X-ray diffraction-based method and system for detecting calcium carbonate content of artificial quartz stone
By optimizing the selection of characteristic peaks and the integration interval, and combining wavelet transform and pseudo-Voigt function fitting, the complex peak shape and overlap problems in the detection of calcium carbonate content in artificial quartz stone were solved, and high-precision calcium carbonate content detection was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- MACHENG ZHONGLEI NEW BUILDING MATERIALS CO LTD
- Filing Date
- 2025-10-23
- Publication Date
- 2026-08-04
AI Technical Summary
In existing technologies, X-ray diffraction detection methods for artificial quartz are difficult to accurately select characteristic peaks and perform integration. Furthermore, the high temperature and high pressure environment leads to complex diffraction peak morphologies, which cannot meet the precise requirements of modern industry for the detection of calcium carbonate content.
By calculating the initial independence coefficient and structural complexity parameters, optimizing the diffraction angle window, and using continuous wavelet transform and pseudo-Voigt function fitting to correct asymmetric distortion, accurate detection of calcium carbonate content is achieved.
It improves the accuracy and precision of calcium carbonate content detection, overcomes the negative impact of complex peak shapes and overlaps on quantitative analysis, and meets the needs of industrial quality control.
Smart Images
Figure CN121364203B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of content detection technology, specifically to a method and system for detecting the calcium carbonate content in artificial quartz based on X-ray diffraction. Background Technology
[0002] Artificial quartz stone is a new type of green and environmentally friendly building decoration material. Due to its excellent properties such as high hardness, corrosion resistance, and rich colors, it is widely used in kitchen countertops, floors, and walls. Its main components include quartz sand as aggregate, unsaturated polyester resin as binder, and pigments and other additives, manufactured through high-pressure pressing and curing processes. During production, to optimize costs and adjust material properties, manufacturers often add a certain amount of calcium carbonate powder as a filler. Therefore, the calcium carbonate content becomes a key quality indicator, directly affecting the product's hardness, gloss, acid resistance, and final cost. Currently, the industry mainly uses chemical titration or thermogravimetric analysis to detect calcium carbonate content. While these methods are accurate, they generally have limitations such as cumbersome operation, long testing cycles, and sample destructiveness.
[0003] X-ray diffraction (XRD) analysis has become an important tool for quantitative phase analysis due to its non-destructive, rapid, and simple sample preparation advantages. This technique, by measuring the integrated intensity of characteristic diffraction peaks of the analyte and the matrix (or internal standard), and combining this with models such as the reference intensity method, can accurately determine the content of each component in a mixture. However, applying traditional XRD techniques to synthetic quartz faces two major challenges. First, the complex composition of synthetic quartz leads to overlapping diffraction peaks of quartz, calcium carbonate, and other possible crystalline phases in its diffraction pattern, greatly complicating the accurate selection and integration of characteristic peaks. Second, the high-temperature and high-pressure environment during production easily causes lattice distortion, uneven crystallinity, or preferred orientation in phases such as quartz and calcium carbonate. This causes the diffraction peak profiles to deviate from the ideal symmetrical shape, often exhibiting complex asymmetric distortions such as broadening, tailing, and shoulder peaks. Traditional quantitative analysis methods often use fixed diffraction angle windows for integration or fit peak shapes with a single function. These methods struggle to handle complex peak shapes and overlap issues, thus failing to meet the precise quality control requirements of modern industry. Summary of the Invention
[0004] This invention provides a method and system for detecting calcium carbonate content in artificial quartz based on X-ray diffraction, which solves the problems in the prior art where it is difficult to accurately select characteristic peaks and integrate the diffraction peaks, and the contours of the diffraction peaks deviate from the ideal symmetrical shape, resulting in low accuracy in detecting calcium carbonate content.
