A three-dimensional image assisted xrf spectral analysis of abrasive grain particle size effect correction method

Abstract

The application discloses a three-dimensional image auxiliary XRF spectrum analysis abrasive particle granularity effect correction method, S1. Establishing an abrasive particle granularity effect correction model: S2. Utilizing an abrasive particle granularity effect correction device to simultaneously acquire abrasive three-dimensional images and XRF spectrum data in an irradiation area; S3. Processing the abrasive three-dimensional images through a computer to obtain abrasive morphology parameters in the irradiation area; S4. Processing the XRF spectrum data through the computer to obtain actual characteristic X-ray fluorescence intensities Ii' of elements to be analyzed in the abrasive; S5. Substituting the abrasive morphology parameters into the abrasive particle granularity effect correction model to obtain theoretical characteristic X-ray fluorescence intensities Ii of the elements to be analyzed; S4. Calculating the content Ci of the elements to be analyzed according to a Sherman equation to obtain the content of the elements to be analyzed in the abrasive, and abrasive particle granularity effect correction is realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of spectral analysis, and particularly relates to a three-dimensional image assisted XRF spectral analysis abrasive particle granularity effect correction method. BACKGROUND

[0002] Element detection of abrasive particles carried in oil is an important means of oil condition monitoring, and the oil condition monitoring is an effective way to obtain the wear condition of key equipment, so the oil abrasive particle element detection has important practical significance. The XRF spectral technology is an important method for oil abrasive particle element detection, and has the advantages of not being affected by particle size and not requiring sample processing. However, in the aspect of particle detection, the XRF technology has been affected by the granularity effect for a long time, and the sample must meet certain uniformity, particle size, flatness and thickness requirements. However, due to the influence of wear condition and fluid motion, the oil abrasive particles have great differences in particle size / shape and uneven distribution, especially for large size oil abrasive particles (particle size greater than 100 mu m), the detection result will have great uncertainty, resulting in great difference of XRF spectral analysis result and poor detection repeatability.

[0003] Most of the existing particle size effect correction methods need complex and time-consuming sample processing or manual selection of sample size, which loses the advantages of convenient and fast XRF detection and does not meet the actual needs of oil abrasive particle element detection. Therefore, there is an urgent need for a kind of abrasive particle granularity effect correction method for on-site rapid measurement to improve the detection precision of abrasive particle element content. SUMMARY

[0004] The purpose of the present application is to overcome the deficiencies in the prior art, provide a three-dimensional image assisted XRF spectral analysis abrasive particle granularity effect correction method and device, synchronously collect three-dimensional microscopic images of oil abrasive particles, adopt the basic parameter method, analyze the influence of oil abrasive particle morphological parameters on fluorescence spectrum, and construct a fluorescence intensity correction model based on abrasive particle morphological parameters. The problems of poor repeatability and low correction accuracy caused by the granularity effect of large size abrasive particles in the existing traditional XRF oil element detection method are solved, and a high-precision and low-power XRF oil element detection device is provided, which can be popularized for on-site detection of oil elements of various equipment systems including aircraft engines, gas turbines and the like.

[0005] The purpose of the present application is realized by the following technical scheme:

[0006] A three-dimensional image assisted XRF spectral analysis abrasive particle granularity effect correction device, comprising a sample stage, a confocal microscope, a light beam scanning displacement stage, a spectrometer, a scanning displacement stage controller, a computer, an X-ray source, an SDD detector and a multi-channel analyzer.

[0007] The objective table is horizontally placed, the confocal microscope is fixed and arranged above the objective table through a light beam scanning displacement table, and the X-ray source and the SDD detector are arranged on the two sides above the objective table respectively; the light beam scanning displacement table is connected with a scanning displacement table controller and a computer in sequence, and the confocal microscope is connected with a spectrometer and the computer in sequence; and the computer is connected with a multichannel analyzer and the SDD detector in sequence.

[0008] The confocal microscope comprises a white light point light source, a dispersion lens, and a beam splitter.

