber domain frequency and the weights corresponding to the trigonometric function values, the weighted trigonometric statistics of each row of the interference spectral signal of the two-dimensional interference image are calculated in parallel. Based on the weighted triangular statistics of the interference spectral signals of each row of the two-dimensional interference image, the signal projection of the interference spectral signals of each row of the two-dimensional interference image is calculated in parallel. The mean influence error in the weighted triangular statistics of each row of interference spectral signals in the two-dimensional interference image is corrected to obtain the corrected statistics.

3. The method as described in claim 1, characterized in that, The step of determining the normalized power spectrum of each row of the two-dimensional interferometric image based on the key statistical indices of the interferometric spectral signals in the relative wavenumber domain includes: Based on the interference spectral signals of each row of the two-dimensional interference image and the weights corresponding to the interference spectral signals, the weighted variance of the interference spectral signals of each row of the two-dimensional interference image is calculated in parallel. Obtain the correspondence between key statistical indicators, weighted variance, and normalized power spectrum; Based on the key statistical indicators of the interference spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency, the weighted variance of the interference spectral signals of each row of the two-dimensional interferometric image, and the corresponding relationship, the normalized power spectrum of the interference spectral signals of each row of the two-dimensional interferometric image is determined.

4. The method as described in claim 1, characterized in that, The step of determining the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image based on the power peak value of each row of interference spectral signals includes: The relative wavenumber frequency corresponding to the power peak of each row of the interference spectral signal of the two-dimensional interference image is taken as the measured thickness corresponding to each row of the interference spectral signal of the two-dimensional interference image; When the power peak value of the interference spectrum signal corresponding to the measured thickness is greater than or equal to the reliability threshold, the measured thickness is taken as the effective thickness.

5. The method as described in claim 4, characterized in that, The method further includes: The number of samples is determined based on the number of pixels in the horizontal direction of the two-dimensional interference image; Based on the number of samples, a reliability threshold is determined.

6. The method as described in claim 4, characterized in that, The method further includes: The power peaks of the interference spectral signals in each row of the two-dimensional interference image and the power values ​​within a preset range of the power peaks are removed to obtain the normalized power spectrum evaluation power value of the interference spectral signals in each row of the two-dimensional interference image. The median power is determined from the evaluation frequency values ​​of the normalized power spectrum of each row of the interference spectral signal in the two-dimensional interference image; Based on the median power of the normalized power spectrum of each row of the interference spectral signal of the two-dimensional interference image and a preset relative significance threshold, the reliability threshold of each row of the interference spectral signal of the two-dimensional interference image is determined.

7. The method according to any one of claims 1 to 6, characterized in that, Before the step of acquiring the two-dimensional interference image of the thin film under test at the current scanning position in real time and calculating the key statistical indicators of the interference spectral signals of each row of the two-dimensional interference image in the relative wavenumber domain frequency, the method further includes: Based on the material refractive index and process thickness range of the thin film under test, the relative wavenumber domain frequency search range is calculated. The relative wavenumber domain frequency search range is discretized to obtain the relative wavenumber domain frequency.

8. A real-time film thickness measuring device, characterized in that, The device includes: The power spectrum calculation module is used to acquire the two-dimensional interference image of the thin film under test at the current scanning position in real time, and to calculate the key statistical indicators of the interference spectrum signal of each row of the two-dimensional interference image in the relative wavenumber domain frequency in parallel. The power spectrum calculation module is also used to determine the normalized power spectrum of each row of the two-dimensional interferometric image based on the key statistical indicators of the interferometric spectral signals of each row of the two-dimensional interferometric image at the relative wavenumber domain frequency. The reliability assessment module is used to determine the power peak value of each row of the interference spectral signal of the two-dimensional interference image based on the normalized power spectrum of each row of the interference spectral signal. The reliability assessment module is also used to determine the effective thickness corresponding to each row of interference spectral signals in the two-dimensional interference image based on the power peak value of each row of interference spectral signals in the two-dimensional interference image; The film thickness output module is used to determine the thickness distribution of the film under test at the current scanning position based on the effective thickness corresponding to the interference spectral signals of each row of the two-dimensional interference image.

9. A real-time film thickness measurement device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the real-time film thickness measurement method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the real-time film thickness measurement method as described in any one of claims 1 to 7.

Images