[0005] In a first aspect, the present invention provides a method for detecting the calcium carbonate content in artificial quartz based on X-ray diffraction, comprising the following steps: X-ray diffraction (XRD) data of artificial quartz samples were acquired, including diffraction angles and intensities. Multiple characteristic diffraction peaks of quartz and calcium carbonate were pre-defined in the data. The ratio of peak intensity to the sum of signal intensities within the initial diffraction angle window of each characteristic diffraction peak was calculated to obtain the initial independence coefficient. The calcium carbonate characteristic diffraction peak with the largest initial independence coefficient was selected as the initial target peak. The peak shape profile of the initial target peak was fitted, and the ratio of the sum of the integrated areas of the shoulder peaks to the integrated area of the main peak was calculated to obtain the structural complexity parameter. Based on the structural complexity parameter, the analytical diffraction angle window for each characteristic diffraction peak was determined. The independence coefficient was recalculated within each analytical diffraction angle window, and the coefficient was selected accordingly. The largest quartz characteristic diffraction peak is selected as the reference peak, and the calcium carbonate characteristic diffraction peak with the largest independence coefficient is selected as the target peak. Based on the peak shape profile of the target peak, wavelet coefficients at the second and third scales are extracted using continuous wavelet transform. The energy integral ratio of the wavelet coefficients on both sides of the peak point of the target peak is calculated to obtain the asymmetric distortion coefficient. The peak shape profiles of the target peak and the reference peak are fitted respectively to obtain their respective main peak integral areas. When the structural complexity parameter is not lower than the first preset threshold, the main peak integral area of the target peak is corrected using the asymmetric distortion coefficient to obtain the corrected integral area. Based on the main peak integral area or the corrected integral area of the target peak, and the main peak integral area of the reference peak, the calcium carbonate content is calculated.
[0006] Preferably, the step of pre-setting multiple characteristic diffraction peaks of quartz and calcium carbonate in the spectral data includes: The diffraction peaks at 2θ angles of 20.86° and 26.64° of quartz were pre-defined as characteristic diffraction peaks of quartz. The diffraction peaks of calcium carbonate at 2θ angles of 29.42°, 39.43°, and 47.54° are preset as characteristic diffraction peaks of calcium carbonate; the initial diffraction angle window for each characteristic diffraction peak is set to a range of 1.0° plus or minus 1θ angle position.
[0007] Preferably, the step of calculating the ratio of peak intensity to the sum of signal intensities within the initial diffraction angle window of each characteristic diffraction peak to obtain the initial independence coefficient, and selecting the calcium carbonate characteristic diffraction peak with the largest initial independence coefficient as the initial target peak, includes: Within each initial diffraction angle window, the maximum diffraction intensity among the data points is taken as the peak intensity. The diffraction intensities of all data points are summed to obtain the total signal intensity. The ratio of the peak intensity to the total signal intensity is calculated to obtain the initial independence coefficient. By comparing the initial independence coefficients of the characteristic diffraction peaks of calcium carbonate, the characteristic diffraction peak of calcium carbonate with the largest initial independence coefficient is determined as the initial target peak.
[0008] Preferably, the process of fitting the peak shape profile of the initial target peak and calculating the ratio of the sum of the integral areas of the shoulder peaks to the integral area of the main peak to obtain the structural complexity parameter includes: A nonlinear least squares method is employed, using a model composed of the superposition of three pseudo-Voigt functions to model the initial target peak with the 2θ angle position of the initial target peak as the center. Fit the peak shape profile within the range; Among the three pseudo-Voigt functions obtained by fitting, the one with the highest peak diffraction intensity is defined as the main peak, and the other two are defined as shoulder peaks. Calculate the sum of the areas of the shoulder peak integrals of the two shoulder peak functions, then calculate the area of the main peak integral of the main peak function. Divide the sum of the areas of the shoulder peak integrals by the area of the main peak integral to obtain the structural complexity parameter.
[0009] Preferably, the step of determining the analytical diffraction angle window for each characteristic diffraction peak based on the structural complexity parameter includes: Using formula Calculate the total width of the diffraction angle window. ,in, This is a structural complexity parameter; When calculated When the angle is less than 0.6°, take Equal to 0.6°; Centered on the 2θ angle position of each characteristic diffraction peak, with Using the radius, determine the analytical diffraction angle window for each characteristic diffraction peak.