[0009] The displacement scanning range of the confocal microscope is controlled by the computer, so that the morphology detection area is coincided with the irradiation area of the X-ray on the objective table, the XRF spectrum and the microscopic image data are collected through time sequence control, and the detection of the elements and the morphology of the abrasive grains in the same area is realized.

[0010] The application further provides a three-dimensional image assisted XRF spectrum analysis abrasive grain granularity effect correction method, comprising the following steps:

[0011] S1. establishing an abrasive grain granularity effect correction model:

[0012] S101. according to the Sherman equation, a relationship expression between the fluorescence intensity of the abrasive grain and the element content is constructed;

[0013] S102. an X-ray fluorescence theory model after introducing the morphology parameters of the abrasive grain is established;

[0014] S103. the total mass m of the abrasive grain in the irradiation area is calculated sum ;

[0015] S104. based on the positive correlation between the total mass of the abrasive grain in the irradiation area and the theoretical fluorescence intensity of the irradiation area, the representation of the morphology parameters of the abrasive grain in the irradiation area on the fluorescence intensity is obtained by using a multivariate linear regression method;

[0016] S105. by using the abrasive grain samples with the same element and different morphologies, a data set is established through several experiments, the regression coefficient estimation is realized based on the least square method or the maximum likelihood estimation, the quantitative influence relationship of the morphology parameters on the fluorescence intensity is obtained, the fluorescence intensity is corrected by substituting into the X-ray fluorescence theory model;

[0017] S2. the abrasive grain three-dimensional image and the XRF spectrum data in the irradiation area are simultaneously obtained by using the abrasive grain granularity effect correction device;

[0018] S3. the abrasive grain morphology parameters in the irradiation area are obtained by processing the abrasive grain three-dimensional image by the computer;

[0019] S4. the actual characteristic X-ray fluorescence intensity I of the element to be analyzed in the abrasive grain is obtained by processing the XRF spectrum data by the computer; i ';

[0020] S5. Substitute the abrasive grain morphology parameters into the abrasive grain granularity effect correction model to obtain the theoretical characteristic X-ray fluorescence intensity I of the element to be analyzed i ;

[0021] S4. Calculate the content C of the element to be analyzed according to the Sherman equation i , to obtain the content of the element to be analyzed in the abrasive grain, and realize the correction of the granularity effect of the abrasive grain.

[0022] Further, in step S101,

[0023] According to the basic parameter method, the basic parameters of the XRF spectrum include the mass absorption coefficient, the fluorescence yield, the absorption limit transition factor, and the spectral line fraction; according to the Sherman equation, the relationship between the fluorescence intensity of the abrasive grain and the element content is represented as

[0024]

[0025] wherein

[0026]

[0027] In the formula, i is the element to be analyzed, j is the matrix element, that is, the element affected by the matrix effect, n is the number of all elements to be analyzed, s represents the measured substance, λ0 is the minimum wavelength of the incident X-ray, λ edgei is the critical excitation wavelength of the element to be analyzed, λ is the wavelength of the incident X-ray, λ i is the characteristic wavelength of the element to be analyzed, I i (λ i ) is the fluorescence intensity of the element to be analyzed, I0(λ) is the intensity of the incident X-ray, G i is the correction factor related to the analyzer, C i is the content of the element to be analyzed, C j is the content of the matrix element, k i is the sensitivity of the element to be analyzed, k j is the sensitivity of the matrix element, δ ij (λ) is the sensitivity of the matrix effect, D j (λ j ) is the correction factor related to the matrix element itself, D i (λ j ) is the correction factor related to the matrix element and the element to be analyzed, L ij (λ) is the coefficient of the matrix effect, r j is the absorption step coefficient of the matrix element, ω j is the fluorescence yield of the matrix element, f j is the spectral line fraction of the matrix element, Φ' is the incident angle, Φ" is the exit angle, μ i(λ) is the mass absorption coefficient of element i for wavelength λ, μ s (λ) and μ s (λ i ) are the effective mass absorption coefficients at the incident and exit, respectively, μ j (λ j ) is the mass absorption coefficient of matrix element j for matrix element wavelength λ j , μ j (λ) is the mass absorption coefficient of element i to be analyzed for matrix element wavelength λ j , μ s (λ j ) is the effective mass absorption coefficient of matrix element j for matrix element wavelength λ j .

