Evaluation Method for Cleaning Effect of Chinese Herbal Medicines Processed by Stir-baking with Honey Based on Spectral Technology

Abstract

This application relates to the technical field of spectral analysis of traditional Chinese medicine processing, specifically to an evaluation method for the cleaning effect of processed traditional Chinese medicine materials combined with spectral technology, including: collecting the cleaning spectral data of the medicinal materials at each sampling point, dividing the characteristic absorption peak sequences, and calculating the absorption interference evaluation coefficient of each sampling point based on the symmetry of each characteristic absorption peak sequence and the stability of the fluctuations at each sampling point; based on the differences in the cleaning spectral data of the medicinal materials between each sampling point and the remaining sampling points in the neighborhood, combined with the absorption interference evaluation coefficient, obtaining the cleaning difference index of each sampling point, obtaining the interference removal balance index of each sampling point, calculating the medicinal material cleaning compliance index, and determining whether the cleaning effect of the medicinal materials meets the standard. This application aims to solve the problem that the near-infrared spectral data during the medicinal material cleaning process is easily interfered, resulting in inaccurate evaluation of the cleaning effect of the medicinal materials, and improves the accuracy of the evaluation of the cleaning effect of the medicinal materials.

Description

Technical Field

[0001] This application relates to the technical field of spectral analysis of traditional Chinese medicine processing, and specifically to a method for evaluating the cleaning effect of processed traditional Chinese medicine materials by combining spectral technology. Background Art

[0002] Traditional Chinese medicine processing refers to the traditional methods and techniques of processing traditional Chinese medicine materials into Chinese medicine decoction pieces under the guidance of traditional Chinese medicine theory. In the process of traditional Chinese medicine processing, there are many common methods for cleaning traditional Chinese medicine materials, such as washing with water, spraying method, soaking method, bleaching method, stewing method, and wine processing, etc. In the process of cleaning the materials, on the one hand, it is to remove impurities such as soil attached to the materials, and on the other hand, it can reduce toxicity, change the medicinal properties, etc. In order to ensure meeting the processing standards, it is necessary to evaluate the cleaning effect of the materials during the cleaning process.

[0003] The traditional evaluation of the cleaning effect of materials is to judge the turbidity of the cleaning tank through manual or traditional Chinese medicine material cleaning equipment, and then evaluate the cleaning effect of the materials. However, in the actual evaluation process, it is interfered by impurities on the surface of the materials, uneven distribution of the medicinal properties of the materials, uneven distribution of the solvent, etc., making the evaluation of the cleaning effect of the materials inaccurate. Summary of the Invention

[0004] In view of the above, it is necessary to provide a method for evaluating the cleaning effect of processed traditional Chinese medicine materials by combining spectral technology, which improves the accuracy of judging the cleaning effect of the materials compared with the traditional method for evaluating the cleaning effect of processed traditional Chinese medicine materials.

[0005] The method for evaluating the cleaning effect of processed traditional Chinese medicine materials by combining spectral technology in this application adopts the following technical solutions:

[0006] An embodiment of this application provides a method for evaluating the cleaning effect of processed traditional Chinese medicine materials by combining spectral technology, and this method includes the following steps:

[0007] Collect the cleaning spectral data of the materials at each sampling point;

[0008] Divide the characteristic absorption peak sequence according to the cleaning spectral data of the materials, and calculate the absorption interference evaluation coefficient of each sampling point based on the symmetry of each characteristic absorption peak sequence and the smoothness of the fluctuation at each sampling point;

[0009] Based on the difference in the cleaning spectral data of the materials between each sampling point and the remaining sampling points in the neighborhood, combine the absorption interference evaluation coefficient to obtain the cleaning difference index of each sampling point;

[0010] Obtain the interference removal balance index of each sampling point according to the cleaning difference index and the absorption interference evaluation coefficient of each sampling point;

[0011] Calculate the compliance index of medicinal material cleaning based on the spectral data of medicinal material cleaning at all sampling points and the interference removal balance index, and determine whether the medicinal material cleaning effect meets the standard.

[0012] In one embodiment, the specific method for dividing the characteristic absorption peak sequences is as follows:

[0013] Use the peak detection algorithm to extract all peak points in the spectral data of medicinal material cleaning. Take the midpoint between each peak point and the next adjacent peak point in the spectral data of medicinal material cleaning as a segmentation point, and divide each spectral data of medicinal material cleaning into multiple characteristic absorption peak sequences.

[0014] In one embodiment, the specific calculation method for the absorption interference evaluation coefficient is as follows:

[0015] Obtain the adjacent wavelength absorbance difference index for each characteristic absorption peak sequence based on the stationarity of the fluctuation of each characteristic absorption peak sequence;

[0016] Obtain the symmetric absorbance difference coefficient for each characteristic absorption peak sequence based on the symmetry of each characteristic absorption peak sequence;

[0017] The absorption interference evaluation coefficient of each sampling point is positively correlated with the adjacent wavelength absorbance difference index and the symmetric absorbance difference coefficient of each characteristic absorption peak sequence of each sampling point, and negatively correlated with the range of each characteristic absorption peak sequence of each sampling point.

