A method and system for rapid detection of heavy metals in traditional Chinese medicines

Abstract

This application relates to the technical field of heavy metal detection, and specifically relates to a method and system for rapidly detecting heavy metals in Chinese medicinal materials. The method includes: respectively collecting the X-ray fluorescence spectral curves of the honeysuckle to be tested and the honeysuckle sample, which are sequentially recorded as the spectral curve to be tested and the standard spectral curve; determining the peak position difference and contour difference of each characteristic peak in the spectral curve to be tested; obtaining the peak shape variation degree of each characteristic peak in the spectral curve to be tested; determining the peak bottom energy difference of each characteristic peak in the spectral curve to be tested; obtaining the abnormal correction coefficient of each characteristic peak in the spectral curve to be tested; obtaining the difference between the measured value and the true value of the heavy metal content in the honeysuckle with known heavy metal content, which is recorded as the measurement difference, and based on the correlation relationship between the measurement difference and the abnormal correction coefficient, determining the actual content of each heavy metal element in the honeysuckle to be tested. Thus, the accuracy of measuring the heavy metal element content in the honeysuckle to be tested is improved.

Description

Technical Field

[0001] This application relates to the technical field of heavy metal detection, and specifically relates to a method and system for rapidly detecting heavy metals in Chinese herbal medicines. Background Art

[0002] Heavy metal pollution is one of the common quality problems in Chinese herbal medicines. It may originate from soil pollution, air pollution, the use of pesticides or fertilizers, or even enter during the processing through improper operations. The excessive accumulation of heavy metals may cause serious harm to human health. Therefore, the accurate detection of heavy metal content in Chinese herbal medicines is particularly important.

[0003] At present, as a non-destructive detection method, X-ray fluorescence spectrometry can rapidly detect the concentration level of heavy metals in Chinese herbal medicines. However, due to the influence of various physical factors, such as temperature, pressure, electromagnetic field, etc., it is easy to cause baseline drift of the X-ray fluorescence spectrum during the detection process, and then the content of heavy metal elements detected in Chinese herbal medicines is quite different from the actual content. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a method and system for rapidly detecting heavy metals in Chinese herbal medicines, and the specific technical solutions adopted are as follows:

[0005] In the first aspect, an embodiment of this application provides a method for rapidly detecting heavy metals in Chinese herbal medicines, and this method includes the following steps:

[0006] Collect the X-ray fluorescence spectrum curves of the Chinese herbal medicine honeysuckle to be tested and the honeysuckle sample, and record them as the spectrum curve to be tested and the standard spectrum curve in sequence;

[0007] Form each pair of characteristic peaks from the characteristic peaks at the same position in the spectrum curve to be tested and the standard spectrum curve; analyze the difference in peak position between each pair of characteristic peaks to determine the peak position difference of each characteristic peak in the spectrum curve to be tested; analyze the difference in shape symmetry between each pair of characteristic peaks to determine the contour difference of each characteristic peak in the spectrum curve to be tested; combine the peak position difference and the contour difference to determine the peak shape variation degree of each characteristic peak in the spectrum curve to be tested;

[0008] Record the difference between the energy intensity at the bottom of the left peak and the energy intensity at the bottom of the right peak of each characteristic peak as the energy intensity difference. Based on the degree of difference in the energy intensity difference between each pair of characteristic peaks, determine the peak bottom energy difference of each characteristic peak in the spectrum curve to be tested; analyze the influence degree of carbon elements in the Chinese herbal medicine honeysuckle to be tested on the detection of its heavy metal element content, and combine the peak shape variation degree, the peak bottom energy difference, and the difference in peak shape width between each pair of characteristic peaks to determine the abnormal correction coefficient of each characteristic peak in the spectrum curve to be tested;

[0009] Obtain the difference between the measured value and the true value of the heavy metal content in honeysuckle with known heavy metal content, which is denoted as the measurement difference. Obtain the abnormal correction coefficient of the corresponding characteristic peak of each heavy metal element in the honeysuckle with known heavy metal content. Based on the correlation between the measurement difference and the abnormal correction coefficient of the corresponding characteristic peak, determine the actual content of each heavy metal element in the to-be-detected honeysuckle.

[0010] In one embodiment, the determination process of the peak position difference includes: obtaining the abscissa corresponding to the peak value of each characteristic peak in the X-ray fluorescence spectrum curve, and the peak position difference is the absolute value of the difference of the abscissa between each pair of characteristic peaks.

