CN117037935B - Material composition determination method, device, equipment and storage medium - Google Patents

Material composition determination method, device, equipment and storage medium Download PDF

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CN117037935B
CN117037935B CN202311038528.3A CN202311038528A CN117037935B CN 117037935 B CN117037935 B CN 117037935B CN 202311038528 A CN202311038528 A CN 202311038528A CN 117037935 B CN117037935 B CN 117037935B
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CN117037935A (en
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胡朋举
肖军
崔亚超
肖红丽
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Hebei Duncheng New Energy Technology Co ltd
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Abstract

The application is applicable to the technical field of analysis materials, and provides a method, a device, equipment and a storage medium for determining material components, wherein the method comprises the following steps: acquiring a standard Raman spectrum, a mixed Raman spectrum and a Raman spectrum of a material to be detected, wherein the standard Raman spectrum is obtained based on a single-component standard specification material, and the mixed Raman spectrum is obtained based on a preset-ratio multi-component standard specification material; based on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured, the relative Raman signal intensity among all components in the material to be measured is calculated through least square fitting; and obtaining the components of the material to be measured and the component ratio of the material to be measured based on the standard Raman spectrum, the Raman spectrum of the material to be measured and the relative Raman signal intensity among the components in the material to be measured. The method and the device can be used for rapidly analyzing the components and the component ratio of the material to be measured.

Description

Material composition determination method, device, equipment and storage medium
Technical Field
The application belongs to the technical field of analytical materials, and particularly relates to a method, a device, equipment and a storage medium for determining material components.
Background
Along with the continuous development of economy, the industry of degradable plastics enters a quick expansion stage of productivity, but some enterprises blend fully degradable materials and non-degradable materials for reducing cost or improving product performance, so that the products disintegrate to form micro plastics, the damage is larger, the traditional detection method is GB/T19277.1-2011, the method takes the materials as organic compounds under the controlled composting condition, the final aerobic biological decomposition capacity and the disintegration degree of the materials are determined by measuring the carbon dioxide amount discharged by the materials, and whether the materials to be detected are the components of the degradable plastics and the materials to be detected is judged. The detection period of the method is generally 3-6 months, the detection equipment is self-developed for each detection mechanism, the deviation between the same batch of experiments is less than 20%, the reliable data are determined, the data accuracy is poor, the detection data of different detection mechanisms are incomparable, and a rapid and accurate method for detecting and determining the material components is needed to be established.
Disclosure of Invention
In order to solve the technical problems of long time period and poor data accuracy of the traditional detection method in the related technology, the embodiment of the application provides a method, a device, equipment and a storage medium for determining material components.
The application is realized by the following technical scheme:
in a first aspect, embodiments of the present application provide a method for determining a material composition, including:
and acquiring a standard Raman spectrum, a mixed Raman spectrum and a Raman spectrum of the material to be detected, wherein the standard Raman spectrum is obtained based on a single-component standard specification material, and the mixed Raman spectrum is obtained based on a preset-ratio multi-component standard specification material.
Based on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured, the relative Raman signal intensity among all components in the material to be measured is obtained through least square fitting calculation.
And obtaining the components of the material to be measured and the component ratio of the material to be measured based on the standard Raman spectrum, the Raman spectrum of the material to be measured and the relative Raman signal intensity among the components in the material to be measured.
With reference to the first aspect, in some possible implementations, based on the standard raman spectrum, the mixed raman spectrum, and the raman spectrum of the material to be measured, the calculating by least square fitting the relative raman signal intensities between the components in the material to be measured includes: and carrying out normalization treatment on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured. Based on the normalized mixed Raman spectrum, the preset proportion and the normalized standard Raman spectrum, the relative Raman signal intensity among all components in the mixed Raman spectrum is obtained. And obtaining a first simulated hybrid Raman spectrum based on the normalized standard Raman spectrum, the simulated proportion and the relative Raman signal intensity among the components in the hybrid Raman spectrum. And fitting the first simulated hybrid Raman spectrum and the Raman spectrum of the material to be measured after normalization processing based on a least square method to obtain the relative Raman signal intensity among all components in the material to be measured.