[0028] Further, in steps S102 to S105,

[0029] The abrasive grain morphology parameters are obtained by the basic size parameter operation combination, which can quantitatively characterize the morphology characteristics of the abrasive grain, including the equivalent particle size D e , the compactness S o , the flatness e, the sphericity S p , and the convexity C o . On the basis of the original basic parameter XRF theory model, the influence of the abrasive grain morphology parameters on the theoretical characteristic X-ray fluorescence intensity I i of the element to be analyzed is represented as

[0030] I i ′=f(D e ,S o ,e,S p ,C o )I i (3)

[0031] Where I i ' is the actual characteristic X-ray fluorescence intensity of the element to be analyzed, I i is the theoretical characteristic X-ray fluorescence intensity of the element to be analyzed, and f represents the influence function of the comprehensive action of each morphology parameter of the abrasive grain on the fluorescence intensity. The solution of this function is achieved by means of simulation and experimental data, using multivariate fitting method combined with parameter estimation;

[0032] The volume of a single abrasive grain is calculated by the equivalent particle size, and the total mass m sum of the abrasive grains in the irradiation area is represented as

[0033]

[0034] In the formula, ρ is the density of the metal elemental abrasive grain, V g is the volume of a single abrasive grain, V sum is the total volume of the abrasive grains in the irradiation area, and Deg D is the equivalent diameter of the single abrasive particle, N is the total number of abrasive particles in the irradiation area;

[0035] According to formula (1), the total mass of abrasive particles in the irradiation area and the theoretical characteristic X-ray fluorescence intensity I of the element to be analyzed i show a positive correlation, that is,

[0036] I i = Km sum (5)

[0037] In the formula, K is a proportional coefficient, which is related to the mass absorption coefficient, fluorescence yield, and absorption limit transition factor, and is considered as a constant;

[0038] Substituting formula (5) into formula (3), we obtain

[0039] I i ′= f(D e ,S o ,e,S p ,C o )I i = f(D e ,S o ,e,S p ,C o )Km sum (6)

[0040] which can be written as

[0041]

[0042] Using the multiple linear regression method, the fluorescence intensity of the abrasive particles in the irradiation area is expressed as

[0043]

[0044] Using abrasive particle samples of the same element and different shapes, through several groups of experiments, a data set is established, and the regression coefficient estimation is realized based on the least square method or maximum likelihood estimation. The polynomial coefficients a0, a1, a2, a3, a4, a5 in formula (8) are obtained, and the quantitative influence relationship of the shape parameters on the fluorescence intensity is obtained. Substituting formula (8) into formula (3) obtains the abrasive particle size effect correction model, that is,

[0045]

[0046] The abrasive particle size effect correction model is used to correct the fluorescence intensity.

[0047] The application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for correcting the granularity effect of abrasive particles in three-dimensional image assisted XRF spectral analysis when executing the program.

[0048] The application further provides a computer readable storage medium, which stores a computer program, wherein the computer program implements the steps of the method for correcting the granularity effect of abrasive particles in three-dimensional image assisted XRF spectral analysis when executed by a processor.

[0049] Compared with the prior art, the technical scheme of the application has the beneficial effects that:

[0050] 1. Solving the problem of granularity effect of large-size abrasive particles: By synchronously collecting and analyzing the three-dimensional images of abrasive particles in oil, the morphological parameters of the abrasive particles can be accurately obtained, thereby effectively solving the problems of poor repeatability and low precision caused by the granularity effect of large-size abrasive particles.

[0051] 2. Improving the detection precision: By using the collected morphological parameters of the abrasive particles, the granularity effect of the abrasive particles in oil is corrected by improving the basic parameter method. In this way, not only the repeatability of oil element detection is improved, but also the detection precision is improved.

[0052] 3. Overcoming the limitations of traditional methods: The basic parameter method usually assumes that the measured substance is uniform, infinite, and has a flat and smooth surface, while the morphological differences of the abrasive particles in oil are huge in practice, and the correction precision of the traditional method is insufficient. The present application makes up for this deficiency by collecting the three-dimensional morphology of real abrasive particles, thereby significantly improving the correction precision.