[0010] Preferably, the step of extracting wavelet coefficients at the second and third scales based on the peak profile of the target peak using continuous wavelet transform, and calculating the energy integral ratio of the wavelet coefficients on both sides of the peak point of the target peak to obtain the asymmetric distortion coefficients includes: Symlets4 was selected as the mother wavelet function, and continuous wavelet transform was performed on the peak shape profile of the target peak within the analysis diffraction angle window to obtain the wavelet coefficient sequence at the second scale and the wavelet coefficient sequence at the third scale, respectively. Taking the 2θ angle position corresponding to the peak diffraction intensity of the target peak as the center point, the sum of the squares of all wavelet coefficients to the left of the center point within the analysis diffraction angle window is taken as the left energy integral, and the sum of the squares of all wavelet coefficients to the right is taken as the right energy integral. The left-side energy integral at the second scale is added to the left-side energy integral at the third scale to obtain the total left-side energy integral; the right-side energy integral at the second scale is added to the right-side energy integral at the third scale to obtain the total right-side energy integral; the ratio of the total right-side energy integral to the total left-side energy integral is calculated to obtain the asymmetric distortion coefficient.
[0011] Preferably, when the structural complexity parameter is not lower than a first preset threshold, the integral area of the main peak of the target peak is corrected using an asymmetric distortion coefficient to obtain the corrected integral area, including: When the structural complexity parameter is greater than or equal to the first preset threshold, the corrected integral area is calculated using the following formula. : ; in, The integral area of the main peak of the target peak. The asymmetric distortion coefficient.
[0012] Preferably, the step of fitting the peak profiles of the target peak and the reference peak respectively to obtain the integral area of their respective main peaks includes: Linear background subtraction is performed on the data of the target peak and the reference peak within their respective analysis diffraction angle windows; The Levenberg-Marquardt algorithm was used to fit the peak profile after background subtraction using pseudo-Voigt function with peak height, peak position, full width at half maximum and Gauss-Lorentz mixing ratio as parameters. Based on the optimal parameters obtained from the fitting, the integral area of the main peak is calculated by performing analytical integration on the pseudo-Voigt function.
[0013] Preferably, the calculation of calcium carbonate content based on the integral area of the main peak of the target peak or the corrected integral area, and the integral area of the main peak of the reference peak includes: The mass percentage of calcium carbonate was calculated using an adiabatic model. The calculation formula is: ; in, This represents the integral area of the main peak of the quartz benchmark peak. The integral area of the main peak or the corrected integral area of the target peak for calcium carbonate. This is the relative intensity factor.
[0014] Secondly, the X-ray diffraction-based artificial quartz calcium carbonate content detection system of the present invention includes a memory and a processor. The memory stores computer instructions, and when the processor executes the computer instructions, it implements the above-mentioned X-ray diffraction-based artificial quartz calcium carbonate content detection method.
[0015] The beneficial effects of this invention are as follows: By calculating the independence coefficient, this invention reduces analytical interference caused by overlapping phase peaks in the spectrum. It uses a structural complexity parameter to represent the complexity of the spectrum and determines the width of the analytical diffraction angle window accordingly, ensuring the accuracy of peak area integration. This invention uses continuous wavelet transform to quantitatively represent the asymmetric distortion of the target peak and corrects the area of complex peak shapes caused by factors such as lattice distortion. Through a series of optimizations to peak selection, integration interval, and peak shape correction, this invention overcomes the negative impact of peak overlap and peak shape distortion in complex sample matrices on quantitative analysis. This invention can improve the detection quality of calcium carbonate content in artificial quartz. Attached Figure Description
[0016] Figure 1 This is a schematic flowchart of a method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction, provided in an embodiment of the present invention. Detailed Implementation
[0017] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0018] like Figure 1 As shown, an embodiment of the method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction provided by the present invention includes the following steps: S1. Obtain X-ray diffraction pattern data of the artificial quartz sample. The pattern data includes diffraction angle and diffraction intensity. Preset multiple characteristic diffraction peaks of quartz and calcium carbonate in the pattern data. Calculate the ratio of peak intensity to the sum of signal intensity within the initial diffraction angle window of each characteristic diffraction peak to obtain the initial independence coefficient. Select the characteristic diffraction peak of calcium carbonate with the largest initial independence coefficient as the initial target peak.