With reference to the first aspect, in some possible implementations, a calculation formula of the normalization process is:
wherein,for wave number on X-axis, +.>，/>For wave number->Number of (A)>For normalizing the signal intensity of the processed spectrum, +.>For normalizing the signal intensity of the pre-processed spectrum, +.>The signal intensity of the spectrum before normalization is the average value of the signal intensity, wherein the spectrum after normalization in the formula is the standard Raman spectrum after normalization, the mixed Raman spectrum after normalization or the Raman spectrum of the material to be measured after normalization, and the spectrum before normalization in the formula is the standard Raman spectrum, the mixed Raman spectrum or the Raman spectrum of the material to be measured.
With reference to the first aspect, in some possible implementations, a calculation formula of the first analog hybrid raman spectrum is:
wherein,for wave number on X-axis, +.>，/>For wave number->Number of (A)>Wave number +.>The signal intensity at the point, the first simulated hybrid Raman spectrum is a hybrid spectrum of a single component A standard specification material and a single component B standard specification material mixed according to a simulated ratio, < >>Standard Raman spectra for Single component A at wavenumber +.>Signal intensity at>Standard Raman spectra for Single component A at wavenumber +.>Mean value of signal intensity at>Standard Raman spectra for Single component B at wavenumber +.>Signal intensity at>Standard Raman spectra for Single component B at wavenumber +.>Mean value of signal intensity at>The percentage of component B is obtained by means of a simulated proportion,/->Is the raman signal intensity of component B versus component a in the first simulated hybrid raman spectrum.
With reference to the first aspect, in some possible implementations, obtaining the component of the material to be measured and the component ratio of the material to be measured based on the standard raman spectrum, the raman spectrum of the material to be measured, and the relative raman signal intensities between the components in the material to be measured includes: and obtaining the components of the material to be measured based on the standard Raman spectrum and the Raman spectrum of the material to be measured. Enumerating the concentration of each component in the material to be measured, and obtaining a second simulated hybrid raman spectrum based on the concentration of each component and the relative raman signal intensity between each component in the material to be measured. And obtaining the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum based on the second simulated hybrid Raman spectrum. And performing partial least square method calculation on the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum and the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization processing to obtain the component duty ratio of the material to be measured.
With reference to the first aspect, in some possible implementations, the method further includes: and obtaining the mass fraction of each component of the material to be tested based on the component proportion of the material to be tested.
The calculation formula of the mass fraction of each component of the material to be measured is as follows:
wherein,is the component->Mass fraction of->Is the component->Component ratio of->Representing the composition of the material to be tested>Is the sum of the duty ratios of the components.
With reference to the first aspect, in some possible implementations, a method for determining a material composition, a standard specification material, includes: polypropylene, polyethylene, polyvinyl chloride, polystyrene, ethylene-vinyl acetate copolymer, polylactic acid, polybutylene terephthalate-adipate, polybutylene succinate, starch, calcium carbonate, or talc.
In a second aspect, embodiments of the present application provide a material composition determination apparatus, comprising:
the acquisition module is used for acquiring a standard Raman spectrum, a mixed Raman spectrum and a Raman spectrum of a material to be detected, wherein the standard Raman spectrum is obtained based on a single-component standard specification material, and the mixed Raman spectrum is obtained based on a preset-ratio multi-component standard specification material.
The calculation module is used for calculating the relative Raman signal intensity among all components in the material to be measured through least square fitting based on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured.
The result module is used for obtaining the components of the material to be measured and the component ratio of the material to be measured based on the standard Raman spectrum, the Raman spectrum of the material to be measured and the relative Raman signal intensity among the components in the material to be measured.
In a third aspect, an embodiment of the present application provides a terminal device, including: a processor and a memory for storing a computer program which when executed by the processor implements the material composition determination method according to any one of the first aspects.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a material composition determination method as in any one of the first aspects.
It will be appreciated that the advantages of the second to fourth aspects may be found in the relevant description of the first aspect and are not repeated here.
Compared with the prior art, the embodiment of the application has the beneficial effects that:
according to the method, the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured are subjected to fitting calculation through the least square method to obtain the relative Raman signal intensity among all components in the material to be measured, and then the component proportion of the material to be measured is accurately and rapidly obtained according to the standard Raman spectrum, the relative Raman signal intensity among all components in the material to be measured and the Raman spectrum of the material to be measured, so that the problem of poor accuracy of a traditional method is avoided, the detection period is saved, and the components and the component proportion of the material to be measured can be rapidly and accurately obtained.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for determining a material composition according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a material composition determining apparatus according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
An embodiment of the present application proposes a method for determining a material component, and fig. 1 is a schematic flow chart of the method for determining a material component according to an embodiment of the present application, and referring to fig. 1, the method for determining a material component is described in detail as follows:
and 101, acquiring a standard Raman spectrum, a mixed Raman spectrum and a Raman spectrum of a material to be detected, wherein the standard Raman spectrum is obtained based on a single-component standard specification material, and the mixed Raman spectrum is obtained based on a preset-ratio multi-component standard specification material.