[0053] 4. Adapting to the demand for rapid measurement on site: The present application does not require complex and time-consuming sample processing or manual selection, and is suitable for rapid measurement on site, thereby improving the detection efficiency and meeting the demand for practical application.

[0054] 5. Wide application: The method can be used for on-site detection of oil elements of various equipment systems including aircraft engines, gas turbines, etc., and has a wide application prospect.

[0055] 6. Low power and high precision: A high-precision and low-power XRF oil element detection device is provided, which reduces energy consumption while ensuring high detection precision.

[0056] In summary, the present application has significant advantages in improving the accuracy and efficiency of oil abrasive particle element detection, and provides reliable technical support for the condition monitoring and maintenance of mechanical equipment. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 Figure 1 is a structural schematic diagram of a device for correcting the granularity effect of abrasive particles.

[0058] Figure 2 Figure 1 is a schematic diagram of the specific connection and positional relationship of the abrasive particle granularity effect correction device.

[0059] Reference numerals: 101-stage, 102-confocal microscope, 103-beam scanning displacement stage, 104-spectrometer, 105-scanning displacement stage controller, 106-computer, 107-X-ray source, 108-SDD detector, 109-multichannel analyzer DETAILED DESCRIPTION

[0060] The application will be further described below in conjunction with the drawings and specific examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0061] The embodiment provides an abrasive particle granularity effect correction device for three-dimensional image assisted XRF spectral analysis, which comprises a stage 101, a confocal microscope 102, a beam scanning displacement stage 103, a spectrometer 104, a scanning displacement stage controller 105, a computer 106, an X-ray source 107, an SDD detector 108 and a multichannel analyzer 109.

[0062] The stage 101 is horizontally placed, the confocal microscope 102 is fixed and arranged above the stage 101 through the beam scanning displacement stage 103, the X-ray source 107 and the SDD detector 108 are arranged on the two sides above the stage 101 respectively, the beam scanning displacement stage 103 is sequentially connected with the scanning displacement stage controller 105 and the computer 106, the confocal microscope 102 is sequentially connected with the spectrometer 104 and the computer 106, and the computer 106 is sequentially connected with the multichannel analyzer 109 and the SDD detector 108.

[0063] The confocal microscope 102 comprises a white light point light source, a dispersion lens and a beam splitter.

[0064] The displacement scanning range of the confocal microscope 102 is controlled by the computer 106, so that the morphology detection area is coincided with the irradiation area of the X-ray on the stage 101, the XRF spectrum and the microscopic image data are collected through time sequence control, and the detection of the abrasive particle element and morphology in the same area is realized.

[0065] The embodiment further provides an abrasive particle granularity effect correction method for three-dimensional image assisted XRF spectral analysis based on the above abrasive particle granularity effect correction device, and the method specifically comprises the following steps.

[0066] An abrasive particle granularity effect correction method for three-dimensional image assisted XRF spectral analysis, which comprises the following steps.

[0067] S1. An abrasive particle granularity effect correction model is established.

[0068] S101. According to the Sherman equation, the relationship expression of the fluorescence intensity of the abrasive particles and the element content is constructed;

[0069] S102. The X-ray fluorescence theoretical model after introducing the abrasive particle morphology parameters is established;

[0070] S103. The total mass m of the abrasive particles in the irradiation area is calculated sum ;

[0071] S104. Based on the positive correlation between the total mass of the abrasive particles in the irradiation area and the theoretical fluorescence intensity of the irradiation area, the representation of the abrasive particle morphology parameters on the fluorescence intensity is obtained by using the multiple linear regression method;

[0072] S105. By using the abrasive particle samples of the same element and different morphologies, a data set is established through several experiments, the regression coefficient estimation is realized based on the least square method or the maximum likelihood estimation, the quantitative influence relationship of the morphology parameters on the fluorescence intensity is obtained, and the X-ray fluorescence theoretical model is substituted to realize the correction of the fluorescence intensity;