[0011] In one embodiment, the calculation method of the profile difference is as follows:

[0012] ; where is the profile difference of the i-th characteristic peak in the to-be-detected spectrum curve, is the horizontal distance between the k-th data point on the left side of the peak value and the peak value of the i-th characteristic peak in the to-be-detected spectrum curve, is the horizontal distance between the k-th data point on the right side of the peak value and the peak value of the i-th characteristic peak in the to-be-detected spectrum curve, is the minimum value of the number of data points included on both sides of the peak value of the i-th characteristic peak in the to-be-detected spectrum curve, is the horizontal distance between the l-th data point on the left side of the peak value and the peak value of the i-th characteristic peak in the standard spectrum curve, is the horizontal distance between the l-th data point on the right side of the peak value and the peak value of the i-th characteristic peak in the standard spectrum curve, is the minimum value of the number of data points included on both sides of the peak value of the i-th characteristic peak in the standard spectrum curve.

[0013] In one embodiment, the peak shape variation degree is the fusion result of the absolute value of the profile difference of each characteristic peak in the to-be-detected spectrum curve and the peak position difference.

[0014] In one embodiment, the peak bottom energy difference is the absolute value of the difference of the energy intensity difference between each pair of characteristic peaks.

[0015] In one embodiment, the determination of the influence degree of carbon element in the to-be-detected honeysuckle on the detection of its heavy metal element content includes:

[0016] Obtain the difference between the measured value and the true value of the heavy metal content in multiple honeysuckles, respectively obtain the carbon element content in the multiple honeysuckles, and fit the carbon element content in all honeysuckles with the difference of each heavy metal content to obtain the fitting curve corresponding to each heavy metal content;

[0017] Based on the carbon element content in the honeysuckle to be measured and the fitting curve, determine the difference corresponding to the heavy metal content in the honeysuckle to be measured, which is denoted as the influence degree of carbon element in the honeysuckle to be measured on the detection of its heavy metal element content.

[0018] In one embodiment, the calculation method of the abnormal correction coefficient is as follows:

[0019] ; in the formula, is the abnormal correction coefficient of the i-th characteristic peak in the spectral curve to be measured, is the influence degree of the heavy metal element corresponding to the i-th characteristic peak in the spectral curve to be measured, is the energy difference at the bottom of the i-th characteristic peak in the spectral curve to be measured, is the degree of abnormal change in the peak shape of the i-th characteristic peak in the spectral curve to be measured, is the width of the bottom of the i-th characteristic peak in the spectral curve to be measured, is the width of the bottom of the i-th characteristic peak in the standard spectral curve.

[0020] In one embodiment, the determination of the actual content of each heavy metal element in the honeysuckle to be measured includes:

[0021] Perform curve fitting on the abnormal correction coefficient of each characteristic peak in the X-ray fluorescence spectral curves of the multiple honeysuckles and the measurement difference of the heavy metal corresponding to the characteristic peak to obtain an error curve corresponding to each heavy metal element;

[0022] Based on the abnormal correction coefficient of each characteristic peak in the spectral curve to be measured and the error curve, obtain the measurement error value of the heavy metal element corresponding to each characteristic peak in the spectral curve to be measured, and combine the measurement value of the heavy metal element corresponding to each characteristic peak in the spectral curve to be measured to obtain the actual content of each heavy metal element in the honeysuckle to be measured.

[0023] In one embodiment, the actual content of each heavy metal element in the honeysuckle to be measured is the difference between the measurement value of the heavy metal element corresponding to each characteristic peak in the spectral curve to be measured and its measurement error value.

[0024] In a second aspect, an embodiment of the present application further provides a system for quickly detecting heavy metals in traditional Chinese medicinal materials, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0025] The present application has at least the following beneficial effects:

[0026] In this application, the X-ray fluorescence spectral curves of the honeysuckle to be measured and the honeysuckle sample are collected respectively, and are denoted as the spectral curve to be measured and the standard spectral curve in sequence; the characteristic peaks with the same sequence number in the spectral curve to be measured and the standard spectral curve are combined to form each pair of characteristic peaks; the differences in the peak positions between each pair of characteristic peaks are analyzed to determine the peak position differences of each characteristic peak in the spectral curve to be measured; the peak position difference reflects the degree of deviation of the position of each characteristic peak in the spectral curve to be measured, and reflects the degree of influence of the spectral curve to be measured by baseline drift; the differences in the shape symmetry between each pair of characteristic peaks are analyzed to determine the profile differences of each characteristic peak in the spectral curve to be measured; the profile difference reflects the degree of deformation of each characteristic peak in the spectral curve to be measured; combining the peak position difference and the profile difference, the peak shape variation degree of each characteristic peak in the spectral curve to be measured is determined; the peak shape variation degree generally reflects the overall deviation degree of the characteristic peaks in the spectral curve to be measured caused by the influence of baseline drift, and improves the accuracy of the analysis of the influence degree of baseline drift on the spectral curve to be measured; further, the differences between the energy intensities at the bottom of the left peak and the energy intensities at the bottom of the right peak of each characteristic peak are analyzed, denoted as the energy intensity difference, and based on the difference degree of the energy intensity differences between each pair of characteristic peaks, the peak bottom energy difference of each characteristic peak in the spectral curve to be measured is determined; the peak bottom energy difference reflects the difference in the energy intensities at the bottom of the characteristic peaks with the same sequence number in the spectral curve to be measured and the standard spectral curve, and the greater the difference, the more serious the influence of the characteristic peaks in the spectral curve to be measured by baseline drift; the influence degree of carbon elements in the honeysuckle to be measured on the detection of heavy metal element contents is analyzed, and combining the peak shape variation degree, the peak bottom energy difference, and the differences in the peak widths between each pair of characteristic peaks, the abnormal correction coefficient of each characteristic peak in the spectral curve to be measured is determined; the abnormal correction coefficient integrates the multi-faceted and multi-angle comparison differences of the characteristic peaks in the spectral curve to be measured, and improves the accuracy of quantifying the degree of interference of the characteristic peaks; the difference between the measured value and the true value of the heavy metal content in the honeysuckle with known heavy metal content is obtained, denoted as the measurement difference, and based on the correlation between the measurement difference and the abnormal correction coefficient, the actual contents of each heavy metal element in the honeysuckle to be measured are determined, avoiding the measurement error of the heavy metal element contents in the honeysuckle to be measured caused by the influence of baseline drift, and improving the measurement accuracy of the heavy metal element contents in the honeysuckle to be measured. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following described drawings are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0028] Figure 1 It is a flowchart of the steps of a method for rapidly detecting heavy metals in traditional Chinese medicinal materials provided by an embodiment of this application;

[0029] Figure 2 It is a flowchart for determining the abnormal correction coefficient. Specific implementation manners

[0030] In order to further elaborate on the technical means and effects adopted by this application to achieve the predetermined invention purpose, the following combines the accompanying drawings and preferred embodiments to elaborate in detail on a method and system for rapidly detecting heavy metals in Chinese herbal medicines proposed according to this application, its specific implementation manners, structures, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0032] The following specifically describes the specific solutions of a method and system for rapidly detecting heavy metals in Chinese herbal medicines provided by this application in conjunction with the accompanying drawings.

[0033] Please refer to Figure 1 , which shows a flowchart of the steps of a method for rapidly detecting heavy metals in Chinese herbal medicines provided by an embodiment of this application. The method includes the following steps:

[0034] S1, respectively collect the X-ray fluorescence spectral curves of the honeysuckle to be tested and the honeysuckle sample, and record them as the spectral curve to be tested and the standard spectral curve in sequence.

[0035] Taking the honeysuckle in Chinese herbal medicines as an example in this application, the content of heavy metal elements in the honeysuckle is detected. Specifically: record the honeysuckle that needs to be detected for the content of heavy metal elements as the honeysuckle to be tested, wipe the surface of the honeysuckle to be tested with clean water to remove the dirt and impurities on the surface, place the cleaned honeysuckle to be tested at room temperature for natural drying, and use an energy dispersive X-ray fluorescence spectrometer to collect the X-ray fluorescence spectral data of the processed honeysuckle to be tested at a tube voltage of 35 keV, a current of 40 μA, and a time of 90 s, and record it as the spectral curve to be tested; at the same time, obtain the X-ray fluorescence spectral curve of the honeysuckle sample without interference and accurate measurement, and record it as the standard spectral curve.

[0036] In this embodiment, the length of the X-ray fluorescence spectral data is N, N = 2048. The median filtering algorithm is used to filter the spectral curve to be tested to reduce the influence of environmental noise and instrument noise on the spectral data. It should be noted that the median filtering algorithm is a well-known existing technology, and the implementer can select other feasible filtering algorithms according to the actual situation, such as Gaussian filtering, Kalman filtering, etc. This embodiment does not limit this here.

