Raman spectroscopy detection method, apparatus, device, and computer-readable storage medium

Abstract

This invention provides a Raman spectroscopy detection method, apparatus, device, and computer-readable storage medium. The method involves acquiring a first spectrum of a sample to be tested doped with a preset impurity and a second spectrum of the preset impurity. Based on the first spectrum and multiple second spectra with different proportions, a similarity curve between the proportion of the preset impurity in the sample to be tested and the similarity is obtained. A target proportion corresponding to the minimum similarity change rate is determined based on the relationship curve. The second spectrum with the target proportion is removed from the first spectrum to obtain the Raman spectrum of the sample to be tested. The Raman spectroscopy detection method according to this invention enables more accurate acquisition of the Raman spectrum of the sample to be tested.

Description

Technical Field

[0001] This invention belongs to the field of detection, and particularly relates to a Raman spectroscopy detection method, apparatus, device, and computer-readable storage medium. Background Technology

[0002] Raman spectroscopy is a type of molecular vibrational spectroscopy that reflects the fingerprint characteristics of molecules and can be used for the detection of substances. Raman spectroscopy detection detects and identifies substances by detecting the Raman spectrum generated by the Raman scattering effect of the analyte on excitation light. Raman spectroscopy detection methods have been widely applied in fields such as liquid security inspection, jewelry testing, explosives detection, drug detection, pharmaceutical testing, and pesticide residue detection.

[0003] In the process of using Raman spectroscopy for detection, the test item usually contains impurities, which means that the obtained spectrum includes the spectrum of the impurities.

[0004] Currently, in Raman spectroscopy detection, the proportion of impurity spectra in the Raman detection spectrum is usually determined based on experience or information entropy. Then, the spectrum of the impurity spectrum is subtracted from the obtained Raman detection spectrum to obtain the spectrum of the item to be detected. However, the proportion of impurity spectra determined by experience or information entropy is inaccurate, leading to inaccurate spectra of the item to be detected and consequently, inaccurate detection of the item. Summary of the Invention

[0005] This invention provides a Raman spectroscopy detection method, apparatus, device, and computer-readable storage medium, which can improve the accuracy of detection of the items to be tested.

[0006] In a first aspect, embodiments of the present invention provide a Raman spectroscopy detection method, the method comprising:

[0007] Obtain the first spectrum of the sample to be tested doped with a preset impurity and the second spectrum of the preset impurity;

[0008] Based on the first spectrum and multiple second spectra of different proportions, the relationship curve between the proportion of preset impurities in the sample to be detected and the similarity is obtained.

[0009] Determine the target proportion corresponding to the minimum similarity change rate based on the relationship curve;

[0010] The Raman spectrum of the sample to be tested is obtained by removing the target proportion of the second spectrum from the first spectrum.

[0011] In some implementations, a curve showing the relationship between the proportion of a preset impurity in the sample to be detected and its similarity is obtained based on a first spectrum and multiple second spectra at different proportions, specifically including:

[0012] Multiple third spectra are obtained by removing different proportions of the second spectrum from the first spectrum;

[0013] The similarity between each third spectrum and the second spectrum is calculated to obtain the relationship curve between the proportion of the preset impurities in the sample to be tested and the similarity.

[0014] In some implementations, calculating the similarity between each third spectrum and the second spectrum specifically includes:

[0015] The similarity between each third spectrum and the second spectrum is calculated using the cosine similarity formula.

[0016] In some implementations, determining the target proportion corresponding to the minimum similarity change rate specifically includes:

[0017] By taking the derivative of the relationship curve, we obtain the derivative curve of the relationship curve;

[0018] The proportion of the preset impurity corresponding to the lowest point of the derivative curve in the sample to be tested is determined as the target proportion.

[0019] In some embodiments, after obtaining the Raman spectrum of the sample to be tested, the method further includes:

[0020] The composition of the sample to be tested is determined based on the Raman spectrum of the sample.

[0021] Secondly, embodiments of the present invention provide a Raman spectroscopy detection device, the device comprising:

[0022] The acquisition module is used to acquire the first spectrum of the sample to be tested, which is doped with a preset impurity, and the second spectrum of the preset impurity.

[0023] The first determining module is used to obtain a curve showing the relationship between the proportion of a preset impurity in the sample to be detected and the similarity, based on the first spectrum and multiple second spectra of different proportions.

