Method for identifying overlapping peaks in spectroscopic measurement data, thickness measurement method and equipment

Abstract

The invention provides a method for identifying overlapping peaks in spectroscopic measurement data, a thickness measurement method and equipment, and relates to the technical field of data processing. The method comprises the following steps: acquiring target spectroscopic measurement data; carrying out peak value detection on the target spectroscopic measurement data to obtain a main peak identification result; identifying a relative position of the second peak value and the main peak value based on the main peak identification result; determining an independent variable range based on the target spectroscopic measurement data and the relative position, and generating a half measurement result containing a main peak value; a user-defined function is used for fitting the half measurement result, a first fitting function is obtained, and the first fitting function comprises a main peak position; substituting global independent variables in the target spectroscopic measurement data into the first fitting function to obtain a first fitting result; obtaining second peak data based on the target spectroscopic measurement data and the first fitting result; and fitting the second peak data by using a self-defined function to obtain a second fitting function which comprises a second peak position.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a method for identifying overlapping peaks in spectroscopic measurement data, a thickness measurement method, and a device. Background Art

[0002] Measurement and analysis technologies such as spectroscopy and energy spectroscopy are important steps in scientific research and industrial production. By analyzing the data of spectroscopy and energy spectroscopy, effective information can be extracted. For example, the position of a peak can provide physical or chemical intensity attributes, and the area of a peak can provide physical or chemical breadth attributes. However, in the actual spectroscopic analysis data obtained by measurement, due to the thermodynamic fluctuations in the physical properties of the system particles, there are various broadenings. Therefore, in the actual analysis data, there are often peaks with a certain width, and sometimes the width of the peak will affect the accurate attribution of the peak position. Summary of the Invention

[0003] In view of this, the present invention provides a method for identifying overlapping peaks in spectroscopic measurement data, a thickness measurement method, and a device.

[0004] In a first aspect, an embodiment of the present invention provides a method for identifying overlapping peaks in spectroscopic measurement data, including: obtaining target spectroscopic measurement data; performing peak detection on the target spectroscopic measurement data to obtain a main peak identification result; identifying the relative position of the second peak and the main peak peak based on the main peak identification result; determining an independent variable range based on the target spectroscopic measurement data and the relative position, and generating a half-side measurement result including the main peak peak; using a custom function to fit the half-side measurement result to obtain a first fitting function, where the first fitting function includes the main peak position; substituting the global independent variable in the target spectroscopic measurement data into the first fitting function to obtain a first fitting result; obtaining second peak data based on the target spectroscopic measurement data and the first fitting result; using a custom function to fit the second peak data to obtain a second fitting function, where the second fitting function includes the second peak position.

[0005] In a second aspect, an embodiment of the present invention provides a thickness measurement method, which includes: obtaining the main peak peak and the second peak peak of the current frame by using the method for identifying overlapping peaks in spectroscopic measurement data described in any implementation manner of the first aspect; calculating the wafer thickness of the current frame according to the main peak peak and the second peak peak.

[0006] In a third aspect, an embodiment of the present invention provides a thinning control method, which includes: obtaining the wafer thickness of the current frame according to the method described in the second aspect; stopping thinning the wafer when the wafer thickness of the current frame reaches a preset thickness.

[0007] Fourthly, an embodiment of the present invention provides an overlapping peak identification device for spectroscopic measurement data. The device 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 when the instructions are executed by the at least one processor, the at least one processor is enabled to implement the overlapping peak identification method for spectroscopic measurement data described in any implementation manner of the first aspect.

[0008] Fifthly, an embodiment of the present invention provides a thickness measurement device. The device includes: a processor and a memory connected to the processor; wherein the memory stores instructions executable by the processor, and when the instructions are executed by the processor, the processor is enabled to implement the thickness measurement method described in the second aspect.

[0009] Sixthly, an embodiment of the present invention provides a thinning control device. The device includes: a processor and a memory connected to the processor; wherein the memory stores instructions executable by the processor, and when the instructions are executed by the processor, the processor is enabled to implement the thinning control method described in the third aspect.