[0019] Specifically, the artificial quartz sample was first crushed and passed through a 200-mesh sieve to obtain a powder sample. Then, the powder was pressed into a smooth sample piece for testing using a pressing method. Data acquisition was performed using an X-ray diffractometer with the following settings: copper target Kα radiation source, tube voltage 40 kV, tube current 40 mA. The scanning range was set to 10° to 90° at the 2θ angle, with a scanning step of 0.02°, to obtain spectral data showing the variation of sample diffraction intensity with the diffraction angle.
[0020] In an optional embodiment, the step of pre-setting multiple characteristic diffraction peaks of quartz and calcium carbonate in the spectral data includes: The diffraction peaks at 2θ angles of 20.86° and 26.64° of quartz were pre-defined as characteristic diffraction peaks of quartz. The diffraction peaks of calcium carbonate at 2θ angles of 29.42°, 39.43°, and 47.54° are preset as characteristic diffraction peaks of calcium carbonate; the initial diffraction angle window for each characteristic diffraction peak is set to a range of 1.0° plus or minus 1θ angle position.
[0021] The process involves calculating the ratio of peak intensity to the sum of signal intensities within the initial diffraction angle window of each characteristic diffraction peak to obtain the initial independence coefficient. The calcium carbonate characteristic diffraction peak with the largest initial independence coefficient is selected as the initial target peak. This includes: Within each initial diffraction angle window, the maximum diffraction intensity among the data points is taken as the peak intensity. The diffraction intensities of all data points are summed to obtain the total signal intensity. The ratio of the peak intensity to the total signal intensity is calculated to obtain the initial independence coefficient. By comparing the initial independence coefficients of the characteristic diffraction peaks of calcium carbonate, the characteristic diffraction peak of calcium carbonate with the largest initial independence coefficient is determined as the initial target peak.
[0022] For example, an initial diffraction angle window is first set for each characteristic peak. For instance, for the 29.42° peak of calcium carbonate, the window range can be set from 28.42° to 30.42°. Assume that within this window, the highest detected diffraction intensity (peak intensity) is 5000 count units, and the cumulative diffraction intensity of all data points within the window (total signal intensity) is 80000 count units. According to the calculation rules, the initial independence coefficient for this peak is 5000 divided by 80000, which is 0.0625. Similarly, the same calculation is performed for the other two characteristic peaks of calcium carbonate, 39.43° and 47.54°, assuming the obtained coefficients are 0.0510 and 0.0480, respectively. By comparing these three coefficients (0.0625, 0.0510, and 0.0480), since 0.0625 is the maximum value, the 29.42° diffraction peak is selected as the initial target peak.
[0023] S2. Fit the peak shape profile of the initial target peak, calculate the ratio of the sum of the integral areas of the shoulder peaks to the integral area of the main peak, and obtain the structural complexity parameter; determine the analysis diffraction angle window of each characteristic diffraction peak based on the structural complexity parameter; recalculate the independence coefficient within each analysis diffraction angle window, select the quartz characteristic diffraction peak with the largest independence coefficient as the reference peak, and select the calcium carbonate characteristic diffraction peak with the largest independence coefficient as the target peak.
[0024] In an optional embodiment, fitting the peak profile of the initial target peak and calculating the ratio of the sum of the integral areas of the shoulder peaks to the integral area of the main peak to obtain the structural complexity parameter includes: A nonlinear least squares method is employed, using a model composed of the superposition of three pseudo-Voigt functions to model the initial target peak with the 2θ angle position of the initial target peak as the center. Fit the peak shape profile within the range; Among the three pseudo-Voigt functions obtained by fitting, the one with the highest peak diffraction intensity is defined as the main peak, and the other two are defined as shoulder peaks. Calculate the sum of the areas of the shoulder peak integrals of the two shoulder peak functions, then calculate the area of the main peak integral of the main peak function. Divide the sum of the areas of the shoulder peak integrals by the area of the main peak integral to obtain the structural complexity parameter.