[0073] Specifically, in S1, according to the basic parameter method, the important basic parameters of XRF spectrum include mass absorption coefficient, fluorescence yield, absorption limit transition factor, spectral line fraction, etc. In order to obtain the relationship between XRF fluorescence intensity and element content to be analyzed, according to the Sherman equation, the relationship between the fluorescence intensity of the oil liquid abrasive particles and the element content can be expressed as

[0074]

[0075] Among them

[0076]

[0077] In the formula, i is the element to be analyzed, j is the matrix element, that is, the matrix effect influencing element, n is the number of all elements to be analyzed, s represents the measured substance, λ0 is the minimum wavelength of incident X-rays, λ edgei is the critical excitation wavelength of the element to be analyzed, λ is the incident X-ray wavelength, λ i is the characteristic wavelength of the element to be analyzed, I i (λ i ) is the fluorescence intensity of the element to be analyzed, I0(λ) is the incident X-ray intensity, G i is the correction factor related to the analyzer, C i is the content of the element to be analyzed, C j is the content of the matrix element, k i is the sensitivity of the element to be analyzed, k j is the sensitivity of the matrix element, δ ij (λ) is the sensitivity of the matrix effect, D j (λ j) is the correction factor related to the matrix element itself, D i (λ j ) is the correction factor related to the matrix element and the element to be analyzed, L ij (λ) is the coefficient of the matrix effect, r j is the absorption step coefficient of the matrix element, ω j is the fluorescence yield of the matrix element, f j is the spectral line fraction of the matrix element, Φ' is the incident angle, Φ" is the exit angle, μ i (λ) is the mass absorption coefficient of element i to wavelength λ, μ' s (λ) and μ" s (λ i ) are the effective mass absorption coefficients at the incident and exit, respectively, μ j (λ j ) is the mass absorption coefficient of matrix element j to matrix element wavelength λ j , μ j (λ) is the mass absorption coefficient of element to be analyzed i to matrix element wavelength λ j , μ s (λ j ) is the effective mass absorption coefficient of matrix element j to matrix element wavelength λ j .

[0078] The theoretical calculation of the fluorescence intensity of the above formula is based on the premise that the measured substance is uniform, infinite and flat and smooth in surface. However, the actual oil abrasive particles have great differences in morphology, and the particle size effect leads to significant changes in the intensity of X-rays, reducing the accuracy and repeatability of detection. The morphological parameters of abrasive particles are the root cause of the particle size effect, and the morphological parameters of abrasive particles need to be introduced to establish an improved X-ray fluorescence theoretical model.

[0079] The morphological parameters of abrasive particles are obtained by combining the basic size parameters, which can simply and efficiently quantify and characterize the morphological characteristics of particles, mainly including the equivalent particle size D e , the compactness S o , the flatness e, the sphericity S p , the convexity C o , etc. On the basis of the original basic parameter XRF theoretical model, the influence of the morphological parameters of abrasive particles on the theoretical characteristic X-ray fluorescence intensity I i of the element to be analyzed is represented as

[0080] I i ′=f(D e ,S o ,e,S p ,C o )I i (3)

[0081] Wherein, I i I is the actual characteristic X-ray fluorescence intensity of the element to be analyzed, I i is the theoretical characteristic X-ray fluorescence intensity of the element to be analyzed, and f represents the influence function of the morphological parameters of the abrasive particles on the fluorescence intensity. The specific form of this function can be solved by simulation and experimental data, using multivariate fitting method combined with parameter estimation.

[0082] According to the XRF principle, for a sample containing only one specific element, in an ideal case, the detected characteristic X-ray fluorescence intensity is related to the absolute content (mass) of the element. For abrasive particle samples, due to uneven distribution, the total number and total volume of abrasive particles in the irradiation area differ each time, directly affecting the characteristic X-ray fluorescence intensity. Using metal single-element abrasive particles, based on the abrasive particle morphology detection results, the number and volume of abrasive particles in the irradiation area are statistically analyzed, and based on the XRF abrasive particle element detection results, the characteristic X-ray measurement fluorescence intensity of the abrasive particles in the irradiation area can be obtained. The volume of a single abrasive particle is calculated by the equivalent particle diameter, and the total mass m sum is expressed as