[0010] Seventhly, an embodiment of the present invention provides a thinning machine for thinning a wafer and executing the method described in any implementation manner of the first aspect during the thinning process.

[0011] The overlapping peak identification method and device for spectroscopic measurement data provided by the embodiments of the present invention can analyze and process spectroscopic measurement data containing overlapping peaks, and accurately identify peaks such as main peaks and secondary peaks therein through relatively small amounts of data and computations, thereby improving the usability of spectroscopic measurement data.

[0012] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understandable through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0014] Figure 1 is an exemplary system architecture to which the present invention can be applied; Figure 2Flowchart of a method for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present invention; Figure 3 Flowchart of another method for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present invention; Figure 4 Flowchart of another method for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present invention; Figures 5A - 5E Schematic diagram of a method for identifying overlapping peaks in spectroscopic measurement data in an application scenario provided by an embodiment of the present invention; Figure 6 Structural block diagram of a device for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present invention; Figure 7 Structural schematic diagram of an electronic device suitable for executing a method for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present invention. Detailed implementation manners

[0015] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0016] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation to the present invention. In addition, the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0017] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can also be the internal connection of two elements. It can be a wireless connection or a wired connection. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0018] 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.

[0019] Figure 1 FIG. 100 shows an exemplary system architecture of an embodiment of a method and apparatus for identifying overlapping peaks in spectroscopic measurement data to which the present invention can be applied.

[0020] As Figure 1 shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0021] Users can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various applications for implementing information communication between the two may be installed on the terminal devices 101, 102, 103 and the server 105, such as instant messaging applications, etc.

[0022] The terminal devices 101, 102, 103 and the server 105 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices with a display screen, including but not limited to smart phones, tablet computers, laptop portable computers, and desktop computers, etc.; when the terminal devices 101, 102, 103 are software, they may be installed in the above-listed electronic devices, and may be implemented as multiple software or software modules, or may be implemented as a single software or software module, which is not specifically limited herein. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of multiple servers, or may be implemented as a single server; when the server is software, it may be implemented as multiple software or software modules, or may be implemented as a single software or software module, which is not specifically limited herein.

[0023] The server 105 can provide various services through various built-in applications. It should be noted that the data or information required to provide services can be obtained from the terminal devices 101, 102, 103 through the network 104, and can also be pre-stored locally in the server 105 in various ways. Therefore, when the server 105 detects that these data have been stored locally, it can choose to directly obtain these data from the local. In this case, the exemplary system architecture 100 may not include the terminal devices 101, 102, 103 and the network 104.

[0024] Since processes such as data analysis and processing may require a large amount of computing resources and strong computing power, the method for identifying overlapping peaks in the spectroscopic measurement data provided in the subsequent embodiments of the present invention is generally executed by the server 105 with strong computing power and a large amount of computing resources. Correspondingly, the device for identifying overlapping peaks in the spectroscopic measurement data is generally also set in the server 105. However, it should also be noted that when the terminal devices 101, 102, and 103 also have computing power and computing resources that meet the requirements, the terminal devices 101, 102, and 103 can also complete the above operations that were originally performed by the server 105 through the relevant applications installed thereon, and then output the same results as the server 105. Especially in the case where there are multiple terminal devices with different computing capabilities at the same time, when the relevant application determines that the terminal device where it is located has strong computing power and a large amount of remaining computing resources, the terminal device can be allowed to execute the above operations, thereby appropriately reducing the computing pressure on the server 105. Correspondingly, the device for identifying overlapping peaks in the spectroscopic measurement data can also be set in the terminal devices 101, 102, and 103. In this case, the exemplary system architecture 100 may not include the server 105 and the network 104 either.

[0025] It should be understood that Figure 1 the numbers of terminal devices, networks, and servers in

[0026] Please refer to Figure 2 , Figure 2 which is a flowchart of a method for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present invention. The process 200 includes the following steps: Step 201: Obtain target spectroscopic measurement data.