[0024] The second determining module is used to determine the target proportion corresponding to the minimum similarity change rate based on the relationship curve.

[0025] The removal module is used to remove the target proportion of the second spectrum from the first spectrum to obtain the Raman spectrum of the sample to be detected.

[0026] In some implementations, the first determining module includes:

[0027] The first determining unit is used to remove multiple second spectra of different proportions from the first spectrum to obtain multiple third spectra.

[0028] The second determining unit is used to calculate the similarity between each third spectrum and the second spectrum, and obtain the relationship curve between the proportion of preset impurities in the sample to be detected and the similarity.

[0029] In some implementations, the second determining unit includes:

[0030] The first defined subunit is used to calculate the similarity between each third spectrum and the second spectrum according to the cosine similarity formula.

[0031] In some implementations, the second determining module specifically includes:

[0032] The derivative unit is used to differentiate the relationship curve to obtain the derivative curve of the relationship curve;

[0033] The third determining unit is used to determine the proportion of the preset impurity corresponding to the lowest point of the derivative curve in the sample to be tested as the target proportion.

[0034] In some embodiments, the Raman spectroscopy detection device further includes:

[0035] The third determination module is used to determine the composition of the sample to be tested based on the Raman spectrum of the sample.

[0036] Thirdly, embodiments of this application provide a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the steps of the Raman spectroscopy detection method as described in any embodiment of the first aspect.

[0037] Fourthly, embodiments of this application provide a computer program product in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the steps of the Raman spectroscopy detection method as described in any embodiment of the first aspect.

[0038] The Raman spectroscopy detection method, apparatus, device, and computer-readable storage medium of this invention acquire a first spectrum of a sample to be tested doped with a preset impurity and a second spectrum of the preset impurity. Then, based on the first spectrum and second spectra at different proportions, a relationship curve between the proportion of the impurity in the sample to be tested and its similarity is obtained. The proportion corresponding to the smallest rate of change in the relationship curve is then determined as the target proportion. Finally, the second spectrum at the target proportion is removed from the first spectrum to obtain the spectrum of the sample to be tested without the impurity. Therefore, since the relationship curve between the proportion of the preset impurity in the sample to be tested and its similarity is determined based on the first spectrum and multiple second spectra at different proportions, and the target proportion of the preset impurity in the sample to be tested is determined based on the acquired curve, the target proportion determined based on the relationship curve is more accurate. Furthermore, the acquired Raman spectrum of the sample to be tested is more accurate. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a schematic flowchart of a Raman spectroscopy detection method provided in one embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of the structure of a Raman spectroscopy detection device provided in one embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0043] The features and exemplary embodiments of various aspects of the present invention will now be described in detail. To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely intended to explain the present invention and not to limit the present invention. For those skilled in the art, the present invention can be practiced without some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present invention by illustrating examples of the invention.

[0044] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0045] Raman spectroscopy is a type of molecular spectroscopy based on the Raman effect. The Raman effect refers to the phenomenon where, when a substance is irradiated with monochromatic excitation light, a series of Raman scattered lights with wavelengths greater than and less than the incident light wavelength are produced. These Raman scattered lights, with varying intensities at different wavelengths, constitute the Raman spectrum. The shift in wavelength of these scattered lights relative to the excitation light wavelength corresponds to the type of molecular functional groups in the substance, while the intensity reflects the number of these functional groups. Therefore, Raman spectroscopy can be used for qualitative and quantitative analysis of molecules. For example, in the qualitative identification of an unknown substance, its Raman spectrum can be collected and matched with the spectra of known substances in a database. The known substance with the highest matching degree can be used as the qualitative identification result.

[0046] Because the samples to be tested are sometimes contained in packaging, or even sealed within packaging, packaging interference is unavoidable during Raman spectroscopy detection. Even when the laser is focused on the sample inside the packaging, the unfocused laser light will still excite a Raman spectrum on the packaging and be received by the detector. This results in the Raman spectrum received by the detector containing both the spectrum of the analyte and the spectrum of the packaging. Furthermore, when the transmittance of the packaging is low and the spectrum of the sample to be tested is weak, the measured spectrum may show a stronger packaging spectrum. This leads to a significant difference between the acquired spectrum and the Raman spectrum of the sample itself, making it difficult to accurately identify many substances.

[0047] To address the problems of the prior art, embodiments of the present invention provide a Raman spectroscopy detection method, apparatus, device, and computer-readable storage medium.