The raman spectrum of the material can be collected by a raman spectrometer (ATR method), among other methods.
Here, the standard specification material of a single component refers to a material of a single standard specification substance. The multicomponent standard specification material refers to a material in which a plurality of standard specification substances are mixed according to a preset ratio
Exemplary, standard specification materials may include: polypropylene (PP), polyethylene (PE), polyvinyl chloride (PVC), polystyrene (PS), ethylene-vinyl acetate copolymer (EVA), polylactic acid (PLA), polybutylene terephthalate-adipate (PBAT), polybutylene succinate (PBS), starch, calcium carbonate or talc. The standard specification material may also be a mixture of the above materials in a predetermined proportion of some of the materials.
And 102, based on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured, calculating the relative Raman signal intensity among all components in the material to be measured through least square fitting.
The method for obtaining the relative raman signal intensity between the components in the material to be measured by least square fitting calculation based on the standard raman spectrum, the mixed raman spectrum and the raman spectrum of the material to be measured specifically comprises the following steps: and carrying out normalization treatment on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured. Based on the normalized mixed Raman spectrum, the preset proportion and the normalized standard Raman spectrum, the relative Raman signal intensity among all components in the mixed Raman spectrum is obtained. And obtaining a first simulated hybrid Raman spectrum based on the normalized standard Raman spectrum, the simulated proportion and the relative Raman signal intensity among the components in the hybrid Raman spectrum. And fitting the first simulated hybrid Raman spectrum and the Raman spectrum of the material to be measured after normalization processing based on a least square method to obtain the relative Raman signal intensity among all components in the material to be measured.
In this embodiment, the first analog hybrid raman spectrum is also subjected to the same normalization process. The Raman spectrum after normalization processing leads each Raman spectrum to be consistent, and a uniform relative Raman signal intensity ratio exists between the Raman spectrum of the material to be measured after normalization processing and the first analog mixed Raman spectrum. The first simulated hybrid raman spectrum exhibits a computable proportional relationship to the hybrid raman spectrum. Therefore, after fitting is completed, the relative raman signal intensity among the components in the material to be measured can be replaced by the relative raman signal intensity in the first simulated hybrid raman spectrum, so that the relative raman signal intensity among the components in the material to be measured is obtained.
The calculation formula of the normalization process is as follows:
wherein,for wave number on X-axis, +.>，/>For wave number->Number of (A)>For the normalized spectrum at wave number +.>Signal intensity at>The spectrum before normalization is at wave number +.>Signal intensity at>The spectrum before normalization is at wave number +.>The mean value of the signal intensity, wherein the spectrum after normalization in the formula is a standard Raman spectrum after normalization, a mixed Raman spectrum after normalization or a Raman spectrum of a material to be measured after normalization, and the spectrum before normalization in the formula is a standard Raman spectrumSpectrum, hybrid raman spectrum, or raman spectrum of the material to be measured. In this embodiment, the signal intensity of the raman spectrum is taken as the Y axis, and the wave number is taken as the X axis to establish a coordinate system.
Here, when the spectrum after normalization processing in the formula is a standard raman spectrum after normalization processing, the spectrum before normalization processing in the formula is a standard raman spectrum. Similarly, when the spectrum after normalization in the formula is a mixed raman spectrum after normalization, the spectrum before normalization in the formula is a mixed raman spectrum. When the spectrum after normalization processing in the formula is the Raman spectrum of the material to be measured after normalization processing, the spectrum before normalization processing in the formula is the Raman spectrum of the material to be measured.
Optionally, the denominator of the normalization processing formula in the scheme is the denominator of the traditional vector normalization formula, and the numerator of the normalization processing formula in the scheme is the numerator of the traditional area normalization formula. Compared with vector normalization, the normalization processing of the scheme keeps the relative signal intensity of the Raman spectrum consistent with the original signal intensity, and negative values cannot occur in a large range. The normalization process of this scheme is fixed for the baseline shifted raman spectrum compared to the area normalization. The enumeration range calculated by the enumeration method is effectively limited, and the operation amount is greatly saved.