[0027] This step aims to obtain the corresponding target spectroscopic measurement data by the execution entity of the method for identifying overlapping peaks in spectroscopic measurement data (such as Figure 1 the server 105 shown). In this embodiment, the target spectroscopic measurement data may include at least one or more of: spectrum, energy spectrum, chromatogram, and nuclear magnetic resonance spectrum (for example, types such as ultraviolet-visible-near-infrared spectrum, X-ray photoelectron spectroscopy (XPS spectrum), solid nuclear magnetic resonance spectrum, etc.), and the measurement data generated by various spectroscopic analysis methods can be obtained. Among them, the target spectroscopic measurement data contains data with overlapping peaks, and the overlapping peaks include the main peak and the second peak.

[0028] Step 202: Perform peak detection on the target spectroscopic measurement data to obtain the main peak identification result.

[0029] This step aims to perform peak detection on the target spectroscopic measurement data by the above-mentioned execution entity, so as to obtain the main peak recognition result including the main peak. Exemplarily, it can be peak detection for a spectrum or an energy spectrum (for example, peak detection can be performed through find_peak processing), and the main peak recognition result is obtained. Exemplarily, in the case where the distance between two peaks in the measurement data is relatively small (for example, less than 2.3 times the standard deviation of the two peaks, that is, the case where the distance between the two peaks is less than the Rayleigh criterion), peak detection may only obtain the main peak recognition result L1 including the position of one peak.

[0030] In some alternative embodiments of this embodiment, for the spectroscopic measurement data of overlapping peaks, the positional relationship between the main peak and the second peak may be known or preset. In this case, the relative position of the second peak value to the main peak value can be directly determined based on this positional relationship and the main peak recognition result.

[0031] In some other alternative embodiments of this embodiment, for the spectroscopic measurement data containing overlapping peaks, the execution entity can identify the relative position of the second peak value to the main peak value based on the main peak recognition result. Exemplarily, it can be, for example, the case of super-close peaks containing two peak values, that is, including the main peak and the secondary peak. In this case, it is necessary to determine the relative position of the secondary peak value to the main peak value.

[0032] In some alternative embodiments of this embodiment, the execution entity can identify the position of the second peak value by using an integration window, and determine the relative position based on the position of the second peak value and the main peak position in the main peak recognition result. The process of using an integration window to identify the peak position belongs to a relatively mature technology and will not be elaborated here.

[0033] Step 203: Determine the independent variable range based on the target spectroscopic measurement data and the main peak recognition result, and generate a half-side measurement result including the main peak value.

[0034] In this embodiment, the target spectroscopic measurement data includes an independent variable and a dependent variable. The execution entity can determine the independent variable range based on the target spectroscopic measurement data and the main peak recognition result, and further generate a half-side measurement result including the main peak value.

[0035] Step 204: Fit the half-side measurement result using a custom function to obtain a first fitting function, and the first fitting function includes the main peak position.

[0036] This step aims to enable the executing entity to use a custom function for fitting to obtain a first fitting function, which contains parameters such as the position of the main peak. Exemplarily, considering the distribution laws of spectra and energy spectra in general cases, a pseudo Voigt function can be used to fit them. The pseudo Voigt function contains 4 parameters of the main peak: position, height, width, and the proportion of the Gaussian function. The equation of the pseudo Voigt function obtained after fitting is set as F1, and the 4 parameters are set as p1.

[0037] In some alternative embodiments of this embodiment, the form of the pseudo Voigt function is: , where amplitude represents the height of the function, frac represents the proportion of the Gaussian function in the pseudo Voigt function (the pseudo Voigt function is a certain proportion of the Gaussian function plus another proportion of the Cauchy function, and the sum of the two parts is 1, and the coefficients are not less than 0), center1 represents the position or symmetry center of the main peak, and std is the coefficient determining the width of the Gaussian function or the Cauchy function.

[0038] Step 205: Substitute the global independent variable in the target spectroscopic measurement data into the first fitting function to obtain a first fitting result.

[0039] This step aims to enable the above-mentioned executing entity to substitute the global independent variable in the target spectroscopic measurement data into the first fitting function to obtain a first fitting result. Since this first fitting function is obtained by fitting based on the half-side measurement result, therefore, substituting the global independent variable in the target spectroscopic measurement data into this first fitting function, the obtained first fitting result is the complete fitting curve containing the main peak obtained by fitting based on this half-side measurement data.