[0025] Specifically, the initial target peak determined in the previous step, centered at 29.42°, is selected, and data within a 1.5° range on either side of its center position are extracted, resulting in peak profile data from 27.92° to 30.92°. Then, a mathematical model consisting of the superposition of three independent pseudo-Voigt functions is used, and this peak profile is fitted using nonlinear least squares; the algorithm adjusts the parameters of the three functions to best match the experimental data.
[0026] After fitting, three independent pseudo-Voigt functions are obtained. For example, suppose the peak intensities of these three functions are 4800, 350, and 200 count units, respectively. By definition, the function with an intensity of 4800 is considered the main peak, and the other two are shoulder peaks. Next, the integral area below each of them is calculated. Assume the integral area of the main peak is 12000 units, and the integral areas of the two shoulder peaks are 900 units and 500 units, respectively. Adding the integral areas of the two shoulder peaks gives 1400 units. Dividing 1400 by the integral area of the main peak (12000) yields a structural complexity parameter of approximately 0.117.
[0027] In an optional embodiment, the step of determining the analytical diffraction angle window for each characteristic diffraction peak based on the structural complexity parameter includes: Using formula Calculate the total width of the diffraction angle window. ,in, This is a structural complexity parameter; When calculated When the angle is less than 0.6°, take Equal to 0.6°; Centered on the 2θ angle position of each characteristic diffraction peak, with Using the radius, determine the analytical diffraction angle window for each characteristic diffraction peak.
[0028] For example, assume the structural complexity parameter The value is 0.117, and the total width of the analysis diffraction angle window is calculated using the formula. The value is 1.9415°. Since 1.9415° > 0.6°, the total width of the determined analytical diffraction angle window is 1.9415°. If another sample... If the value is large, for example, 3.0, the calculated value is... Since 0.5° is less than 0.6°, the total width of the analytical diffraction angle window determined in this case is 0.6°. Centered on the 2θ angle position of each characteristic diffraction peak, with... Using the radius, determine the analytical diffraction angle window for each characteristic diffraction peak.
[0029] Within the analysis diffraction angle window of each characteristic diffraction peak, the ratio of the peak intensity to the sum of the signal intensities within the window is calculated to obtain a new independence coefficient. The quartz peak with the largest new independence coefficient, such as the 26.6° peak, is selected as the reference peak; the calcium carbonate peak with the largest new independence coefficient, such as the 29.4° peak, is selected as the target peak.
[0030] S3. Based on the peak shape profile of the target peak, the wavelet coefficients at the second and third scales are extracted using continuous wavelet transform. The energy integral ratio of the wavelet coefficients on both sides of the peak point of the target peak is calculated to obtain the asymmetric distortion coefficient.
[0031] Specifically, Symlets4 is selected as the mother wavelet function, and continuous wavelet transform is performed on the peak shape profile of the target peak within the analysis diffraction angle window to obtain the wavelet coefficient sequence at the second scale and the wavelet coefficient sequence at the third scale, respectively. Taking the 2θ angle position corresponding to the peak diffraction intensity of the target peak as the center point, the sum of the squares of all wavelet coefficients to the left of the center point within the analysis diffraction angle window is taken as the left energy integral, and the sum of the squares of all wavelet coefficients to the right is taken as the right energy integral. The left-side energy integral at the second scale is added to the left-side energy integral at the third scale to obtain the total left-side energy integral; the right-side energy integral at the second scale is added to the right-side energy integral at the third scale to obtain the total right-side energy integral; the ratio of the total right-side energy integral to the total left-side energy integral is calculated to obtain the asymmetric distortion coefficient.
[0032] Specifically, firstly, data within the analysis diffraction angle window determined in the previous step is extracted from the target peak, for example, data between 28.45° and 30.39°. Then, Symlets4 is selected as the mother wavelet function to perform continuous wavelet transform on this extracted data, thereby generating a series of wavelet coefficient values at the second and third scales, respectively.