[0037] S2. Form each pair of characteristic peaks by using the characteristic peaks at the same sequence positions in the spectral curve to be measured and the standard spectral curve; analyze the differences in peak positions between each pair of characteristic peaks to determine the peak position differences of the characteristic peaks in the spectral curve to be measured; analyze the differences in shape symmetry between each pair of characteristic peaks to determine the profile differences of the characteristic peaks in the spectral curve to be measured; combine the peak position differences and the profile differences to determine the peak shape variation degrees of the characteristic peaks in the spectral curve to be measured.

[0038] For X-ray fluorescence spectral data, each characteristic peak therein represents an element. In the X-ray fluorescence spectral curve graph, the horizontal axis represents energy and the vertical axis represents energy intensity. However, when baseline drift occurs in the detected X-ray fluorescence spectral curve, the baseline drift will cause changes in the shape and characteristics of the X-ray fluorescence spectral curve. Ideally, the positions of the characteristic peaks in the X-ray fluorescence spectral curve are fixed. However, the baseline drift will cause the positions of the characteristic peaks to shift. Secondly, the baseline drift will also cause slight up and down fluctuations in the collected X-ray fluorescence spectral curve, thereby causing changes in the intensities of the characteristic peaks and resulting in inaccurate detection results of the heavy metal element contents.

[0039] In the collected X-ray fluorescence spectral curve, since the atomic structure and electron arrangement of the same heavy metal element are fixed, the positions of the characteristic peaks corresponding to the same element in the X-ray fluorescence spectral curve are fixed. Therefore, in this embodiment, the influence degree of baseline drift on each characteristic peak in the spectral curve to be measured is evaluated by comparing the characteristic differences of the characteristic peaks at the same sequence positions in the spectral curve to be measured and the standard spectral curve.

[0040] Based on the above analysis, compared with the standard spectral curve, calculate the peak position differences of the characteristic peaks in the spectral curve to be measured. The specific calculation method is as follows:

[0041] ; where represents the peak position difference of the i-th characteristic peak in the spectral curve to be measured, represents the abscissa corresponding to the peak position of the i-th characteristic peak in the spectral curve to be measured, represents the abscissa corresponding to the peak position of the i-th characteristic peak in the standard spectral curve.

[0042] Secondly, for the characteristic peaks corresponding to the same heavy metal element, their shapes should be consistent in the X-ray fluorescence spectral curve. However, due to the influence of baseline drift, the shapes of the characteristic peaks in the spectral curve to be measured usually change. Therefore, in this embodiment, the influence of baseline drift is evaluated by comparing the shape characteristic differences of the corresponding characteristic peaks in the spectral curve to be measured and the standard spectral curve.

[0043] Ideally, the shape of the characteristic peaks in the spectral curve is symmetric left and right. However, baseline drift will cause the shape of the characteristic peaks to change, that is, the symmetry of the characteristic peak shape is destroyed. Therefore, in this embodiment, the symmetric zero-area transformation method is used to extract each characteristic peak in the spectral curve to be measured and the standard spectral curve. The symmetric zero-area transformation method is a well-known existing technology and will not be elaborated in detail here. Secondly, the characteristic peaks with the same sequence number in the spectral curve to be measured and the standard spectral curve are recorded as each pair of characteristic peaks. For example, the first characteristic peak in the spectral curve to be measured and the first characteristic peak in the standard spectral curve are recorded as a pair of characteristic peaks, and the second characteristic peak in the spectral curve to be measured and the second characteristic peak in the standard spectral curve are also recorded as a pair of characteristic peaks, and so on, to obtain each pair of characteristic peaks in the spectral curve to be measured and the standard spectral curve.

[0044] Furthermore, analyze the symmetry difference between each pair of characteristic peaks to determine the contour difference of each characteristic peak in the spectral curve to be measured. The specific calculation method is as follows:

[0045] ; where is the contour difference of the i-th characteristic peak in the spectral curve to be measured, is the horizontal distance between the k-th data point on the left side of the peak of the i-th characteristic peak in the spectral curve to be measured and the peak, is the horizontal distance between the k-th data point on the right side of the peak of the i-th characteristic peak in the spectral curve to be measured and the peak, is the minimum value of the number of data points included on both sides of the peak of the i-th characteristic peak in the spectral curve to be measured, is the horizontal distance between the l-th data point on the left side of the peak of the i-th characteristic peak in the standard spectral curve and the peak, is the horizontal distance between the l-th data point on the right side of the peak of the i-th characteristic peak in the standard spectral curve and the peak, is the minimum value of the number of data points included on both sides of the peak of the i-th characteristic peak in the standard spectral curve.