Illustratively, the first simulated hybrid raman spectrum is calculated as:
wherein,for wave number on X-axis, +.>，/>For wave number->Number of (A)>Wave number +.>The signal intensity at the point, the first simulated hybrid Raman spectrum is a hybrid spectrum of a single component A standard specification material and a single component B standard specification material mixed according to a simulated ratio, < >>Standard Raman spectra for Single component A at wavenumber +.>Signal intensity at>Standard Raman spectra for Single component A at wavenumber +.>Mean value of signal intensity at>Standard Raman spectra for Single component B at wavenumber +.>Signal intensity at>Standard Raman spectra for Single component B at wavenumber +.>Mean value of signal intensity at>The percentage of component B is obtained by means of a simulated proportion,/->Is the raman signal intensity of component B versus component a in the first simulated hybrid raman spectrum. Component a and component B are any two components of the first simulated hybrid raman spectrum described above.
And step 103, obtaining the components of the material to be measured and the component ratio of the material to be measured based on the standard Raman spectrum, the Raman spectrum of the material to be measured and the relative Raman signal intensity among the components in the material to be measured.
The method for obtaining the component of the material to be measured and the component ratio of the material to be measured based on the standard raman spectrum, the raman spectrum of the material to be measured and the relative raman signal intensity among the components in the material to be measured comprises the following steps: and obtaining the components of the material to be measured based on the standard Raman spectrum and the Raman spectrum of the material to be measured. Enumerating the concentration of each component in the material to be measured, and obtaining a second simulated hybrid raman spectrum based on the concentration of each component and the relative raman signal intensity between each component in the material to be measured. And obtaining the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum based on the second simulated hybrid Raman spectrum. And performing partial least square calculation on the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum and the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization processing to obtain the component duty ratio of the material to be measured.
Here, for the raman spectrum signal intensity of the second analog hybrid raman spectrum and the raman spectrum signal intensity of the raman spectrum of the material to be measured after normalization processing, a plurality of observation is required, that is, a plurality of corresponding comparison points are set, a plurality of partial least square method calculations are performed, and by combining with the setting of a polynomial inequality, the interference of unknown interference components on the quantitative result is avoided as much as possible, wherein the polynomial inequality is as follows:. The left side of the inequality is the Raman spectrum signal intensity of the second analog hybrid Raman spectrum, and the right side of the inequality is the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization processing.
In this embodiment, after knowing the composition of the material to be tested, by establishing a secondAnd simulating the mixed Raman spectrum to obtain the Raman spectrum signal intensity of the second simulated mixed Raman spectrum, and when the Raman spectrum signal intensity of the second simulated mixed Raman spectrum is higher than the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization treatment, determining that the concentration of a certain component exceeds the upper limit. Repeatedly enumerating the concentrations of multiple groups of components, fitting by a partial least squares method, and when the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum is approximately equal to the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization processing (when the internal verification mean error square Root (RMSECV) of the two spectrums is minimum, the specific formula of the expression of the corresponding relation between the error square root and the concentrations of the components is expressed as) The concentration of each component at this time can be determined as the component concentration of the material to be measured, and the component concentration of the material to be measured can be converted into the component ratio of the material to be measured.
The mass fraction of each component of the material to be measured can also be obtained based on the component ratio of the material to be measured.
The calculation formula of the mass fraction of each component of the material to be measured is as follows:
wherein,is the component->Mass fraction of->Is the component->Component ratio of->Representing the composition of the material to be tested>Is the sum of the duty ratios of the components.
In the embodiment, the standard raman spectrum, the mixed raman spectrum and the raman spectrum of the material to be measured are subjected to fitting calculation by a least square method to obtain the relative raman signal intensity among all the components in the material to be measured, so that the component proportion of the material to be measured is accurately and rapidly obtained according to the standard raman spectrum, the relative raman signal intensity among all the components in the material to be measured and the raman spectrum of the material to be measured, the problem of poor accuracy of the traditional method is avoided, the detection period is also saved, and the component proportion of the material to be measured can be rapidly and accurately obtained.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.
Corresponding to the material composition determining method described in the above embodiments, fig. 2 shows a block diagram of the material composition determining apparatus provided in the embodiment of the present application, and for convenience of explanation, only the portions relevant to the embodiment of the present application are shown.