[0083]

[0084] In the formula, p is the density of the metal single-element abrasive particles, V g is the volume of a single abrasive particle, V sum is the total volume of abrasive particles in the irradiation area, D eg is the equivalent particle diameter of a single abrasive particle, and N is the total number of abrasive particles in the irradiation area; according to formula (1), the total mass of abrasive particles in the irradiation area and the theoretical characteristic X-ray fluorescence intensity I i of the element to be analyzed present a positive correlation, that is,

[0085] I i = K m sum (5)

[0086] In the formula, K is a proportional coefficient related to the mass absorption coefficient, fluorescence yield, absorption limit transition factor, etc., and is regarded as a constant.

[0087] However, due to the particle size effect of abrasive particles, the actual fluorescence intensity detected in the irradiation area differs from the theoretical fluorescence intensity. Substituting formula (5) into formula (3), we get

[0088] I i ′= f (D e ,S o ,e,S p ,C o )I i = f (D e ,S o ,e,S p ,Co )Km sum (6)

[0089] can be written as

[0090]

[0091] The particle size effect correction model is obtained by using the multi-element, different morphology of abrasive grain sample, through a plurality of experiments, establishing the irradiation area of abrasive grain morphology parameter data set and theoretical fluorescence intensity data set, based on least square method or maximum likelihood estimation to realize regression coefficient estimation, get the quantitative influence relationship of morphology parameters on fluorescence intensity, into formula (3), realize the correction of fluorescence intensity, obtain the particle size effect correction model of abrasive grain

[0092]

[0093] The particle size effect correction model is obtained by using the multi-element, different morphology of abrasive grain sample, through a plurality of experiments, establishing the irradiation area of abrasive grain morphology parameter data set and theoretical fluorescence intensity data set, based on least square method or maximum likelihood estimation to realize regression coefficient estimation, get the quantitative influence relationship of morphology parameters on fluorescence intensity, into formula (3), realize the correction of fluorescence intensity, obtain the particle size effect correction model of abrasive grain

[0094]

[0095] The particle size effect correction model is obtained by using the multi-element, different morphology of abrasive grain sample, through a plurality of experiments, establishing the irradiation area of abrasive grain morphology parameter data set and theoretical fluorescence intensity data set, based on least square method or maximum likelihood estimation to realize regression coefficient estimation, get the quantitative influence relationship of morphology parameters on fluorescence intensity, into formula (3), realize the correction of fluorescence intensity, obtain the particle size effect correction model of abrasive grain

[0096] S2. The particle size effect correction device is used to obtain the three-dimensional image and XRF spectrum data of the abrasive grain in the irradiation area simultaneously.

[0097] S3. The three-dimensional image of the abrasive grain is processed by computer to obtain the morphology parameters of the abrasive grain in the irradiation area, including the equivalent particle size D e , the compactness S o , the flatness e, the sphericity S p , and the convexity C o .

[0098] S4. The XRF spectrum data is processed by computer to obtain the actual characteristic X-ray fluorescence intensity I i ' of the analyzed element in the abrasive grain.

[0099] S5. The morphology parameters of the abrasive grain are substituted into the particle size effect correction model of the abrasive grain, i.e. formula (9), to obtain the theoretical characteristic X-ray fluorescence intensity I i of the analyzed element.

[0100] S4. The content C i of the analyzed element is calculated according to the Sherman equation to obtain the content of the analyzed element in the abrasive grain, and the particle size effect correction of the abrasive grain is realized.

[0101] Preferably, the embodiment of the present application further provides a specific implementation of an electronic device capable of implementing all steps of the abrasive particle granularity effect correction method of three-dimensional image assisted XRF spectrum analysis in the above embodiment, and the electronic device specifically includes the following contents:

[0102] a processor, a memory, a communications interface, and a bus;

[0103] The processor, the memory, and the communications interface complete mutual communication through the bus; the communications interface is used for realizing information transmission between a server-side device, a metering device, a user-side device, and other related devices.

[0104] The processor is used for calling a computer program in the memory, and the processor realizes all steps of the abrasive particle granularity effect correction method of three-dimensional image assisted XRF spectrum analysis in the above embodiment when executing the computer program.