[0040] Step 206: Obtain second peak data based on the target spectroscopic measurement data and the first fitting result.

[0041] In this embodiment, the target spectroscopic measurement data contains the main peak and the second peak data. The executing entity can obtain the second peak data based on the target spectroscopic measurement data and the first fitting result.

[0042] In some alternative embodiments of this embodiment, the first fitting result mainly contains data of the main peak peak value. Therefore, the executing entity can use the target spectroscopic measurement data minus the first fitting result to obtain the second peak data.

[0043] Step 207: Use a custom function to fit the second peak data to obtain a second fitting function, and the second fitting function contains the second peak position.

[0044] This step aims to use a custom function by the executing entity to fit the second peak data. The obtained second fitting function contains the position information of the second peak, and thus the positions of the main peak and the second peak in the target spectroscopic measurement data containing overlapping peaks can be confirmed. Exemplarily, for data such as spectra and energy spectra, a pseudo Voigt function can be used to fit them. The pseudo Voigt function contains 4 parameters of the secondary peak: position, height, width, and the proportion of the Gaussian function. The pseudo Voigt function equation obtained after fitting is set as F2, and the 4 parameters are set as p2. Therefore, through the above process, p1 containing the position of the main peak and p2 containing the position of the second peak have been obtained.

[0045] The method for identifying overlapping peaks in spectroscopic measurement data provided by the embodiments of the present invention can analyze and process spectroscopic measurement data containing overlapping peaks, and accurately identify peaks such as the main peak and the secondary peak therein through relatively small amounts of data and computational amounts, which can improve the usability of spectroscopic measurement data.

[0046] Please refer to Figure 3 , Figure 3 which is a flowchart of a method for identifying overlapping peaks in spectroscopic measurement data provided by an embodiment of the present disclosure, that is, a specific implementation manner is provided for step 201 in process 200 shown in Figure 2 . Other steps in process 200 are not adjusted, and a new complete embodiment is obtained by replacing step 201 with the specific implementation manner provided in this embodiment. The process 300 includes the following steps: Step 301: Obtain the original spectroscopic measurement data.

[0047] The original spectroscopic measurement data may be the original data of one or more of spectra, energy spectra, chromatograms, and nuclear magnetic resonance spectra. The original data may contain noise data, background data, etc. In this embodiment, the noise data and background data in the original data can be processed.

[0048] Step 302: In response to the presence of preset background spectroscopic measurement data, perform background removal processing on the original spectroscopic measurement data based on the background spectroscopic measurement data to obtain the target spectroscopic measurement data after background removal.

[0049] For the case where the original spectroscopic measurement data contains background spectroscopic measurement data, the original spectroscopic measurement data can be subjected to background removal processing (for example, subtracting the background spectroscopic measurement data from the original spectroscopic measurement data) to obtain the target spectroscopic measurement data after background removal.

[0050] Step 303: In response to the absence of preset background spectroscopic measurement data, use the original spectroscopic measurement data as the target spectroscopic measurement data.

[0051] For the case where the original spectroscopy measurement data center does not contain background spectroscopy measurement data, the original spectroscopy measurement data is directly used as the target spectroscopy measurement data.

[0052] In some alternative embodiments of the present embodiment, the execution subject may further perform low-pass filtering on the target spectroscopy measurement data to obtain the target spectroscopy measurement data after noise reduction and smoothing.

[0053] Through the above process, interference factors (such as background data, noise data, etc.) in the original spectroscopy measurement data can be excluded, further improving the accuracy of analysis and identification based on the target spectroscopy measurement data.