[0046] It should be noted that the horizontal distance between the k-th data point and the peak is the absolute value of the difference between the abscissa of the k-th data point and the abscissa corresponding to the peak. In this embodiment, the horizontal distance is calculated using this method, and the serial numbers of the data points on both sides of the peak are set in ascending order according to the horizontal distance from the peak from near to far.

[0047] Combining the peak position difference and the profile difference of each characteristic peak in the spectral curve to be measured, determine the peak shape variation degree of each characteristic peak in the spectral curve to be measured, where the peak shape variation degree is the fusion result of the absolute value of the profile difference and the peak position difference of each characteristic peak in the spectral curve to be measured. It should be noted that fusion means combining multiple variables, and specifically, calculations can be performed in ways such as multiplication, addition, or a combination of addition and multiplication. In this embodiment, multiplication is used as the calculation method for fusion.

[0048] In this embodiment, the specific calculation method of the peak shape variation degree is as follows:

[0049] ; where, represents the peak position difference of the i-th characteristic peak in the spectral curve to be measured, is the profile difference of the i-th characteristic peak in the spectral curve to be measured, is the peak shape variation degree of the i-th characteristic peak in the spectral curve to be measured.

[0050] It should be understood that when the spectral curve to be measured has a baseline drift, the more severe the baseline drift in the spectral curve to be measured, the greater the calculated peak position difference of the characteristic peaks in the spectral curve to be measured; at the same time, the baseline drift will also cause a change in the shape of the characteristic peaks in the spectral curve to be measured. The more severe the baseline drift, the greater the difference in the horizontal distance between the data points on both sides of the characteristic peak and the peak value, indicating that the symmetry of the characteristic peak is worse, and further making the calculated absolute value of the profile difference of the characteristic peaks in the spectral curve to be measured larger, indicating that the shape of the characteristic peak is more affected by the baseline drift; finally, the greater the calculated shape difference between the spectral curve to be measured and the corresponding characteristic peaks in the standard spectral curve, that is, the greater the peak shape variation degree of the characteristic peaks in the spectral curve to be measured.

[0051] S3. Analyze the difference between the left peak bottom energy intensity and the right peak bottom energy intensity of each characteristic peak, denoted as the energy intensity difference, and determine the peak bottom energy difference of each characteristic peak in the spectral curve to be measured based on the degree of difference in the energy intensity difference between each pair of characteristic peaks; analyze the influence degree of carbon elements in the honeysuckle to be measured on the detection of its heavy metal element content, and combine the peak shape variation degree, the peak bottom energy difference, and the difference in the peak shape width between each pair of characteristic peaks to determine the abnormal correction coefficient of each characteristic peak in the spectral curve to be measured.

[0052] Ideally, the shapes on both sides of the peak value of the characteristic peak in the X-ray fluorescence spectral curve are symmetric. However, due to the influence of baseline drift, the shape of the characteristic peak in the X-ray fluorescence spectral curve will change, and the change in the shape of the characteristic peak will further affect the width of the peak bottom of the characteristic peak. The greater the change in the shape of the characteristic peak, that is, the peak shape variation degree The greater it is, the greater the difference between the width of the bottom of the characteristic peak in the spectral curve to be measured and the width of the bottom of the corresponding characteristic peak in the standard spectral curve. Therefore, in this embodiment, the abnormal change in the width of the bottom of the characteristic peak caused by the change in the shape of the characteristic peak in the spectral curve to be measured is further analyzed.

[0053] In addition, baseline drift will also cause the characteristic peaks at different positions in the spectral curve to be measured to drift up and down. Under ideal conditions, for the characteristic peaks corresponding to the same heavy metal element in the X-ray fluorescence spectral curve, although the content of the heavy metal element is different, the bottom of the characteristic peak corresponding to the heavy metal element is consistent, that is, the content of the heavy metal will not change the energy intensity and the width of the bottom of the characteristic peak.

