Method and system for rapidly detecting heavy metals in traditional Chinese medicinal materials

Abstract

The invention relates to the technical field of heavy metal detection, in particular to a method and a system for rapidly detecting heavy metals in traditional Chinese medicinal materials, and the method comprises the following steps: respectively collecting X-ray fluorescence spectrum curves of to-be-detected honeysuckle and a honeysuckle sample, and sequentially recording the X-ray fluorescence spectrum curves as a to-be-detected spectrum curve and a standard spectrum curve; determining a peak position difference and a contour difference of each characteristic peak in the spectrum curve to be measured; obtaining the peak shape variation degree of each characteristic peak in the spectrum curve to be measured; determining the peak bottom energy difference of each characteristic peak in the spectrum curve to be measured; obtaining an abnormal correction coefficient of each characteristic peak in the spectrum curve to be measured; obtaining the difference between the measured value of the heavy metal content in the honeysuckle with the known heavy metal content and the real value, recording the difference as the measurement difference, and determining the actual content of each heavy metal element in the honeysuckle to be measured based on the correlation between the measurement difference and the abnormal correction coefficient. Therefore, the accuracy of measuring the content of the heavy metal elements in the to-be-measured honeysuckle is improved.

Description

Technical Field

[0001] The present application relates to the technical field of heavy metal detection, and in particular to a method and system for rapid detection of heavy metals in traditional Chinese medicines. Background Art

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

[0003] At present, X-ray fluorescence spectrometry, as a non-destructive detection method, can quickly detect the concentration level of heavy metals in traditional Chinese medicines. However, due to the influence of various physical factors, such as temperature, pressure, electromagnetic field, etc., it is easy to cause baseline drift in the X-ray fluorescence spectrum during the detection process, which in turn causes the detected content of heavy metal elements in traditional Chinese medicines to be 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 rapid detection of heavy metals in traditional Chinese medicines. The technical solutions adopted are as follows: In a first aspect, the present invention provides a method for rapid detection of heavy metals in Chinese medicinal materials, the method comprising 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; 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, which is recorded as the measurement difference. The abnormal correction coefficient of the corresponding characteristic peak of each heavy metal element in the honeysuckle with known heavy metal content is obtained. Based on the correlation between the measurement difference and the abnormal correction coefficient of the corresponding characteristic peak, the actual content of each heavy metal element in the honeysuckle to be tested is determined.

[0005] In one embodiment, 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 between each pair of characteristic peaks.

[0006] In one embodiment, 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.

[0007] In one embodiment, the peak shape variability is a 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.

[0008] In one embodiment, the peak-to-bottom energy difference is the absolute value of the difference in energy intensity between each pair of characteristic peaks.

[0009] In one embodiment, the determination of the influence of the carbon element in the honeysuckle on the detection of the heavy metal element content 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.

[0010] In one embodiment, the abnormal correction coefficient is calculated as follows: ; 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.

[0011] In one embodiment, 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.

[0012] In one embodiment, the actual content of each heavy metal element in the honeysuckle to be measured is the difference between the measured value of the heavy metal element corresponding to each characteristic peak in the spectrum curve to be measured and its measurement error value.

[0013] In a second aspect, an embodiment of the present application also provides a system for rapidly detecting heavy metals in traditional Chinese medicines, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above methods when executing the computer program.