[0105] The embodiment of the present application further provides a computer readable storage medium capable of implementing all steps of the abrasive particle granularity effect correction method of three-dimensional image assisted XRF spectrum analysis in the above embodiment, and the computer readable storage medium stores a computer program, and the computer program realizes all steps of the abrasive particle granularity effect correction method of three-dimensional image assisted XRF spectrum analysis in the above embodiment when being executed by a processor.

[0106] Each of the embodiments in the specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each of the embodiments mainly describes differences from other embodiments. Especially, for the hardware+program type embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the related parts can be referred to the part of the method embodiment.

[0107] The above describes specific embodiments of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be executed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0108] Although the present application provides method operational steps as the embodiments or flowcharts, more or less operational steps can be included based on routine or non-creative labor. The order of steps listed in the embodiments is only one of the many ways of executing the steps, and does not represent the only way of execution. In actual device or client product execution, the method order shown in the embodiments or the drawings can be executed in sequence or in parallel (for example, in parallel processor or multi-thread processing environment).

[0109] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code thereon.

[0110] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks

[0112] The present application is not limited to the embodiments described above. The above description of the specific embodiments is intended to describe and illustrate the technical solutions of the present application, and the specific embodiments described above are merely illustrative and are not restrictive. Based on the disclosure of the present application, those skilled in the art can make many forms of specific changes without departing from the purpose of the present application and the scope protected by the claims, and these all belong to the protection scope of the present application.

Claims

1. A method of three-dimensional image assisted XRF spectral analysis grit particle size effect correction, characterized by, The method comprises the following steps: S1. Establishing a particle size effect correction model of abrasive particles: S101. According to the Sherman equation, a relationship expression between the fluorescence intensity of the abrasive particles and the element content is constructed; S102. A theoretical X-ray fluorescence model after introducing the abrasive particle morphology parameters is established; S103. Calculate the total mass of abrasive particles within the irradiation area ; S104. Based on the positive correlation between the total mass of the abrasive particles in the irradiation area and the theoretical fluorescence intensity of the irradiation area, the abrasive particle morphology parameters are used to represent the fluorescence intensity by using a multiple linear regression method; S105. A data set is established by using abrasive particle samples of the same element and different morphologies through a plurality of experiments, and the least square method or the maximum likelihood estimation is used to realize the regression coefficient estimation, so as to obtain the quantitative influence relationship of the morphology parameters on the fluorescence intensity, and the X-ray fluorescence theoretical model is substituted to realize the correction of the fluorescence intensity; S2. The abrasive particle three-dimensional image and the XRF spectrum data in the irradiation area are obtained by using the particle size effect correction device of the abrasive particles; S3. The abrasive particle morphology parameters in the irradiation area are obtained by processing the abrasive particle three-dimensional image by using a computer; S4. Processing the XRF spectral data by computer to obtain the actual characteristic X-ray fluorescence intensity I of the element to be analyzed in the abrasive grain i ' ; S5. Substitute the abrasive grain morphology parameters into the abrasive grain granularity effect correction model to obtain the theoretical characteristic X-ray fluorescence intensity I of the element to be analyzed i ; S4. Calculate the content C of the element to be analyzed according to the Sherman equation i , to obtain the content of the element to be analyzed in the abrasive particles and achieve the correction of the particle size effect of the abrasive particles.