Referring to fig. 2, a material composition determining apparatus in an embodiment of the present application may include an acquisition module 201, a calculation module 202, and a result module 203.
The acquisition module 201 is configured to acquire a standard raman spectrum, a mixed raman spectrum, and a raman spectrum of a material to be measured, where the standard raman spectrum is obtained based on a single component of a material of standard specification, and the mixed raman spectrum is obtained based on a preset proportion of a material of standard specification of multiple components.
The calculation module 202 is configured to calculate, by least square fitting, relative raman signal intensities between components in the material to be measured based on the standard raman spectrum, the mixed raman spectrum, and the raman spectrum of the material to be measured.
The result module 203 is configured to obtain a component of the material to be measured and a component ratio of the material to be measured based on the standard raman spectrum, the raman spectrum of the material to be measured, and the relative raman signal intensity between components in the material to be measured.
Exemplary, standard gauge materials, including: polypropylene (PP), polyethylene (PE), polyvinyl chloride (PVC), polystyrene (PS), ethylene-vinyl acetate copolymer (EVA), polylactic acid (PLA), polybutylene terephthalate-adipate (PBAT), polybutylene succinate (PBS), starch, calcium carbonate or talc.
Illustratively, the computing module 202 is specifically configured to: and carrying out normalization treatment on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured. Based on the normalized mixed Raman spectrum, the preset proportion and the normalized standard Raman spectrum, the relative Raman signal intensity among all components in the mixed Raman spectrum is obtained. And obtaining a first simulated hybrid Raman spectrum based on the normalized standard Raman spectrum, the simulated proportion and the relative Raman signal intensity among the components in the hybrid Raman spectrum. And fitting the first simulated hybrid Raman spectrum and the Raman spectrum of the material to be measured after normalization processing based on a least square method to obtain the relative Raman signal intensity among all components in the material to be measured.
The calculation formula of the normalization process is as follows:
wherein,for wave number on X-axis, +.>，/>For wave number->Number of (A)>For the normalized spectrum at wave number +.>Signal intensity at>The spectrum before normalization is at wave number +.>Signal intensity at>The spectrum before normalization is at wave number +.>The average value of the signal intensity is obtained, wherein the spectrum after normalization processing in the formula is a standard Raman spectrum after normalization processing, a mixed Raman spectrum after normalization processing or a Raman spectrum of a material to be measured after normalization processing, and the spectrum before normalization processing in the formula is a standard Raman spectrum, a mixed Raman spectrum or a Raman spectrum of the material to be measured.
Illustratively, the first simulated hybrid raman spectrum is calculated as:
wherein,for wave number on X-axis, +.>，/>For wave number->Number of (3)，/>Wave number +.>The signal intensity at the point, the first simulated hybrid Raman spectrum is a hybrid spectrum of a single component A standard specification material and a single component B standard specification material mixed according to a simulated ratio, < >>Standard Raman spectra for Single component A at wavenumber +.>Signal intensity at>Standard Raman spectra for Single component A at wavenumber +.>Mean value of signal intensity at>Standard Raman spectra for Single component B at wavenumber +.>Signal intensity at>Standard Raman spectra for Single component B at wavenumber +.>Mean value of signal intensity at>The percentage of component B is obtained by means of a simulated proportion,/->For a first simulated hybrid pullRaman signal intensity of component B versus component a in the raman spectrum.
Illustratively, the results module 203 is specifically configured to: and obtaining the components of the material to be measured based on the standard Raman spectrum and the Raman spectrum of the material to be measured. Enumerating the concentration of each component in the material to be measured, and obtaining a second simulated hybrid raman spectrum based on the concentration of each component and the relative raman signal intensity between each component in the material to be measured. And obtaining the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum based on the second simulated hybrid Raman spectrum. And performing partial least square calculation on the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum and the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization processing to obtain the component duty ratio of the material to be measured.
Illustratively, the results module 203 is specifically configured to: and obtaining the mass fraction of each component of the material to be tested based on the component proportion of the material to be tested.