[0014] This application has at least the following beneficial effects: The present application collects X-ray fluorescence spectrum curves of honeysuckle to be tested and honeysuckle sample respectively, and records them as the spectrum curve to be tested and the standard spectrum curve in sequence; characteristic peaks of the same position order in the spectrum curve to be tested and the standard spectrum curve are combined 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 tested; the peak position difference reflects the degree of displacement of the position of each characteristic peak in the spectrum curve to be tested, and reflects the degree to which the spectrum curve to be tested is affected by baseline drift; the difference in shape symmetry between each pair of characteristic peaks is analyzed to determine the peak position difference of each characteristic peak in the spectrum curve to be tested The profile difference of each characteristic peak in the curve; the profile difference reflects the degree of deformation of each characteristic peak in the spectral curve to be measured; the peak shape variability of each characteristic peak in the spectral curve to be measured is determined by combining the peak position difference and the profile difference; the peak shape variability generally reflects the overall deviation degree of the characteristic peak in the spectral curve to be measured caused by the influence of baseline drift, which improves the accuracy of the analysis of the influence degree of baseline drift on the spectral curve to be measured; further, the difference between the left peak bottom energy intensity and the right peak bottom energy intensity of each characteristic peak is analyzed, which is recorded as the energy intensity difference, and the energy intensity difference between each pair of characteristic peaks is calculated based on the energy intensity difference between each pair of characteristic peaks. The peak-to-base energy difference of each characteristic peak in the measured spectral curve is determined by the degree of distinction of the degree of difference; the peak-to-base energy difference reflects the difference in the peak-to-base energy intensity of the characteristic peaks of the same position in the measured spectral curve and the standard spectral curve. The greater the difference, the more serious the influence of the baseline drift on the characteristic peaks in the measured spectral curve is; the influence of the carbon element in the measured honeysuckle on the detection of its heavy metal element content is analyzed, and the abnormal correction coefficient of each characteristic peak in the measured spectral curve is determined by combining the peak shape variability, the peak-to-base 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 measured spectral curve is determined by combining the peak shape variability, the peak-to-base energy difference, and the difference in the peak shape width between each pair of characteristic peaks; the abnormal The correction coefficient integrates the multi-directional and multi-angle contrast differences of characteristic peaks in the spectral curve to be measured, thereby improving the accuracy of quantifying the degree of interference of characteristic peaks; the difference between the measured value and the true value of the heavy metal content in honeysuckle with known heavy metal content is obtained, recorded as the measurement difference, and the actual content of each heavy metal element in the honeysuckle to be measured is determined based on the correlation between the measurement difference and the abnormal correction coefficient, thereby avoiding the measurement error of the heavy metal element content in the honeysuckle to be measured caused by the influence of baseline drift, and improving the accuracy of measuring the heavy metal element content in the honeysuckle to be measured. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A flowchart of a method for rapid detection of heavy metals in traditional Chinese medicine provided in one embodiment of the present application; Figure 2 Determine the flow chart for the abnormal correction factor. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the method and system for rapid detection of heavy metals in Chinese medicinal materials proposed in accordance with the present application, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0019] The specific scheme of a method and system for rapid detection of heavy metals in traditional Chinese medicine provided by the present application is described in detail below with reference to the accompanying drawings.

[0020] See also Figure 1 , which shows a flowchart of a method for rapid detection of heavy metals in Chinese medicinal materials provided by an embodiment of the present application, the method comprising the following steps: S1, respectively collecting X-ray fluorescence spectrum curves of the honeysuckle to be tested and the honeysuckle sample, and recording them as the spectrum curve to be tested and the standard spectrum curve respectively.

[0021] This application takes honeysuckle in Chinese medicinal materials as an example to detect the content of heavy metal elements in honeysuckle, specifically: the honeysuckle that needs to be tested for heavy metal element content is recorded as honeysuckle to be tested, the surface of the honeysuckle to be tested is wiped with clean water to remove surface dirt and impurities, the cleaned honeysuckle to be tested is placed at room temperature to dry naturally, and an energy dispersive X-ray fluorescence spectrometer is used to collect the X-ray fluorescence spectrum 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, which is recorded as the spectrum curve to be tested; at the same time, the X-ray fluorescence spectrum curve of the honeysuckle sample without interference and with accurate measurement is obtained, which is recorded as the standard spectrum curve.

[0022] In this embodiment, the length of the X-ray fluorescence spectrum data is N, N=2048, and the median filtering algorithm is used to filter the spectrum curve to be measured to reduce the impact of environmental noise and instrument noise on the spectrum data. It should be noted that the median filtering algorithm is an existing well-known technology, and the implementer can choose other existing feasible filtering algorithms according to actual conditions, such as Gaussian filtering, Kalman filtering, etc., which are not limited in this embodiment.

[0023] S2, grouping characteristic peaks of the same position in the spectral curve to be measured and the standard spectral curve into pairs of characteristic peaks; analyzing the differences in peak positions between each pair of characteristic peaks to determine the peak position differences of each characteristic peak in the spectral curve to be measured; analyzing the differences in shape symmetry between each pair of characteristic peaks to determine the contour differences of each characteristic peak in the spectral curve to be measured; combining the peak position differences and the contour differences to determine the peak shape variability of each characteristic peak in the spectral curve to be measured.

[0024] For X-ray fluorescence spectrum data, each characteristic peak represents an element. In the X-ray fluorescence spectrum curve, the horizontal axis represents energy and the vertical axis represents energy intensity. However, when baseline drift occurs in the detected X-ray fluorescence spectrum curve, the baseline drift will cause the shape and characteristics of the X-ray fluorescence spectrum curve to change. Ideally, the position of the characteristic peak of the X-ray fluorescence spectrum curve is fixed, but the baseline drift will cause the position of the characteristic peak to shift. Secondly, the baseline drift will also cause the collected X-ray fluorescence spectrum curve to have slight ups and down fluctuations, which will change the intensity of the characteristic peak, resulting in the detection results of the heavy metal element content being no longer accurate.