[0033] Determine the 2θ angle position corresponding to the peak intensity of the target peak, for example, 29.45°, and use it as the center point. Next, process the wavelet coefficient sequences at the second and third scales respectively. Taking the second scale as an example: sum the squares of all coefficients to the left of the center point to obtain the left energy integral, assumed to be 1500 units; similarly, sum the squares of all coefficients to the right to obtain the right energy integral, assumed to be 1650 units. Perform the same operation on the coefficient sequence at the third scale, assuming a left energy of 800 units and a right energy of 920 units. Then, combine the energies of the two scales: the total left energy is 2300 units, and the total right energy is 2570 units. Finally, divide the total right energy by the total left energy to obtain the asymmetric distortion coefficient of approximately 1.117.
[0034] S4. Fit the peak shape profiles of the target peak and the reference peak respectively to obtain their respective main peak integral areas. When the structural complexity parameter is not lower than the first preset threshold, use the asymmetric distortion coefficient to correct the main peak integral area of the target peak to obtain the corrected integral area. Calculate the calcium carbonate content based on the main peak integral area or the corrected integral area of the target peak and the main peak integral area of the reference peak.
[0035] In an optional embodiment, fitting the peak profiles of the target peak and the reference peak respectively to obtain their respective main peak integral areas includes: Linear background subtraction is performed on the data of the target peak and the reference peak within their respective analysis diffraction angle windows; The Levenberg-Marquardt algorithm was used to fit the peak profile after background subtraction using pseudo-Voigt function with peak height, peak position, full width at half maximum and Gauss-Lorentz mixing ratio as parameters. Based on the optimal parameters obtained from the fitting, the integral area of the main peak is calculated by performing analytical integration on the pseudo-Voigt function.
[0036] Specifically, the target peak of calcium carbonate and the reference peak of quartz (e.g., the peak at 26.64° of quartz) were selected, and the data of these two peaks within their respective analytical diffraction angle windows were extracted. Subsequently, linear background subtraction was performed on these two sets of data to eliminate the influence of baseline noise in the diffraction patterns.
[0037] For each set of peak data after background subtraction, the Levenberg-Marquardt algorithm is used to fit a pseudo-Voigt function. This algorithm iteratively adjusts four core parameters of the function: peak height, peak position, full width at half maximum (FWHM), and Gaussian-Lorentz mixing ratio, until the error between the fitted curve and the experimental data points is minimized. After fitting, the optimal parameter set describing the profile of each peak is obtained. Using this optimal parameter set, the total area under the function curve, i.e., the integral area of the main peak, can be calculated by analytically integrating the mathematical expression of the pseudo-Voigt function. For example, this method calculates the integral area of the main peak of the calcium carbonate target peak to be 12,000 units, while the integral area of the main peak of the quartz reference peak is 25,000 units.
[0038] In an optional embodiment, when the structural complexity parameter is not lower than a first preset threshold, the integral area of the main peak of the target peak is corrected using an asymmetric distortion coefficient to obtain the corrected integral area, including: When the structural complexity parameter is greater than or equal to the first preset threshold, the corrected integral area is calculated using the following formula. : ; in, The integral area of the main peak of the target peak. The asymmetric distortion coefficient.
[0039] Specifically, a first preset threshold is set to 0.15. If the structural complexity parameter is ≥0.15, the peak distortion is considered severe and correction is required. If the structural complexity parameter is <0.15, no correction is required.
[0040] For example, suppose the structure complexity parameter of a sample is 0.18. Since 0.18 ≥ 0.15, it needs to be adjusted. If the structure complexity parameter of another sample is 0.117, then no adjustment is needed. For the case where adjustment is required, assume... It is 1.117. The corrected integral area is calculated with 12,000 units. The value is 12280.8 units.
[0041] In an optional embodiment, calculating the calcium carbonate content based on the integral area of the target peak or its corrected integral area, and the integral area of the reference peak, includes: The mass percentage of calcium carbonate was calculated using an adiabatic model. The calculation formula is: ; in, This represents the integral area of the main peak of the quartz benchmark peak. The integral area of the main peak or the corrected integral area of the target peak for calcium carbonate. This is the relative intensity factor.
[0042] For example, suppose 25,000 units The mass percentage of calcium carbonate is 12280.8 units; K is a constant pre-calibrated by measuring a series of standard samples with known calcium carbonate content, and its value is 2.15. The mass percentage of calcium carbonate is calculated using the formula. It is 18.60%.