The calculation formula of the mass fraction of each component of the material to be measured is as follows:
wherein,is the component->Mass fraction of->Is the component->Component ratio of->Representing the composition of the material to be tested>Is the sum of the duty ratios of the components.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
The embodiment of the present application further provides a terminal device, referring to fig. 3, the terminal device 300 may include: at least one processor 310, a memory 320, the memory 320 being configured to store a computer program 321, the processor 310 being configured to invoke and execute the computer program 321 stored in the memory 320 to perform the steps of any of the various method embodiments described above, such as steps 101 to 103 in the embodiment shown in fig. 1. Alternatively, the processor 310 may implement the functions of the modules/units in the above-described embodiments of the apparatus when executing the computer program, for example, the functions of the modules shown in fig. 2.
By way of example, the computer program 321 may be partitioned into one or more modules/units that are stored in the memory 320 and executed by the processor 310 to complete the present application. The one or more modules/units may be a series of computer program segments capable of performing specific functions for describing the execution of the computer program in the terminal device 300.
It will be appreciated by those skilled in the art that fig. 3 is merely an example of a terminal device and is not limiting of the terminal device and may include more or fewer components than shown, or may combine certain components, or different components, such as input-output devices, network access devices, buses, etc.
The processor 310 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 320 may be an internal storage unit of the terminal device, or may be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card), or the like. The memory 320 is used for storing the computer program and other programs and data required by the terminal device. The memory 320 may also be used to temporarily store data that has been output or is to be output.
The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or one type of bus.
The method for determining the material composition provided by the embodiment of the application can be applied to terminal equipment such as a computer, wearable equipment, vehicle-mounted equipment, a tablet personal computer, a notebook computer, a netbook and the like, and the embodiment of the application does not limit the specific type of the terminal equipment.
Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements steps in various embodiments of a material composition determination method as described above.
Embodiments of the present application provide a computer program product which, when run on a mobile terminal, causes the mobile terminal to perform steps that may be performed in the various embodiments of the material composition determination method described above.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims (8)

1. A method of determining a composition of a material, comprising:
the method comprises the steps of obtaining a standard Raman spectrum, a mixed Raman spectrum and a Raman spectrum of a material to be detected, wherein the standard Raman spectrum is obtained based on a single-component standard specification material, and the mixed Raman spectrum is obtained based on a preset-ratio multi-component standard specification material;
based on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured, calculating the relative Raman signal intensity among all components in the material to be measured through least square fitting;
obtaining the components of the material to be measured and the component ratio of the material to be measured based on the standard Raman spectrum, the Raman spectrum of the material to be measured and the relative Raman signal intensity among the components in the material to be measured;
the calculating the relative raman signal intensity among each component in the material to be measured by least square fitting based on the standard raman spectrum, the mixed raman spectrum and the raman spectrum of the material to be measured comprises the following steps:
normalizing the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured;
based on the normalized mixed Raman spectrum, the preset proportion and the normalized standard Raman spectrum, obtaining the relative Raman signal intensity among all components in the mixed Raman spectrum;
obtaining a first simulated hybrid raman spectrum based on the normalized standard raman spectrum, the simulated proportion and the relative raman signal intensity between components in the hybrid raman spectrum;
fitting the first simulated hybrid Raman spectrum and the Raman spectrum of the material to be measured after normalization processing based on a least square method to obtain the relative Raman signal intensity among all components in the material to be measured;
the calculation formula of the first simulation mixed Raman spectrum is as follows:
where i is the number of waves on the X-axis, i=1, 2,3 … n, n is the number of waves, E AB simulation, i For the signal intensity at wavenumber i of a first simulated hybrid Raman spectrum, which is a hybrid spectrum of a standard specification material of single component A and a standard specification material of single component B mixed according to the simulated proportion, E A，i The signal intensity at wavenumber i for the standard raman spectrum of single component a,is the mean value of the signal intensities at wavenumber i of the standard raman spectrum of single component a, E B，i Signal intensity at wavenumber i for standard raman spectrum of single component B, +.>Is the mean value of the signal intensity at wavenumber i for standard raman spectrum of single component B, C B The percentage of the component B is obtained by the simulation proportion, K B Is the raman signal intensity of component B versus component a in the first simulated hybrid raman spectrum.
2. The material composition determination method according to claim 1, wherein the calculation formula of the normalization process is:
where i is the number of waves on the X-axis, i=1, 2,3 … n, n is the number of waves, E Normalization, i To normalize the signal intensity of the processed spectrum at wavenumber i, E Original, i To normalize the signal intensity at wavenumber i for the pre-processed spectrum,the method comprises the steps of normalizing a signal intensity average value of a spectrum before normalization at a wave number i, wherein the spectrum after normalization in a formula is a standard Raman spectrum after normalization, a mixed Raman spectrum after normalization or a Raman spectrum of a material to be measured after normalization, and the spectrum before normalization in the formula is the standard Raman spectrum, the mixed Raman spectrum or the Raman spectrum of the material to be measured.