[0025] In the collected X-ray fluorescence spectrum curve, since the atomic structure and electronic arrangement of the same heavy metal element are fixed, the position of the characteristic peak corresponding to the same element on the X-ray fluorescence spectrum curve is fixed. Therefore, this embodiment evaluates the degree of influence of baseline drift on each characteristic peak in the measured spectrum curve by comparing the characteristic differences of the characteristic peaks of the same position in the measured spectrum curve and the standard spectrum curve.

[0026] Based on the above analysis, the peak position difference of each characteristic peak in the spectrum curve to be measured is calculated by comparing the standard spectrum curve. The specific calculation method is: ; In the formula, It represents the peak position difference of the i-th characteristic peak in the spectrum curve to be measured, Indicates the horizontal coordinate corresponding to the peak position of the i-th characteristic peak in the measured spectrum curve, Represents the horizontal coordinate corresponding to the peak position of the i-th characteristic peak in the standard spectrum curve.

[0027] Secondly, the shape of the characteristic peak corresponding to the same heavy metal element should be consistent in the X-ray fluorescence spectrum curve, but due to the influence of baseline drift, the shape of the characteristic peak in the measured spectrum curve usually changes. Therefore, this embodiment evaluates the influence of baseline drift by comparing the shape characteristic difference of the corresponding characteristic peak in the measured spectrum curve and the standard spectrum curve.

[0028] In an ideal case, the shape of the characteristic peak in the spectrum curve is bilaterally symmetrical, but the baseline drift will cause the shape of the characteristic peak to change, that is, the symmetry of the characteristic peak shape is destroyed. Therefore, the present embodiment extracts the characteristic peaks in the spectrum curve to be measured and the standard spectrum curve by the symmetrical zero area transformation method. The symmetrical zero area transformation method is a known technology and will not be described in detail here. Secondly, the characteristic peaks of the same position in the spectrum curve to be measured and the standard spectrum curve are recorded as pairs of characteristic peaks. For example, the first characteristic peak in the spectrum curve to be measured and the first characteristic peak in the standard spectrum curve are recorded as a pair of characteristic peaks, and the second characteristic peak in the spectrum curve to be measured and the second characteristic peak in the standard spectrum curve are also recorded as a pair of characteristic peaks. By analogy, each pair of characteristic peaks in the spectrum curve to be measured and the standard spectrum curve is obtained.

[0029] Furthermore, the difference in symmetry between each pair of characteristic peaks is analyzed to determine the profile difference of each characteristic peak in the spectrum curve to be measured. The specific calculation method is: ; 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.

[0030] It should be noted that the lateral distance between the kth data point and the peak value is the absolute value of the difference between the horizontal coordinate of the kth data point and the horizontal coordinate corresponding to the peak value. The lateral distances in this embodiment are calculated using this method, and the serial numbers of the data points on both sides of the peak value are set in ascending order from near to far according to the lateral distance to the peak value.

[0031] The peak position difference and profile difference of each characteristic peak in the measured spectral curve are combined to determine the peak shape variability of each characteristic peak in the measured spectral curve, and the peak shape variability is the fusion result of the absolute value of the profile difference of each characteristic peak in the measured spectral curve and the peak position difference. It should be noted that fusion means combining multiple variables, which can be calculated by multiplication, addition, addition and multiplication mixture, etc. This embodiment uses multiplication as the calculation method of fusion.

[0032] In this embodiment, the specific calculation method of peak shape variability is: ; In the formula, It represents the peak position difference of the i-th characteristic peak in the spectrum curve to be measured, is the profile 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.

[0033] It should be understood that when the baseline drift occurs in the measured spectrum curve, the more serious the baseline drift in the measured spectrum curve, the greater the peak position difference of the characteristic peak in the measured spectrum curve; at the same time, the baseline drift will also cause the shape of the characteristic peak in the measured spectrum curve to change. The more serious the baseline drift, the greater the difference in the lateral 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, which in turn makes the calculated contour of the characteristic peak in the measured spectrum curve worse. The larger the absolute value of is, the greater the influence of baseline drift on the characteristic peak shape is; the greater the shape difference between the corresponding characteristic peaks in the measured spectrum curve and the standard spectrum curve is, the greater the peak shape variability of the characteristic peak in the measured spectrum curve is. The bigger.