[0043] The implementation principle of the X-ray diffraction-based method for detecting calcium carbonate content in artificial quartz is as follows: First, by introducing and calculating the independence coefficients of each characteristic peak, this invention effectively reduces analytical interference caused by overlapping diffraction peaks in the phase matrix. Second, this invention innovatively proposes a structural complexity parameter to quantify the complexity of the peak shape, and adaptively adjusts the width of the analytical diffraction angle window based on this parameter, thereby ensuring the accuracy of peak area integration. Furthermore, for asymmetric peak shapes caused by factors such as lattice distortion, this invention employs continuous wavelet transform technology for quantitative evaluation, and corrects the area of the target peak based on the evaluation results. Through this series of improvements in characteristic peak selection, integration interval optimization, and peak shape distortion correction, this invention can overcome the negative impact of peak overlap and peak shape distortion on quantitative analysis in complex matrix samples.
[0044] An embodiment of the X-ray diffraction-based artificial quartz calcium carbonate content detection system provided by the present invention includes a memory and a processor. The memory stores computer instructions, and when the processor executes the computer instructions, it implements the X-ray diffraction-based artificial quartz calcium carbonate content detection method in the above embodiment.
[0045] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.
Claims
1. A method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction, characterized in that, include: X-ray diffraction pattern data of artificial quartz samples were obtained, including diffraction angles and intensities. Multiple characteristic diffraction peaks of quartz and calcium carbonate were pre-defined in the pattern data. The ratio of peak intensity to the sum of signal intensities within the initial diffraction angle window of each characteristic diffraction peak was calculated to obtain the initial independence coefficient. The characteristic diffraction peak of calcium carbonate with the largest initial independence coefficient was selected as the initial target peak. The peak shape profile of the initial target peak was fitted, and the ratio of the sum of the integral areas of the shoulder peaks to the integral area of the main peak was calculated to obtain the structural complexity parameters, including: A nonlinear least squares method is employed, using a model composed of the superposition of three pseudo-Voigt functions to model the initial target peak with the 2θ angle position of the initial target peak as the center. Fit the peak shape profile within the range; Among the three pseudo-Voigt functions obtained by fitting, the one with the highest peak diffraction intensity is defined as the main peak, and the other two are defined as shoulder peaks. Calculate the sum of the areas of the shoulder peak integrals of the two shoulder peak functions, then calculate the area of the main peak integral of the main peak function, and divide the sum of the areas of the shoulder peak integrals by the area of the main peak integral to obtain the structural complexity parameter. The analytical diffraction angle window for each characteristic diffraction peak is determined based on the structural complexity parameter, including: Using formula Calculate the total width of the diffraction angle window. , This is a structural complexity parameter; When calculated When the angle is less than 0.6°, take Equal to 0.6°; Centered on the 2θ angle position of each characteristic diffraction peak, with Using the radius, determine the analytical diffraction angle window for each characteristic diffraction peak; Within each analytical diffraction angle window, the independence coefficients are recalculated. The quartz characteristic diffraction peak with the largest independence coefficient is selected as the reference peak, and the calcium carbonate characteristic diffraction peak with the largest independence coefficient is selected as the target peak. Based on the peak shape profile of the target peak, wavelet coefficients at the second and third scales are extracted using continuous wavelet transform. The energy integral ratio of the wavelet coefficients on both sides of the peak point of the target peak is calculated to obtain the asymmetric distortion coefficient. The peak shape profiles of the target peak and the reference peak are fitted respectively to obtain their respective main peak integral areas. When the structural complexity parameter is not lower than the first preset threshold, the main peak integral area of the target peak is corrected using the asymmetric distortion coefficient to obtain the corrected integral area. Based on the main peak integral area or the corrected integral area of the target peak, and the main peak integral area of the reference peak, the calcium carbonate content is calculated.