2. The method of claim 1, wherein the method is a method of three-dimensional image assisted XRF spectral analysis of abrasive grain particle size effect correction. In step S101, According to the basic parameter method, the basic parameters of the XRF spectrum include the mass absorption coefficient, the fluorescence yield, the absorption limit transition factor and the spectral line fraction; according to the Sherman equation, the relationship between the fluorescence intensity of the abrasive particles and the element content is represented as (1)； Wherein (2)； where i is the element to be analyzed, j is the matrix element, i.e. the matrix effect influencing element, n is the number of all elements to be analyzed, s represents the substance to be measured, λ0is the minimum wavelength of the incident X-rays, λ edgei is the critical excitation wavelength of the element to be analyzed, λ is the wavelength of the incident X-rays, λ i is the characteristic wavelength of the element to be analyzed, I i (λ i ) is the fluorescence intensity of the element to be analyzed, I0(λ) is the intensity of the incident X-rays, G i is a correction factor related to the analysis instrument, C i is the content of the element to be analyzed, C j is the content of the matrix element, k i is the sensitivity of the element to be analyzed, k j is the sensitivity of the matrix element, is the sensitivity of the matrix effect, D j (λ j ) is a correction factor related to the matrix element itself, D i (λ j ) is a correction factor related to the matrix element and the element to be analyzed, is the coefficient of the matrix effect, r j is the absorption step coefficient of the matrix element, ω j is the fluorescence yield of the matrix element, f j is the spectral line fraction of the matrix element, Φ' is the angle of incidence, Φ" is the angle of emergence, μ i (λ) is the mass absorption coefficient of the element i for the wavelength λ, μ' s (λ) and μ" s (λ i ) are the effective mass absorption coefficients for the incidence and the emergence, respectively, μ j (λ j ) is the mass absorption coefficient of the matrix element j for the wavelength λ j of the matrix element, μ j (λ) is the mass absorption coefficient of the element to be analyzed i for the wavelength λ j of the matrix element, μ s (λ j ) is the effective mass absorption coefficient of the matrix element j for the wavelength λ j of the matrix element.

3. The method of claim 1, wherein the method is a method of three-dimensional image assisted XRF spectral analysis of abrasive grain particle size effect correction. In steps S102 to S105, The abrasive grain morphology parameters are obtained by operation and combination of the basic size parameters, and can quantitatively represent the morphology characteristics of the abrasive grains, including equivalent particle diameter D e , compactness S o , flatness e, sphericity S p , convexity C o , on the basis of the original basic parameter method XRF theoretical model, the influence of the abrasive grain morphology parameters on the theoretical characteristic X-ray fluorescence intensity I i of the element to be analyzed is represented as (3)； where I i ' is the actual characteristic X-ray fluorescence intensity of the element to be analyzed, X i is the theoretical characteristic X-ray fluorescence intensity of the element to be analyzed, and f represents the influence function of the comprehensive action of each morphological parameter of the abrasive particles on the fluorescence intensity. The solution of this function is achieved by means of simulation and experimental data, using a multivariate fitting method combined with parameter estimation. The volume of the individual abrasive particles is calculated from the equivalent diameter, and the total mass of the abrasive particles in the irradiated area is is represented as (4)； where p is the density of the metal elemental abrasive particle, V g is the volume of a single abrasive particle, V sum is the total volume of abrasive particles in the irradiated area, D eg is the equivalent particle diameter of a single abrasive particle, and N is the total number of abrasive particles in the irradiated area. According to formula (1), the total mass of abrasive grains in the irradiation area and the theoretical characteristic X-ray fluorescence intensity of the element to be analyzed a positive correlation relationship, that is (5)； In the formula, K is a proportional coefficient, which is related to the mass absorption coefficient, the fluorescence yield and the absorption limit transition factor, and is regarded as a constant; Formula (5) is substituted into formula (3) to obtain (6)； It can be written as (7)； By using a multiple linear regression method, the abrasive particle morphology parameters in the irradiation area are represented as (8)； By using abrasive particle samples of the same element and different morphologies, a data set is established through a plurality of experiments, and the least square method or the maximum likelihood estimation is used to realize the regression coefficient estimation, so as to obtain the quantitative influence relationship of the morphology parameters on the fluorescence intensity, and formula (8) is substituted into formula (3) to obtain the particle size effect correction model of the abrasive particles, that is (9)； The fluorescence intensity is corrected by using the particle size effect correction model of the abrasive particles.

4. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor realizes the steps of the particle size effect correction method of the three-dimensional image assisted XRF spectrum analysis of the abrasive particles according to any one of claims 1 to 3 when the processor executes the program.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program realizes the steps of the particle size effect correction method of the three-dimensional image assisted XRF spectrum analysis of the abrasive particles according to any one of claims 1 to 3 when the computer program is executed by the processor.

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