3. The material composition determining method according to claim 1, wherein the obtaining the component of the material to be measured and the component ratio of the material to be measured based on the standard raman spectrum, the raman spectrum of the material to be measured, and the relative raman signal intensities between the components in the material to be measured includes:
obtaining components of the material to be detected based on the standard Raman spectrum and the Raman spectrum of the material to be detected;
enumerating the concentration of each component in the material to be measured, and obtaining a second simulated hybrid raman spectrum based on the concentration of each component and the relative raman signal intensity between each component in the material to be measured;
obtaining Raman spectrum signal intensity of the second simulated hybrid Raman spectrum based on the second simulated hybrid Raman spectrum;
and performing partial least square method calculation on the Raman spectrum signal intensity of the second simulated hybrid Raman spectrum and the Raman spectrum signal intensity of the Raman spectrum of the material to be measured after normalization processing to obtain the component duty ratio of the material to be measured.
4. The material composition determination method of claim 1, wherein the method further comprises:
based on the component proportion of the material to be measured, obtaining the mass fraction of each component of the material to be measured;
the calculation formula of the mass fraction of each component of the material to be measured is as follows:
wherein C is i-fold hundred As mass fraction of component i, C i Is the component ratio of component i, i is { A, B, C, the term "refers to the composition of the material to be tested, SUM (C A ，C B ，C C ,.. For each group the sum of the fractions.
5. The material composition determination method of claim 1, wherein the standard specification of material comprises: polypropylene, polyethylene, polyvinyl chloride, polystyrene, ethylene-vinyl acetate copolymer, polylactic acid, polybutylene terephthalate-adipate, polybutylene succinate, starch, calcium carbonate, or talc.
6. A material composition determination apparatus, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a standard Raman spectrum, a mixed Raman spectrum and a Raman spectrum of a material to be detected, the standard Raman spectrum is obtained based on a single-component standard specification material, and the mixed Raman spectrum is obtained based on a preset-ratio multi-component standard specification material;
the calculation module is used for obtaining the relative Raman signal intensity among all components in the material to be measured through least square fitting calculation based on the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured;
the result module is used for obtaining the components of the material to be detected and the component ratio of the material to be detected based on the standard Raman spectrum, the Raman spectrum of the material to be detected and the relative Raman signal intensity among the components in the material to be detected;
the calculation module is further used for:
normalizing the standard Raman spectrum, the mixed Raman spectrum and the Raman spectrum of the material to be measured;
based on the normalized mixed Raman spectrum, the preset proportion and the normalized standard Raman spectrum, obtaining the relative Raman signal intensity among all components in the mixed Raman spectrum;
obtaining a first simulated hybrid raman spectrum based on the normalized standard raman spectrum, the simulated proportion and the relative raman signal intensity between components in the hybrid raman spectrum;
fitting the first simulated hybrid Raman spectrum and the Raman spectrum of the material to be measured after normalization processing based on a least square method to obtain the relative Raman signal intensity among all components in the material to be measured;
the calculation formula of the first simulation mixed Raman spectrum is as follows:
where i is the number of waves on the X-axis, i=1, 2,3 … n, n is the number of waves, E AB simulation, i For the signal intensity at wavenumber i of a first simulated hybrid Raman spectrum, which is a hybrid spectrum of a standard specification material of single component A and a standard specification material of single component B mixed according to the simulated proportion, E A，i The signal intensity at wavenumber i for the standard raman spectrum of single component a,is the mean value of the signal intensities at wavenumber i of the standard raman spectrum of single component a, E B，i Signal intensity at wavenumber i for standard raman spectrum of single component B, +.>Is the mean value of the signal intensity at wavenumber i for standard raman spectrum of single component B, C B The percentage of component BThe percentage content is obtained by the simulation proportion, K B Is the raman signal intensity of component B versus component a in the first simulated hybrid raman spectrum.
7. A terminal device, comprising: a processor and a memory, in which a computer program is stored which is executable on the processor, characterized in that the processor implements the material composition determination method according to any one of claims 1 to 5 when executing the computer program.
8. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the material composition determination method according to any one of claims 1 to 5.
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