[0054] Based on the above analysis, calculate the energy difference at the bottom of each characteristic peak in the spectral curve to be measured. The specific calculation method is as follows:

[0055] ; where is the energy difference at the bottom of the i-th characteristic peak in the spectral curve to be measured, is the energy intensity of the bottom on the left side of the peak value of the i-th characteristic peak in the spectral curve to be measured, is the energy intensity of the bottom on the right side of the peak value of the i-th characteristic peak in the spectral curve to be measured, is the energy intensity of the bottom on the left side of the peak value of the i-th characteristic peak in the standard spectral curve, is the energy intensity of the bottom on the right side of the peak value of the i-th characteristic peak in the standard spectral curve. Denote , both as the energy intensity difference.

[0056] It should be noted that the bottom of the peak represents the data points corresponding to the minimum energy intensity on both the left and right sides of the peak value among the data points constituting the characteristic peak.

[0057] The energy difference at the bottom of each characteristic peak in the spectral curve to be measured reflects the difference in the energy intensity at the bottom of the characteristic peaks with the same ordinal position in the spectral curve to be measured and the standard spectral curve. The greater the difference, the more severely the characteristic peak in the spectral curve to be measured is affected by baseline drift.

[0058] There is a large amount of carbon element in honeysuckle. However, the carbon element has a significant absorption coefficient in honeysuckle, that is, different carbon element contents in honeysuckle will cause the X-ray energy intensity of heavy metal elements in the honeysuckle to be measured to be absorbed to different degrees, thereby affecting the detection accuracy of the heavy metal element content in honeysuckle. Therefore, in this embodiment, the influence of the carbon element content in honeysuckle on the detection accuracy of heavy metal element content is further analyzed.

[0059] Specifically, in this embodiment, for M honeysuckles with known heavy metal element contents, an energy dispersive X-ray fluorescence spectrometer is used to obtain the measured values of the heavy metal element contents in these M honeysuckles, and the difference between the measured values and the true values of the heavy metal element contents in these M honeysuckles is calculated, denoted as the measurement difference. Secondly, the infrared absorption method is used to obtain the carbon element content in these M honeysuckles respectively. For any heavy metal element, the measurement differences of it in the M honeysuckles and the carbon element contents in the M honeysuckles are respectively formed into a two-dimensional array, and the least squares method is used to fit all the two-dimensional arrays of the any heavy metal element to obtain the fitting curve corresponding to the any heavy metal element. Among them, the abscissa is the carbon element content in each honeysuckle, and the ordinate is the measurement difference corresponding to the any heavy metal element in each honeysuckle. The fitting curve is used as the influence curve of the carbon element content in the honeysuckle on the detection accuracy of the any heavy metal element. The influence curves corresponding to each heavy metal element in the honeysuckle are obtained by the same method as the influence curve. Among them, the infrared absorption method and using the energy dispersive X-ray fluorescence spectrometer to obtain the heavy metal element contents in the honeysuckle are both well-known prior arts and will not be elaborated in detail here; the least squares method for curve fitting is a well-known prior art, and the implementer can choose other existing feasible curve fitting algorithms according to the actual situation, which will not be elaborated in detail in this embodiment. In this embodiment, M = 100, and the implementer can set it by himself according to the actual situation, and this embodiment does not limit it here.

[0060] The infrared absorption method is used to detect the carbon element content in the to-be-detected honeysuckle. For the any heavy metal element, the carbon element content in the to-be-detected honeysuckle is used as the independent variable of the influence curve of the any heavy metal element, and the corresponding dependent variable is obtained as the influence degree of the carbon element in the to-be-detected honeysuckle on the content detection of the any heavy metal element.

[0061] Furthermore, based on the influence degree of the carbon element in the to-be-detected honeysuckle on the detection of its heavy metal element content, combined with the peak shape variation degree, the peak bottom energy difference, and the difference in the peak shape width between each pair of characteristic peaks, the abnormal correction coefficient of each characteristic peak in the to-be-detected spectral curve is determined. The specific calculation method is as follows:

[0062] ; In the formula, is the abnormal correction coefficient of the i-th characteristic peak in the to-be-detected spectral curve, is the influence degree of the heavy metal element corresponding to the i-th characteristic peak in the to-be-detected spectral curve, is the peak bottom energy difference of the i-th characteristic peak in the to-be-detected spectral curve, is the peak shape variation degree of the i-th characteristic peak in the to-be-detected spectral curve, is the width of the peak bottom of the i-th characteristic peak in the to-be-detected spectral curve, is the width at the bottom of the i-th characteristic peak in the standard spectral curve.