[0054] In some alternative embodiments of the present embodiment, in any of the above embodiments, the process of determining the independent variable range based on the target spectroscopy measurement data and the relative position mainly determines the range between the independent variable limit value on the side opposite to the relative position and the independent variable value of the main peak peak value as the independent variable range based on the target spectroscopy measurement data. Further, the process includes: if the second peak is located between the main peak and the minimum value of the independent variable, the range from the independent variable value of the main peak peak to the maximum value of the independent variable is determined as the independent variable range; if the second peak is located between the main peak and the maximum value of the independent variable, the range from the minimum value of the independent variable to the independent variable value of the main peak peak is determined as the independent variable range. For example, if the secondary peak is located on the right side of the main peak (i.e., between the main peak and the maximum value of the independent variable), the independent variable range is taken as X min ~L1; if the secondary peak is located on the left side of the main peak (i.e., between the main peak and the minimum value of the independent variable), the independent variable range is taken as L1~X max 。 Further, the execution subject may construct the half-side measurement result based on the data in the target spectroscopy measurement data that conforms to the independent variable range.

[0055] Please refer to Figure 4 , Figure 4 which is a flowchart of another method for identifying overlapping peaks in spectroscopy measurement data provided by an embodiment of the present invention, where process 400 includes the following steps: Step 401: Obtain target spectroscopy measurement data.

[0056] Step 402: Perform peak detection on the target spectroscopy measurement data to obtain the main peak identification result.

[0057] Step 403: Determine the independent variable range based on the target spectroscopy measurement data and the main peak identification result, and generate a half-side measurement result including the main peak peak value.

[0058] Step 404: Fit the half-side measurement result using a custom function to obtain a first fitting function, and the first fitting function includes the main peak position.

[0059] Step 405: Substitute the global independent variable in the target spectroscopic measurement data into the first fitting function to obtain the first fitting result.

[0060] Step 406: Obtain the second peak data based on the target spectroscopic measurement data and the first fitting result.

[0061] Step 407: Fit the second peak data using a custom function to obtain a second fitting function, where the second fitting function includes the second peak position.

[0062] The above steps 401 - 407 are the same as steps 201 - 207 shown in Figure 2 For the same parts, please refer to the corresponding parts of the previous embodiment, and details will not be repeated here.

[0063] Step 408: Substitute the global variable in the target spectroscopic measurement data into the sum function of the first fitting function and the second fitting function to obtain a third fitting result, where the third fitting result includes the main peak position and the second peak position.

[0064] In some alternative embodiments of this embodiment, the form of the sum function is: , where there are a total of 4 parameters , frac, center, and std, where intensity represents the signal intensity, serial number 1 represents the main peak signal, serial number 2 represents the second peak signal (such as a secondary peak), amplitude represents the maximum value of the signal intensity, frac represents the proportion of the Gaussian signal in the signal, center represents the symmetry center of the signal, and std represents the width parameter of the signal.

[0065] Through the above process, the main peak and the second peak positions are obtained by fitting using the sum function, and the accuracy of the obtained results is higher.

[0066] For better understanding, the present invention also provides a specific implementation solution in combination with a specific application example, as shown in Figures 5A - 5E In this specific application example, a spectrum containing a main peak and a secondary peak is taken as an example for illustration. However, as mentioned above, the method for identifying overlapping peaks in the spectroscopic measurement data provided in this embodiment can be used to identify overlapping peaks in spectroscopic measurement data (one or more of spectra, energy spectra, chromatograms, and nuclear magnetic resonance spectra), not limited to spectra. For spectra, the abscissa x in the figure represents wavelength, and the ordinate y represents intensity; for energy spectra, the abscissa x in the figure represents energy, and the ordinate y represents intensity; for chromatograms, the abscissa x in the figure represents time, and the ordinate y represents intensity / concentration; for nuclear magnetic resonance, the abscissa x in the figure represents nuclear magnetic shift, and the ordinate y represents intensity.

[0067] Step 1: Collect spectral data (generate spectrum S1), and generate an example where the peak-to-peak distance is exactly at the limit of the Rayleigh criterion (the standard deviations of the two peaks are the same, and the peak-to-peak distance is 2.35482 times the standard deviation), as Figure 5A shown. When the background spectrum is included, subtract the background spectrum from spectrum S1 to obtain spectrum S2; if the background spectrum is not included, spectra S1 and S2 are the same.

[0068] Step 2: Perform low-pass filtering on spectrum S1 (S2) to obtain spectrum S3, with the cut-off frequency set to 0.06, as Figure 5B shown.