2. The method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction according to claim 1, characterized in that, The method of pre-setting multiple characteristic diffraction peaks for quartz and calcium carbonate in the spectral data includes: The diffraction peaks at 2θ angles of 20.86° and 26.64° of quartz were pre-defined as characteristic diffraction peaks of quartz. The diffraction peaks of calcium carbonate at 2θ angles of 29.42°, 39.43°, and 47.54° are preset as characteristic diffraction peaks of calcium carbonate; the initial diffraction angle window for each characteristic diffraction peak is set to a range of 1.0° plus or minus 1θ angle position.
3. The method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction according to claim 2, characterized in that, The process involves calculating the ratio of peak intensity to the sum of signal intensities within the initial diffraction angle window of each characteristic diffraction peak to obtain the initial independence coefficient. The calcium carbonate characteristic diffraction peak with the largest initial independence coefficient is selected as the initial target peak. This includes: Within each initial diffraction angle window, the maximum diffraction intensity among the data points is taken as the peak intensity. The diffraction intensities of all data points are summed to obtain the total signal intensity. The ratio of the peak intensity to the total signal intensity is calculated to obtain the initial independence coefficient. By comparing the initial independence coefficients of the characteristic diffraction peaks of calcium carbonate, the characteristic diffraction peak of calcium carbonate with the largest initial independence coefficient is determined as the initial target peak.
4. The method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction according to claim 1, characterized in that, The peak shape profile based on the target peak is obtained by extracting wavelet coefficients at the second and third scales using continuous wavelet transform, calculating the energy integral ratio of the wavelet coefficients on both sides of the peak point of the target peak, and obtaining the asymmetric distortion coefficients, including: Symlets4 was selected as the mother wavelet function, and continuous wavelet transform was performed on the peak shape profile of the target peak within the analysis diffraction angle window to obtain the wavelet coefficient sequence at the second scale and the wavelet coefficient sequence at the third scale, respectively. Taking the 2θ angle position corresponding to the peak diffraction intensity of the target peak as the center point, the sum of the squares of all wavelet coefficients to the left of the center point within the analysis diffraction angle window is taken as the left energy integral, and the sum of the squares of all wavelet coefficients to the right is taken as the right energy integral. The left-side energy integral at the second scale is added to the left-side energy integral at the third scale to obtain the total left-side energy integral; the right-side energy integral at the second scale is added to the right-side energy integral at the third scale to obtain the total right-side energy integral; the ratio of the total right-side energy integral to the total left-side energy integral is calculated to obtain the asymmetric distortion coefficient.
5. The method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction according to claim 1, characterized in that, When the structural complexity parameter is not lower than a first preset threshold, the integral area of the main peak of the target peak is corrected using an asymmetric distortion coefficient to obtain the corrected integral area, including: When the structural complexity parameter is greater than or equal to the first preset threshold, the corrected integral area is calculated using the following formula. : ； in, The integral area of the main peak of the target peak. The asymmetric distortion coefficient.
6. The method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction according to claim 1, characterized in that, The process of fitting the peak profiles of the target peak and the reference peak to obtain their respective main peak integral areas includes: Linear background subtraction is performed on the data of the target peak and the reference peak within their respective analysis diffraction angle windows; The Levenberg-Marquardt algorithm was used to fit the peak profile after background subtraction using pseudo-Voigt function with peak height, peak position, full width at half maximum and Gauss-Lorentz mixing ratio as parameters. Based on the optimal parameters obtained from the fitting, the integral area of the main peak is calculated by performing analytical integration on the pseudo-Voigt function.
7. The method for detecting calcium carbonate content in artificial quartz based on X-ray diffraction according to claim 1, characterized in that, The calculation of calcium carbonate content based on the integral area of the main peak of the target peak or the corrected integral area, and the integral area of the main peak of the reference peak includes: The mass percentage of calcium carbonate was calculated using an adiabatic model. The calculation formula is: ； in, This represents the integral area of the main peak of the quartz benchmark peak. The integral area of the main peak or the corrected integral area of the target peak for calcium carbonate. This is the relative intensity factor.
8. A system for detecting calcium carbonate content in artificial quartz based on X-ray diffraction, characterized in that, It includes a memory and a processor. The memory stores computer instructions. When the processor executes the computer instructions, it implements the method for detecting the calcium carbonate content of artificial quartz based on X-ray diffraction as described in any one of claims 1-7.