[0034] S3, analyzing the difference between the energy intensity of the left peak bottom and the energy intensity of the right peak bottom of each characteristic peak, recording it as the energy intensity difference, and determining the peak-to-base energy difference of each characteristic peak in the spectral curve to be measured based on the degree of distinction of the energy intensity difference between each pair of characteristic peaks; analyzing the influence of the carbon element in the honeysuckle to be measured on the detection of its heavy metal element content, and combining the peak shape variability, the peak-to-base energy difference, and the difference in peak shape width between each pair of characteristic peaks, determining the abnormal correction coefficient of each characteristic peak in the spectral curve to be measured.

[0035] Ideally, the shapes of the two sides of the peak value of the characteristic peak in the X-ray fluorescence spectrum curve are symmetrical. However, due to the influence of baseline drift, the shape of the characteristic peak in the X-ray fluorescence spectrum curve will change, and the shape change of the characteristic peak will further affect the width of the base of the characteristic peak. The greater the shape change of the characteristic peak, that is, the peak shape variability of the characteristic peak The larger the value, the greater the difference between the width of the peak-to-base of the characteristic peak in the measured spectrum curve and the width of the peak-to-base of the corresponding characteristic peak in the standard spectrum curve. Therefore, this embodiment further analyzes the abnormal change of the peak-to-base width of the characteristic peak caused by the change of the shape of the characteristic peak in the measured spectrum curve.

[0036] In addition, baseline drift will also cause the characteristic peaks at different positions in the measured spectral curve to drift up and down. Under ideal circumstances, the characteristic peaks corresponding to the same heavy metal element in the X-ray fluorescence spectrum curve have the same peak base despite the different contents of the heavy metal elements. That is, the heavy metal content will not change the energy intensity and width of the peak base of the characteristic peak.

[0037] Based on the above analysis, the peak-to-base energy difference of each characteristic peak in the spectrum curve to be measured is calculated. The specific calculation method is: ; In the formula, is the peak-to-base energy difference of the i-th characteristic peak in the spectrum curve to be measured, is the energy intensity of the peak bottom on the left side of the peak value of the i-th characteristic peak in the spectrum curve to be measured, is the energy intensity of the peak bottom to the right of the peak value of the i-th characteristic peak in the spectrum curve to be measured, is the energy intensity of the peak base on the left side of the peak of the i-th characteristic peak in the standard spectrum curve, is the energy intensity of the peak bottom to the right of the peak value of the i-th characteristic peak in the standard spectrum curve. , All are recorded as energy intensity differences.

[0038] It should be noted that the peak bottom refers to the data points corresponding to the minimum energy intensity on the left and right sides of the peak among the data points constituting the characteristic peak.

[0039] The peak-to-base energy difference of each characteristic peak in the measured spectral curve reflects the difference in peak-to-base energy intensity of characteristic peaks of the same position in the measured spectral curve and the standard spectral curve. The larger the difference, the more serious the influence of baseline drift on the characteristic peaks in the measured spectral curve.

[0040] Honeysuckle contains a large amount of carbon, but carbon has a significant absorption coefficient in honeysuckle, that is, different carbon contents in honeysuckle will cause the X-ray energy intensity of the heavy metal elements in the honeysuckle to be absorbed to different degrees, thereby affecting the detection accuracy of the heavy metal content in honeysuckle. Therefore, this example further analyzes the influence of the carbon content in honeysuckle on the detection accuracy of heavy metal content.

[0041] Specifically, in this embodiment, for M honeysuckle flowers with known contents of various heavy metal elements, an energy dispersive X-ray fluorescence spectrometer is used to obtain the measured values ​​of the contents of various heavy metal elements in the M honeysuckle flowers, and the difference between the measured values ​​and the true values ​​of the contents of various heavy metal elements in the M honeysuckle flowers is calculated, which is recorded as the measurement difference. Secondly, the carbon content in the M honeysuckle flowers is obtained respectively by infrared absorption method. For any heavy metal element, the measured difference in the M honeysuckle flowers and the carbon content in the M honeysuckle flowers are respectively formed into two-dimensional arrays, and all two-dimensional arrays of the any heavy metal element are fitted by the least squares method to obtain a fitting curve corresponding to the any heavy metal element, wherein the abscissa is the carbon content in each honeysuckle flower, and the ordinate is the measurement difference corresponding to the any heavy metal element in each honeysuckle flower. The fitting curve is used as the influence curve of the carbon content in honeysuckle on the detection accuracy of the any heavy metal element, and the influence curve corresponding to each heavy metal element in the honeysuckle is obtained by the same method as the influence curve. Among them, the infrared absorption method and the use of energy dispersive X-ray fluorescence spectrometer to obtain the content of each heavy metal element in honeysuckle are both existing well-known technologies, which will not be described in detail here; the least squares method for curve fitting is an existing well-known technology, and the implementer can select other existing feasible curve fitting algorithms according to actual conditions, which will not be described in detail in this embodiment. In this embodiment, M=100, which can be set by the implementer according to actual conditions, and this embodiment is not limited here.