[0069] Step 3: Perform low-pass filtering on spectrum S3 to obtain a peak position of 500.4. Identify the relative position of the secondary peak and the main peak, and find that the secondary peak is on the right side of the main peak. At this time, select the minimum value of the independent variable until the peak position, and construct a half-spectrum S4, as Figure 5C shown.

[0070] Step 4: Select the minimum value of the independent variable until the peak position, perform pseudo Voigt fitting on this interval to obtain the fitting equation F1 and parameter p1. The peak position corresponding to p1 is 500.0829, which is the main peak position.

[0071] Step 5: Substitute all the independent variables of spectrum S1 into equation F1 to obtain a half-fitted spectrum S5, as Figure 5D shown.

[0072] Step 6: Subtract the half-fitted spectrum S5 from spectrum S1 (S2) to obtain a spectrum S6 composed of the secondary peak and noise, as Figure 5E shown.

[0073] Step 7: Perform pseudo Voigt function fitting on spectrum S6 to obtain equation F2 and parameter p2. The peak position corresponding to p2 is 524.1294, which is the secondary peak position.

[0074] Step 8: Substitute p1 and p2 as initial guesses into the pseudo Voigt function of the double peak (the sum of the two pseudo Voigt functions), and perform fitting on spectrum S2 to obtain the fitting equation F3 and parameter p3. The two peak positions corresponding to p3 are distributed at 499.8704 and 523.5098. The two peak positions of the generated function are 500.0000 and 523.5482 respectively, which are relatively close to the fitting results; in particular, the error of the secondary peak has decreased from +0.5812 to -0.0384, which is only -6.6% of the error in the result of Step 7.

[0075] For further reference Figure 6, as an implementation of the methods shown in the above figures, the present invention provides an embodiment of an apparatus for identifying overlapping peaks in spectroscopic measurement data. This apparatus embodiment corresponds to Figure 2 the method embodiment shown, and this apparatus can be specifically applied to various electronic devices.

[0076] As shown in Figure 6 , the apparatus 600 for identifying overlapping peaks in spectroscopic measurement data in this embodiment may include: a target data acquisition module 601, a main peak identification result generation module 602, a half-side measurement result generation module 603, a first fitting module 604, a first fitting result generation module 605, a second peak data generation module 606, and a second fitting module 607. Among them, the target data acquisition module 601 is configured to acquire target spectroscopic measurement data; the main peak identification result generation module 602 is configured to perform peak detection on the target spectroscopic measurement data to obtain a main peak identification result; the half-side measurement result generation module 603 is configured to determine an independent variable range based on the target spectroscopic measurement data and a relative position, and generate a half-side measurement result including the main peak value; the first fitting module 604 is configured to use a custom function to fit the half-side measurement result to obtain a first fitting function, and the first fitting function includes the main peak position; the first fitting result generation module 605 is configured to substitute the global independent variable in the target spectroscopic measurement data into the first fitting function to obtain a first fitting result; the second peak data generation module 606 is configured to obtain second peak data based on the target spectroscopic measurement data and the first fitting result; the second fitting module 607 is configured to use a custom function to fit the second peak data to obtain a second fitting function, and the second fitting function includes the second peak position.

[0077] In this embodiment, in the apparatus 600 for identifying overlapping peaks in spectroscopic measurement data: the specific processing of the target data acquisition module 601, the main peak identification result generation module 602, the half-side measurement result generation module 603, the first fitting module 604, the first fitting result generation module 605, the second peak data generation module 606, and the second fitting module 607 and the technical effects brought by them can be respectively referred to Figure 2 the relevant descriptions of steps 201-207 in the corresponding embodiment, which will not be elaborated here.

[0078] This embodiment exists as an apparatus embodiment corresponding to the above method embodiment. The apparatus for identifying overlapping peaks in spectroscopic measurement data provided in this embodiment can analyze and process spectroscopic measurement data containing overlapping peaks, and accurately identify peaks such as the main peak and secondary peaks therein through a relatively small amount of data and computational amount, which can improve the usability of spectroscopic measurement data.