[0048] The Raman spectroscopy detection method provided in the embodiments of the present invention will be introduced first below.

[0049] Figure 1 A schematic flowchart of a Raman spectroscopy detection method according to an embodiment of the present invention is shown. Figure 1 As shown, the method may include the following steps:

[0050] S110. Obtain the first spectrum of the sample to be tested doped with a preset impurity and the second spectrum of the preset impurity;

[0051] S120. Based on the first spectrum and multiple second spectra with different proportions, obtain the relationship curve between the proportion of preset impurities in the sample to be detected and the similarity.

[0052] S130. Determine the target proportion corresponding to the minimum similarity change rate based on the relationship curve;

[0053] S140. Remove the second spectrum with the target proportion from the first spectrum to obtain the Raman spectrum of the sample to be tested.

[0054] Therefore, by acquiring the first spectrum of a sample to be tested doped with a preset impurity and the second spectrum of the preset impurity, and then obtaining the relationship curve between the proportion of the impurity and its similarity in the sample to be tested based on the first spectrum and the second spectra at different proportions, the proportion corresponding to the smallest rate of change in the relationship curve is determined as the target proportion. Then, the second spectrum at the target proportion is removed from the first spectrum to obtain the spectrum of the sample to be tested without the impurity. Thus, because the relationship curve between the proportion of the preset impurity and its similarity in the sample to be tested is determined based on the first spectrum and multiple second spectra at different proportions, and the target proportion of the preset impurity in the sample to be tested is determined based on the obtained curve, the target proportion determined based on the relationship curve can be more accurate. Furthermore, this makes the obtained Raman spectrum of the sample to be tested more accurate.

[0055] In some embodiments, in S110, the first spectrum may include the spectrum obtained by detecting a sample containing impurities. The second spectrum may include the spectrum obtained by detecting preset impurities.

[0056] In some implementations, impurities may include the packaging of the item to be tested. When Raman spectroscopy is used to detect the sample, especially when the sample is a liquid, gas, or powdered solid, the sample needs to be placed in a packaging bag, bottle, box, or jar that can hold it.

[0057] In some embodiments, S110 may specifically include: irradiating a sample to be tested with a laser doped with a predetermined impurity, and then collecting the spectrum reflected by the sample using a spectral collection device. Then, the impurity is irradiated with a laser, and the spectrum reflected by the impurity is collected using a spectral collection device.

[0058] In some implementations, S120 may specifically include:

[0059] Multiple third spectra are obtained by removing different proportions of the second spectrum from the first spectrum;

[0060] The similarity between each third spectrum and the second spectrum is calculated to obtain the relationship curve between the proportion of the preset impurities in the sample to be tested and the similarity.

[0061] In some implementations, the third spectrum may include a preset Raman detection spectrum of a sample to be detected that does not contain impurities. Since the amount of impurities doped in the first spectrum is uncertain, the proportion of the second spectrum in the acquired first spectrum is also uncertain. Therefore, the proportion of the doped second spectrum can be set to multiple values, and then the second spectra of each of these multiple set values ​​can be subtracted to obtain multiple possible third spectra.

[0062] In some implementations, the Raman spectral signals of impurities tend to be uniformly distributed. Therefore, the process of subtracting the second spectrum corresponding to the impurity from the first spectrum doped with the preset impurity is the process of subtracting the uniformly distributed second spectrum. That is, the first spectrum of the test sample doped with the preset impurity is relatively flat, while ideally, the third spectrum of the test sample without impurities is relatively uneven.

[0063] In some implementations, the similarity between each third spectrum and the second spectrum is calculated to obtain a curve showing the relationship between the proportion of a preset impurity in the sample to be detected and the similarity. Specifically, this may include:

[0064] The similarity between each third spectrum and the second spectrum is calculated using the cosine similarity formula.

[0065] In some implementations, cosine similarity is the most common algorithm for measuring the similarity of Raman spectra. It is essentially the calculation of the cosine value of the two spectra in a high-dimensional space as the similarity between the two spectra. The closer the cosine value is to 1, the closer the angle between the two spectra is to 0 degrees. For example, when the angle between the two spectra coincides at 0 degrees, the similarity between the two spectra is 1.

[0066] In some implementations, in S130, the target ratio may include the optimal ratio of the second spectrum corresponding to the doped impurities in the acquired first spectrum.