[0063] It should be noted that the width at the bottom of the characteristic peak is the absolute value of the difference in the abscissas between the starting position on the left and the starting position on the right of the characteristic peak.

[0064] It should be understood that due to the influence of baseline drift, compared with the standard spectral curve, the greater the difference in the energy intensity at the bottom of the characteristic peak in the spectral curve to be measured, the greater the difference in the width at the bottom of the characteristic peak, and the greater the absolute value of the degree of influence of the heavy metal element corresponding to the characteristic peak by the carbon element content, all indicating that the degree of interference on the characteristic peak is more serious, and the possibility of the characteristic peak being abnormal is greater, which in turn affects the calculated abnormal correction coefficient. The flowchart for determining the abnormal correction coefficient is as Figure 2 shown.

[0065] S4. Based on the correlation between the measurement difference and the abnormal correction coefficient, determine the actual content of each heavy metal element in the honeysuckle to be measured.

[0066] Each characteristic peak in the spectral curve to be measured corresponds to a heavy metal element. Based on the above analysis, according to the abnormal correction coefficient of each characteristic peak in the spectral curve to be measured, correct the content of the heavy metal element corresponding to each characteristic peak in the spectral elements to be measured.

[0067] Specifically: For M honeysuckles with known heavy metal element contents, adopt the same calculation method for the abnormal correction coefficients of each characteristic peak in the above-mentioned spectral curve to be measured, obtain the abnormal correction coefficients of each characteristic peak in the X-ray fluorescence spectral curves of the M honeysuckles. Similarly, taking any one of the heavy metal elements as an example, form two-dimensional data points with the abnormal correction coefficient of the characteristic peak corresponding to the any one of the heavy metal elements in the X-ray fluorescence spectral curve of any one of the honeysuckles and the measurement difference of the any one of the heavy metal elements in the any one of the honeysuckles, and perform curve fitting on the two-dimensional data points of the any one of the heavy metal elements in the M honeysuckles by using the least squares method to obtain the error curve of the any one of the heavy metal elements, where, during the fitting process, the abnormal correction coefficient is used as the abscissa and the measurement difference of the heavy metal element in the honeysuckle is used as the ordinate.

[0068] Based on the spectral curve to be measured of the honeysuckle to be measured, obtain the measured values of the contents of each heavy metal element in the honeysuckle to be measured. Substitute the abnormal correction coefficients of the characteristic peaks corresponding to each heavy metal element in the spectral curve to be measured of the honeysuckle to be measured as independent variables into the error curve of the corresponding heavy metal element to obtain the measurement error values of the contents of each heavy metal element in the honeysuckle to be measured. The measurement error value is the measurement difference. Calculate the difference between the measured value of the content of each heavy metal element in the honeysuckle to be measured and its measurement error value as the actual content of each heavy metal element in the honeysuckle to be measured.

[0069] Based on the same inventive concept as the above method, an embodiment of the present application further provides a system for rapidly detecting heavy metals in traditional Chinese medicine, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above methods for rapidly detecting heavy metals in traditional Chinese medicine are implemented.

[0070] It should be noted that: the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of the present specification have been described. 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, multitasking and parallel processing are also possible or may be advantageous.

[0071] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0072] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for rapid detection of heavy metals in Chinese medicinal materials, characterized in that: The method comprises the following steps: The X-ray fluorescence spectrum curves of the honeysuckle to be tested and the honeysuckle sample are collected respectively, and are recorded as the spectrum curve to be tested and the standard spectrum curve in sequence; The characteristic peaks of the same position in the spectrum curve to be measured and the standard spectrum curve are grouped into pairs of characteristic peaks; the difference in peak position between each pair of characteristic peaks is analyzed to determine the peak position difference of each characteristic peak in the spectrum curve to be measured; the difference in shape symmetry between each pair of characteristic peaks is analyzed to determine the contour difference of each characteristic peak in the spectrum curve to be measured; and the peak shape variability of each characteristic peak in the spectrum curve to be measured is determined by combining the peak position difference and the contour difference; The difference between the energy intensity of the left peak bottom and the energy intensity of the right peak bottom of each characteristic peak is recorded as the energy intensity difference, and the peak-to-base energy difference of each characteristic peak in the spectrum curve to be measured is determined based on the degree of distinction of the energy intensity difference between each pair of characteristic peaks; the influence of the carbon element in the honeysuckle to be measured on the detection of its heavy metal element content is analyzed, and the abnormal correction coefficient of each characteristic peak in the spectrum curve to be measured is determined by combining the peak shape variability, the peak-to-base energy difference, and the difference in peak shape width between each pair of characteristic peaks; Obtain the difference between the measured value and the true value of the heavy metal content in the honeysuckle with known heavy metal content, record it as the measurement difference, obtain the abnormal correction coefficient of the corresponding characteristic peak of each heavy metal element in the honeysuckle with known heavy metal content, and determine the actual content of each heavy metal element in the honeysuckle to be tested based on the correlation between the measurement difference and the abnormal correction coefficient of the corresponding characteristic peak.

2. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 1, characterized in that: The peak position difference determination process includes: obtaining the horizontal coordinate corresponding to the peak value of each characteristic peak in the X-ray fluorescence spectrum curve, and the peak position difference is the absolute value of the difference between the horizontal coordinates of each pair of characteristic peaks.

3. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 1, characterized in that: The contour difference is calculated as follows: ; In the formula, is the profile difference of the i-th characteristic peak in the spectrum curve to be measured, is the lateral distance between the kth data point on the left side of the peak of the i-th characteristic peak in the spectrum curve to be measured and the peak, is the lateral distance between the kth data point on the right side of the peak of the i-th characteristic peak in the spectrum curve to be measured and the peak, is the minimum value of the number of data points on both sides of the peak value of the i-th characteristic peak in the spectrum curve to be measured, is the lateral distance between the lth data point on the left side of the peak of the i-th characteristic peak in the standard spectrum curve and the peak, is the lateral distance between the lth data point on the right side of the peak of the i-th characteristic peak in the standard spectrum curve and the peak, It is the minimum number of data points on both sides of the peak of the i-th characteristic peak in the standard spectrum curve.

4. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 1, characterized in that: The peak shape variability is the fusion result of the absolute value of the profile difference and the peak position difference of each characteristic peak in the spectrum curve to be measured.

5. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 1, characterized in that: The peak-to-bottom energy difference is the absolute value of the difference in energy intensity between each pair of characteristic peaks.

6. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 1, characterized in that: The determination of the influence of the carbon element in the honeysuckle to be tested on the detection of the heavy metal element content thereof includes: Obtain the difference between the measured value and the true value of each heavy metal content in a plurality of honeysuckle flowers, respectively obtain the carbon content in the plurality of honeysuckle flowers, and fit the carbon content in all honeysuckle flowers with the difference between each heavy metal content to obtain a fitting curve corresponding to each heavy metal content; Based on the content of carbon in the honeysuckle to be tested and the fitting curve, the difference corresponding to the content of each heavy metal in the honeysuckle to be tested is determined, and recorded as the influence of the carbon in the honeysuckle to be tested on the detection of its heavy metal content.

7. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 1, characterized in that: The calculation method of the abnormal correction coefficient is: ; In the formula, is the abnormal correction coefficient of the i-th characteristic peak in the spectrum curve to be measured, is the influence degree of the heavy metal element corresponding to the i-th characteristic peak in the spectrum curve to be measured, is the peak-to-base energy difference of the i-th characteristic peak in the spectrum curve to be measured, is the peak shape variability of the i-th characteristic peak in the spectrum curve to be measured, is the width of the base of the i-th characteristic peak in the spectrum curve to be measured, is the width of the base of the i-th characteristic peak in the standard spectrum curve.

8. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 6, characterized in that: The determination of the actual content of each heavy metal element in the honeysuckle to be tested includes: Performing curve fitting on the abnormal correction coefficient of each characteristic peak in the X-ray fluorescence spectrum curves of the multiple honeysuckle flowers and the measured difference of the heavy metal corresponding to the characteristic peak to obtain an error curve corresponding to each heavy metal element; Based on the abnormal correction coefficient of each characteristic peak in the spectral curve to be measured and the error curve, the measurement error value of the heavy metal element corresponding to each characteristic peak in the spectral curve to be measured is obtained, and combined with the measurement value of the heavy metal element corresponding to each characteristic peak in the spectral curve to be measured, the actual content of each heavy metal element in the honeysuckle to be measured is obtained.

9. A method for rapid detection of heavy metals in Chinese medicinal materials as claimed in claim 8, characterized in that: The actual content of each heavy metal element in the honeysuckle to be tested is the difference between the measured value of the heavy metal element corresponding to each characteristic peak in the spectrum curve to be tested and the measurement error value thereof.

10. A system for rapid detection of heavy metals in traditional Chinese medicine, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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