[0079] According to an embodiment of the present invention, the present invention further provides an apparatus for identifying overlapping peaks in spectroscopic measurement data. The apparatus for identifying overlapping peaks in spectroscopic measurement data 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 when the instructions are executed by the at least one processor, the at least one processor is enabled to implement the method for identifying overlapping peaks in spectroscopic measurement data described in any of the above embodiments.

[0080] According to an embodiment of the present invention, the present invention further provides a readable storage medium storing computer instructions for enabling a computer to implement the method for identifying overlapping peaks in spectroscopic measurement data described in any of the above embodiments when executed.

[0081] According to an embodiment of the present invention, the present invention further provides a computer program product, which can implement the method for identifying overlapping peaks in spectroscopic measurement data described in any of the above embodiments when executed by a processor.

[0082] Figure 7 FIG. shows a schematic block diagram of an exemplary apparatus 700 for identifying overlapping peaks in spectroscopic measurement data that can be used to implement embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0083] As Figure 7 shown, the apparatus 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the apparatus 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0084] Multiple components in device 700 are connected to I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disc, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0085] The computing unit 701 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 executes the various methods and processes described above, such as the method for identifying overlapping peaks in spectroscopic measurement data. For example, in some embodiments, the method for identifying overlapping peaks in spectroscopic measurement data can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the method for identifying overlapping peaks in spectroscopic measurement data described above can be executed. Alternatively, in other embodiments, the computing unit 701 can be configured to execute the method for identifying overlapping peaks in spectroscopic measurement data in any other suitable manner (e.g., by means of firmware).

[0086] An embodiment of the present invention also provides a thickness measurement method, which is executed by an electronic device such as a computer or a server, and specifically includes: obtaining the peak value of the main peak and the peak value of the secondary peak of the current frame by using the method for identifying overlapping peaks described in any of the above embodiments.

[0087] An embodiment of the present invention also provides a thinning control method, which is executed by an electronic device such as a computer or a server, and specifically includes: obtaining the wafer thickness of the current frame according to the thickness measurement method described in any of the above embodiments; stopping thinning the wafer when the wafer thickness of the current frame reaches a preset thickness. The preset thickness is a thickness value set for the thinning requirement.

[0088] In this embodiment, an accurate thickness measurement method is used to obtain the thickness of the wafer in the current frame, which can provide real-time and accurate thickness data for the thinning process. When the wafer thickness reaches the preset value, the thinning operation is automatically stopped, which can effectively avoid the problems of over-thinning or under-thinning, ensure that the final thickness of the wafer accurately meets the expected standard, and improve the quality and consistency of wafer thinning processing.

[0089] An embodiment of the present invention also provides a thinning machine for thinning a wafer according to the method described in any of the above embodiments during the thinning process.

[0090] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0091] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementing in the process Figure 1 a process or multiple processes and / or blocks Figure 1 a device for performing the functions specified in one block or multiple blocks.

[0092] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements in the process Figure 1 a process or multiple processes and / or blocks Figure 1 a device for performing the functions specified in one block or multiple blocks.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide for implementing in the process Figure 1 a process or multiple processes and / or blocks Figure 1Steps of functions specified in one or more boxes.

[0094] Obviously, the above embodiments are only examples given for clear illustration and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation manners here. And the obvious changes or modifications derived therefrom still fall within the protection scope of the present invention.

Claims

1. A method for identifying overlapping peaks in spectroscopic measurement data, characterized in that, Including: Obtain target spectroscopic measurement data; the target spectroscopic measurement data contains data of the overlapping peaks, and the overlapping peaks include a main peak and a second peak; Perform peak detection on the target spectroscopic measurement data to obtain a main peak identification result; Determine an independent variable range based on the target spectroscopic measurement data and the main peak identification result, and generate a half-side measurement result including the main peak peak value; Use a custom function to fit the half-side measurement result to obtain a first fitting function, and the first fitting function contains the main peak position; Substitute the global independent variable in the target spectroscopic measurement data into the first fitting function to obtain a first fitting result; Obtain second peak data based on the target spectroscopic measurement data and the first fitting result; Use the custom function to fit the second peak data to obtain a second fitting function, and the second fitting function contains the second peak position.