[0067] In some implementations, S130 may specifically include:

[0068] By taking the derivative of the relationship curve, we obtain the derivative curve of the relationship curve;

[0069] The proportion of the preset impurity corresponding to the lowest point of the derivative curve in the sample to be tested is determined as the target proportion.

[0070] In some implementations, after obtaining the above-mentioned relationship curve, the maximum similarity value in the similarity curve corresponding to the relationship curve observed by the human eye is inaccurate. Therefore, by taking the derivative of the above-mentioned relationship curve, the minimum point in the derivative curve can be obtained. The minimum point in the derivative curve can represent the maximum similarity value in the similarity curve, which is the preset target proportion of impurities in the sample to be tested.

[0071] In some embodiments, after obtaining the target proportion of a preset impurity in the sample to be detected, the Raman spectroscopy detection device may further include:

[0072] The composition of the sample to be tested is determined based on the Raman spectrum of the sample.

[0073] In some implementations, after obtaining the target proportion of a preset impurity in the sample to be tested, the second spectrum of the target proportion can be removed from the first spectrum to obtain the optimal third spectrum representing the sample to be tested that does not contain impurities.

[0074] After obtaining the optimal third spectrum of the sample to be tested, which is free of impurities, the composition of the sample to be tested can be determined based on the third spectrum.

[0075] In some specific examples, there are multiple Raman peaks in the Raman spectrum. Different Raman peaks represent different molecular structures. Different molecular structures can be determined based on the different Raman peaks in the third spectrum, and then the composition of the substances contained in the sample to be detected can be determined.

[0076] It should be noted that the application scenarios described in the above-disclosed embodiments are for the purpose of more clearly illustrating the technical solutions of the present disclosure embodiments, and do not constitute a limitation on the technical solutions provided by the present disclosure embodiments. As those skilled in the art will know, with the emergence of new application scenarios, the technical solutions provided by the present disclosure embodiments are also applicable to similar technical problems.

[0077] Figure 2 A schematic diagram of an embodiment of the Raman spectroscopy detection device provided in this application is shown, as follows: Figure 2 As shown, the Raman spectroscopy detection device 200 may include:

[0078] Acquisition module 201 is used to acquire the first spectrum of the sample to be tested doped with a preset impurity and the second spectrum of the preset impurity;

[0079] The first determining module 202 is used to obtain a curve showing the relationship between the proportion of a preset impurity in the sample to be detected and the similarity, based on the first spectrum and multiple second spectra of different proportions.

[0080] The second determining module 203 is used to determine the target proportion corresponding to the minimum similarity change rate based on the relationship curve;

[0081] The removal module 204 is used to remove the second spectrum of the target proportion from the first spectrum to obtain the Raman spectrum of the sample to be detected.

[0082] Therefore, by acquiring the first spectrum of a sample to be tested doped with a preset impurity and the second spectrum of the preset impurity, and then obtaining the relationship curve between the proportion of the impurity and its similarity in the sample to be tested based on the first spectrum and the second spectra at different proportions, the proportion corresponding to the smallest rate of change in the relationship curve is determined as the target proportion. Then, the second spectrum at the target proportion is removed from the first spectrum to obtain the spectrum of the sample to be tested without the impurity. Thus, because the relationship curve between the proportion of the preset impurity and its similarity in the sample to be tested is determined based on the first spectrum and multiple second spectra at different proportions, and the target proportion of the preset impurity in the sample to be tested is determined based on the obtained curve, the target proportion determined based on the relationship curve can be more accurate. Furthermore, this makes the obtained Raman spectrum of the sample to be tested more accurate.

[0083] In some implementations, the first determining module 202 may include:

[0084] The first determining unit can be used to remove multiple second spectra of different proportions from the first spectrum to obtain multiple third spectra.

[0085] The second determining unit can be used to calculate the similarity between each third spectrum and the second spectrum, and obtain the relationship curve between the proportion of preset impurities in the sample to be detected and the similarity.

[0086] In some implementations, the second determining unit may include:

[0087] The first defined subunit can be used to calculate the similarity between each third spectrum and the second spectrum according to the cosine similarity formula.

[0088] In some implementations, the second determining module 203 may specifically include:

[0089] The derivative unit can be used to differentiate a relation curve to obtain its derivative curve.

[0090] The third determining unit can be used to determine the proportion of a preset impurity corresponding to the lowest point of the derivative curve in the sample to be tested as the target proportion.