[0042] The infrared absorption method is used to detect the content of carbon in the honeysuckle to be tested. For any of the heavy metal elements, the content of carbon in the honeysuckle to be tested is used as the independent variable of the influence curve of any of the heavy metal elements, and the corresponding dependent variable is obtained as the influence degree of the carbon in the honeysuckle to be tested on the detection of the content of any of the heavy metal elements.

[0043] Further, based on the influence of the carbon element in the honeysuckle to be tested on the detection of the heavy metal element content, combined with the peak shape variability, the peak base energy difference, and the difference in peak shape width between each pair of characteristic peaks, the abnormal correction coefficient of each characteristic peak in the spectral curve to be tested is determined, and the specific calculation method 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.

[0044] It should be noted that the width of the peak bottom of the characteristic peak is the absolute value of the difference between the horizontal coordinates of the left starting position and the right starting position of the characteristic peak.

[0045] It should be understood that due to the influence of baseline drift, the energy intensity of the base of the characteristic peak in the measured spectrum curve will be different from that of the standard spectrum curve, the width of the base of the characteristic peak will also be different, and the absolute value of the influence of the heavy metal element corresponding to the characteristic peak on the carbon content will be greater, which means that the interference degree of the characteristic peak is more serious, and the possibility of abnormality of the characteristic peak is greater, which in turn affects the calculated abnormality correction coefficient. The abnormality correction coefficient determination flow chart is as follows: Figure 2 shown.

[0046] S4, determining 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.

[0047] Each characteristic peak in the measured spectrum curve corresponds to a heavy metal element. Based on the above analysis, according to the abnormal correction coefficient of each characteristic peak in the measured spectrum curve, the content of the heavy metal element corresponding to each characteristic peak in the measured spectrum element is corrected.

[0048] Specifically: for M honeysuckle with known heavy metal content, the same calculation method as the abnormal correction coefficient of each characteristic peak in the above-mentioned spectrum curve to be measured is adopted to obtain the abnormal correction coefficient of each characteristic peak in the X-ray fluorescence spectrum curve of the M honeysuckle, and also taking any heavy metal element as an example, the abnormal correction coefficient of the corresponding characteristic peak in the X-ray fluorescence spectrum curve of any heavy metal element in any honeysuckle and the measured difference of any heavy metal element in any honeysuckle are combined into two-dimensional data points, and the two-dimensional data points of any heavy metal element in the M honeysuckle are curve fitted by the least squares method to obtain the error curve of any heavy metal element, wherein, in the fitting process, the abnormal correction coefficient is used as the horizontal coordinate, and the measured difference of the heavy metal element in the honeysuckle is used as the vertical coordinate.

[0049] Based on the spectral curve of the honeysuckle to be tested, the measured values ​​of the contents of each heavy metal element in the honeysuckle to be tested are obtained, and the abnormal correction coefficients of the corresponding characteristic peaks of each heavy metal element in the honeysuckle to be tested in the spectral curve to be tested are substituted as independent variables into the error curve of the corresponding heavy metal element to obtain the measurement error values ​​of each heavy metal element in the honeysuckle to be tested, and the measurement error values ​​are the measurement differences. The difference between the measured values ​​of the contents of each heavy metal element in the honeysuckle to be tested and the measurement error values ​​is calculated as the actual content of each heavy metal element in the honeysuckle to be tested.

[0050] Based on the same inventive concept as the above method, an embodiment of the present application also provides a system for rapidly detecting heavy metals in traditional Chinese medicinal materials, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above methods for rapidly detecting heavy metals in traditional Chinese medicinal materials are implemented.

[0051] It should be noted that the above sequence of the embodiments of the present application is for description only and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying 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.

[0052] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0053] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present application should 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; 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, which is recorded as the measurement difference. The abnormal correction coefficient of the corresponding characteristic peak of each heavy metal element in the honeysuckle with known heavy metal content is obtained. Based on the correlation between the measurement difference and the abnormal correction coefficient of the corresponding characteristic peak, the actual content of each heavy metal element in the honeysuckle to be tested is determined.

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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