2. The method according to claim 1, characterized in that, The obtaining of the target spectroscopic measurement data includes: Obtain original spectroscopic measurement data; In response to the pre-existence of background spectroscopic measurement data, perform background removal processing on the original spectroscopic measurement data based on the background spectroscopic measurement data to obtain the target spectroscopic measurement data after background removal; In response to the non-pre-existence of background spectroscopic measurement data, use the original spectroscopic measurement data as the target spectroscopic measurement data.

3. The method according to claim 2, wherein The obtaining of the target spectroscopic measurement data further includes: Perform low-pass filtering processing on the target spectroscopic measurement data to obtain the target spectroscopic measurement data after noise reduction and smoothing.

4. The method according to claim 1, wherein The determining of the independent variable range based on the target spectroscopic measurement data and the main peak identification result, and generating a half-side measurement result including the main peak peak value includes: Determine the relative position of the second peak value and the main peak peak value based on the preset position relationship between the main peak and the second peak and the main peak identification result; Determine the independent variable range based on the target spectroscopic measurement data and the relative position, and generate a half-side measurement result including the main peak peak value.

5. The method according to claim 1, characterized in that, The determining of the independent variable range based on the target spectroscopic measurement data and the main peak identification result, and generating a half-side measurement result including the main peak peak value includes: Identify the relative position of the second peak value and the main peak peak value based on the main peak identification result; Determine the independent variable range based on the target spectroscopic measurement data and the relative position, and generate a half-side measurement result including the main peak peak value.

6. The method according to claim 5, wherein The identifying of the relative position of the second peak value and the main peak based on the main peak identification result includes: Use an integration window to identify the position of the second peak value; Determine the relative position based on the position of the second peak value and the main peak position in the main peak identification result.

7. The method according to claim 4, wherein The determining of the independent variable range based on the target spectroscopic measurement data and the relative position includes: Based on the target spectroscopic measurement data, determine the range between the independent variable limit value on the side opposite to the relative position and the independent variable value of the main peak peak value as the independent variable range.

8. The method according to claim 7, wherein The determining of the range between the independent variable limit value on the side opposite to the relative position and the independent variable value of the main peak peak value as the independent variable range includes: In response to the second peak being located between the main peak and the minimum value of the independent variable, determine that the range of the independent variable is from the independent variable value at the peak of the main peak to the maximum value of the independent variable; In response to the second peak being located between the main peak and the maximum value of the independent variable, determine that the range of the independent variable is from the minimum value of the independent variable to the independent variable value at the peak of the main peak.

9. The method according to claim 7, wherein Generate a half-measurement result including the peak value of the main peak, including: Construct the half-measurement result based on the data in the target spectroscopic measurement data that conforms to the range of the independent variable.

10. The method according to claim 1, characterized in that, The obtaining the second peak data based on the target spectroscopic measurement data and the first fitting result includes: Subtract the first fitting result from the target spectroscopic measurement data to obtain the second peak data.

11. The method according to any one of claims 1 to 10, characterized in that, Further includes: Substitute the global variable in the target spectroscopic measurement data into the sum function of the first fitting function and the second fitting function to obtain a third fitting result, and the third fitting result includes the position of the main peak and the position of the second peak.

12. A thickness measurement method, characterized in that, Includes: Obtain the peak value of the main peak and the peak value of the secondary peak of the current frame by using the method according to any one of claims 1-11; Calculate the wafer thickness of the current frame according to the peak value of the main peak and the peak value of the second peak.

13. A thinning control method, characterized in that, Includes: Obtain the wafer thickness of the current frame by using the method according to claim 12; When the wafer thickness of the current frame reaches a preset thickness, stop thinning the wafer.

14. An identification device for overlapping peaks in spectroscopic measurement data, characterized in that, Includes: 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 execute the method for identifying overlapping peaks in spectroscopic measurement data according to any one of claims 1-11.

15. A thickness measuring device, characterized in that, Includes: 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 execute the thickness measurement method according to claim 12.

16. A thinning control device, characterized in that, Includes: 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 execute the thinning control method according to claim 13.

17. A thinning machine, characterized in that, For thinning a wafer and executing the method according to any one of claims 1-13 during the thinning process.

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