[0091] In some embodiments, the Raman spectroscopy detection device may further include:

[0092] The third determination module can be used to determine the composition of the sample to be tested based on the Raman spectrum of the sample.

[0093] Figure 3 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention is shown.

[0094] The electronic device 300 may include a processor 301 and a memory 302 storing computer program instructions.

[0095] Specifically, the processor 301 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of the present invention.

[0096] Memory 302 may include mass storage for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 302 may include removable or non-removable (or fixed) media, or memory 302 may be non-volatile solid-state memory. Memory 302 may be internal or external to the integrated gateway disaster recovery device.

[0097] In one instance, memory 302 may be read-only memory (ROM). In one instance, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0098] Memory 302 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0099] The processor 301 reads and executes computer program instructions stored in the memory 302 to achieve... Figure 3 The method / steps S110 to S140 in the illustrated embodiment are completed, and the desired outcome is achieved. Figure 1 The technical effects achieved by executing the methods / steps shown in the examples are not elaborated here for the sake of brevity.

[0100] In one example, the electronic device may also include a communication interface 303 and a bus 310. For example, Figure 3 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 310 and complete communication with each other.

[0101] The communication interface 303 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of the present invention.

[0102] Bus 310 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 310 may include one or more buses. Although specific buses are described and illustrated in embodiments of the invention, the invention contemplates any suitable bus or interconnect.

[0103] This electronic device can be based on the Raman spectroscopy detection method in the embodiments of the present invention, thereby achieving a combination of Figure 1 and Figure 2 The Raman spectroscopy detection method and apparatus are described.

[0104] Furthermore, in conjunction with the Raman spectroscopy detection methods in the above embodiments, this invention can be implemented using a computer-readable storage medium. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the Raman spectroscopy detection billing methods in the above embodiments.

[0105] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0106] The functional blocks shown in the above structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the required tasks. The programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0107] It should also be noted that the exemplary embodiments mentioned in this invention describe methods or systems based on a series of steps or apparatus. However, this invention is not limited to the order of the steps described above; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0108] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0109] The above are merely specific embodiments of the present invention. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the protection scope of the present invention.

Claims

1. A Raman spectroscopic detection method, characterized by, The method includes: Obtain the first spectrum of the sample to be tested doped with a preset impurity and the second spectrum of the preset impurity; Multiple third spectra are obtained by removing different proportions of the second spectrum from the first spectrum; The similarity between each third spectrum and the second spectrum is calculated to obtain the relationship curve between the proportion of the preset impurity in the sample to be detected and the similarity. Differentiating the relationship curve yields the derivative curve of the relationship curve; The proportion of the preset impurity corresponding to the lowest point of the derivative curve in the sample to be tested is determined as the target proportion. The Raman spectrum of the sample to be tested is obtained by removing the second spectrum of the target proportion from the first spectrum.

2. The method of claim 1, wherein, The calculation of the similarity between each third spectrum and the second spectrum specifically includes: The similarity between each third spectrum and the second spectrum is calculated using the cosine similarity formula.

3. The method of claim 1, wherein, After obtaining the Raman spectrum of the sample to be tested, the method further includes: The composition of the sample to be tested is determined based on the Raman spectrum of the sample.

4. A Raman spectroscopic detection device, characterized by The device includes: The acquisition module is used to acquire the first spectrum of the sample to be tested, which is doped with a preset impurity, and the second spectrum of the preset impurity; The first determining unit is used to remove multiple second spectra of different proportions from the first spectrum to obtain multiple third spectra. The second determining unit is used to calculate the similarity between each third spectrum and the second spectrum, and obtain the relationship curve between the proportion of the preset impurity in the sample to be detected and the similarity. A differentiation unit is used to differentiate the relationship curve to obtain the derivative curve of the relationship curve; The third determining unit is used to determine the proportion of the preset impurity corresponding to the lowest point of the derivative curve in the sample to be tested as the target proportion. The removal module is used to remove the target proportion of the second spectrum from the first spectrum to obtain the Raman spectrum of the sample to be detected.

5. An electronic device, comprising: The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the Raman spectroscopy detection method as described in any one of claims 1-3.

6. A computer readable storage medium characterized by The computer-readable storage medium stores computer program instructions, which are executed by a processor to implement the Raman spectroscopy detection method as described in any one of claims 1-3.

7. A computer program product, characterised in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the Raman spectroscopy detection method as described in any one of claims 1-3.

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