[0018] In one embodiment, the specific method for obtaining the adjacent wavelength absorbance difference index for each characteristic absorption peak sequence is as follows:

[0019] Take the first-order difference of each characteristic absorption peak sequence as the adjacent wavelength absorbance difference sequence, and take the sum of all data points of the adjacent wavelength absorbance difference sequence as the adjacent wavelength absorbance difference index for each characteristic absorption peak sequence.

[0020] In one embodiment, the specific method for obtaining the symmetric absorbance difference coefficient for each characteristic absorption peak sequence is as follows:

[0021] Take the peak point in each characteristic absorption peak sequence as the peak symmetry axis, fill in the missing values for each characteristic absorption peak sequence to obtain the symmetric absorption peak sequence, and take the two data points symmetric about the peak symmetry axis on both sides of the symmetric absorption peak sequence as the symmetric point pairs;

[0022] For each symmetric point pair in the symmetric absorption peak sequence, record the absolute value of the difference between the two data points of each symmetric point pair as the absorbance difference index of each symmetric point pair, and record the average value of the absorbance difference indices of all symmetric point pairs in each symmetric absorption peak sequence as the symmetric absorbance difference coefficient for each characteristic absorption peak sequence.

[0023] In one embodiment, the method for obtaining the cleaning difference index of each sampling point specifically includes:

[0024] For any sampling point, sort the distances between all sampling points and the any sampling point in ascending order, and use the first preset number of sampling points as the neighborhood reference points of the any sampling point;

[0025] Based on the difference in the absorption interference evaluation coefficients between each sampling point and its neighborhood reference points, obtain the anti-interference ability of each neighborhood reference point of each sampling point. Based on the difference in the medicinal material cleaning spectral data between each sampling point and its neighborhood reference points, obtain the neighborhood light absorption difference coefficient of each neighborhood reference point of each sampling point;

[0026] The cleaning difference index of each sampling point is negatively correlated with the anti-interference ability and positively correlated with the neighborhood light absorption difference coefficient.

[0027] In one embodiment, the anti-interference ability of each neighborhood reference point of each sampling point is the absolute value of the difference between the absorption interference evaluation coefficients of each sampling point and each neighborhood reference point.

[0028] In one embodiment, the neighborhood light absorption difference coefficient of each neighborhood reference point of each sampling point is the distance between the medicinal material cleaning spectral data of each sampling point and each neighborhood reference point.

[0029] In one embodiment, the interference removal balance index of each sampling point is negatively correlated with the corresponding cleaning difference index and positively correlated with the corresponding absorption interference evaluation coefficient.

[0030] In one embodiment, the method for calculating the medicinal material cleaning compliance index and determining whether the medicinal material cleaning effect meets the standard specifically includes:

[0031] Use the interference removal balance index of each sampling point as the smoothing parameter of the locally symmetric reweighted penalized least squares method, and use the locally symmetric reweighted penalized least squares method to perform baseline correction on the medicinal material cleaning spectral data of each sampling point, and output the corrected medicinal material cleaning data of each sampling point;

[0032] Use the similarity between the corrected medicinal material cleaning data of each sampling point and the standard medicinal material cleaning data as the medicinal material cleaning index of each sampling point. The medicinal material cleaning compliance index is positively correlated with the medicinal material cleaning indexes of all sampling points;

[0033] When the medicinal material cleaning compliance index is greater than or equal to the preset cleaning qualification threshold, determine that the medicinal material cleaning effect meets the standard; otherwise, determine that the medicinal material cleaning effect does not meet the standard.

[0034] The present application has the following beneficial effects:

[0035] Divide the characteristic absorption peak sequences based on the spectral data of the medicinal material cleaning at each sampling point, analyze the drastic fluctuations and the asymmetry of the peaks in the spectral data of the medicinal material cleaning caused by the interference of the surface texture of the medicinal material and environmental noise, etc., calculate the absorption interference evaluation coefficient for each sampling point based on the symmetry of each characteristic absorption peak sequence and the stability of the fluctuations at each sampling point, so as to measure the degree of interference of the spectral data of the medicinal material cleaning by the surface texture of the medicinal material and environmental noise, etc.; considering that the components in the spectral data of the medicinal material cleaning at the sampling points with poor cleaning effect of the medicinal material are complex and different from the spectral data of the medicinal material cleaning at the surrounding sampling points, based on the difference between the spectral data of the medicinal material cleaning at each sampling point and the spectral data of the medicinal material cleaning at the remaining sampling points in the neighborhood, and combine the absorption interference evaluation coefficient to obtain the cleaning difference index for each sampling point, set a smaller weight for the sampling points with a large difference in the absorption interference evaluation coefficient in the neighborhood, which improves the reliability of evaluating the degree of interference of the spectral data of the medicinal material cleaning at each sampling point by impurities; the cleaning difference index represents the degree of interference of the spectral data of the medicinal material cleaning at the sampling point by impurities, and the absorption interference evaluation coefficient represents the degree of interference of the spectral data of the medicinal material cleaning at the sampling point by the surface texture of the medicinal material and environmental noise, etc. Considering the retention of the cleaning detail information of the spectral data of the medicinal material cleaning at the sampling point and the removal of the interference of the surface texture of the medicinal material, environmental noise, etc., obtain the interference removal balance index for each sampling point according to the cleaning difference index and the absorption interference evaluation coefficient of each sampling point, and use it as the smoothing parameter of the locally symmetric reweighted penalized least squares method, which improves the reliability of determining the smoothing parameter; use the locally symmetric reweighted penalized least squares method to perform baseline correction on the spectral data of the medicinal material cleaning at each sampling point, and output the corrected spectral data of the medicinal material cleaning at each sampling point, while retaining the cleaning detail information of the spectral data of the medicinal material cleaning, as much as possible removing the interference of the surface texture of the medicinal material and environmental noise, etc., and avoiding the problems of insufficient correction or overfitting in the baseline correction of the spectral data of the medicinal material cleaning at each sampling point; calculate the medicinal material cleaning compliance index according to the corrected spectral data of the medicinal material cleaning at all sampling points, and judge whether the cleaning effect of the medicinal material meets the standard, which improves the accuracy of evaluating the cleaning effect of the medicinal material. Description of the Drawings

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0037] Figure 1 Schematic flow chart of the method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials combined with spectral technology provided by an embodiment of the present application;

[0038] Figure 2 Schematic diagram for obtaining the absorption interference evaluation coefficient. Specific implementation manners

[0039] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example", etc. are used to indicate examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary", "or", "for example", etc. is intended to present relevant concepts in a specific manner.

[0040] 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.

[0041] Please refer to Figure 1 , which shows a flowchart of a method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials combined with spectral technology provided by an embodiment of the present application. The method includes the following steps:

[0042] Step S001: Collect the medicinal material cleaning spectral data of each sampling point.

[0043] There are many ways to clean traditional Chinese medicine materials. In the present application, the immersion method is used to clean traditional Chinese medicine materials. Preferably, as an embodiment of the present application, the method for cleaning traditional Chinese medicine materials is: soaking the medicinal materials in an organic solution so that the toxins in the medicinal materials are slowly extracted and separated by the organic solution, thereby changing the medicinal properties of the medicinal materials and reducing the toxicity of the medicinal materials. To obtain the cleaning effect of the immersion method, a near-infrared spectrometer is deployed directly above the immersion container, and the medicinal material cleaning spectral data of each sampling point in the traditional Chinese medicine material immersion container is collected during the immersion process.

[0044] It should be noted that the number of sampling points is a preset value by humans. The organic solution includes yellow rice wine, rice wine and white wine. In this embodiment, white wine is selected as the organic solution to soak the traditional Chinese medicine materials, and the number of sampling points is 100. For the selection of the organic solution and the setting of the number of sampling points, as other implementation manners, the implementer can select by himself / herself, and the present application does not make special restrictions on this. In the medicinal material cleaning spectral data of each sampling point at each acquisition moment, the abscissa represents the wavelength, and the ordinate represents the absorbance, which reflects the degree of light absorption at different wavelengths by the traditional Chinese medicine material soaking solution.

[0045] Step S002: Divide the characteristic absorption peak sequences according to the medicinal material cleaning spectral data, and calculate the absorption interference evaluation coefficient of each sampling point based on the symmetry of each characteristic absorption peak sequence and the smoothness of the fluctuations at each sampling point.

[0046] It should be noted that since most of the traditional Chinese medicines are woody or herbaceous plants, the surfaces of the medicines usually have longitudinal, transverse, reticular or irregular textures. In addition, during the process of collecting the medicines, defects such as cracks or fractures may occur on the medicines. Due to the above reasons, the surface characteristics of the medicines are often uneven and diverse. Therefore, near-infrared light in the soaking solution of traditional Chinese medicines is easily affected by scattered light, resulting in a large number of noise points in the spectral data of medicine cleaning. At the same time, affected by the unevenness of scattering and reflection, the spectral data of medicine cleaning undergoes a certain degree of deformation, which affects the detection of the cleaning effect of traditional Chinese medicines.

[0047] In order to analyze the influence of the concave-convex characteristics of the surface of traditional Chinese medicines on the spectral data of medicine cleaning, a peak detection algorithm is used to extract all the peak points in the spectral data of medicine cleaning. The midpoint between each peak point and the next adjacent peak point in the spectral data of medicine cleaning is used as a segmentation point, and each spectral data of medicine cleaning is segmented into multiple characteristic absorption peak sequences.

[0048] It should be noted that each characteristic absorption peak sequence contains a peak point. The peak detection algorithm is a well-known technology. In this embodiment, the automatic multi-scale peak detection algorithm is selected for the extraction of peak points. For the selection of the peak detection algorithm, as other implementation manners, the implementer can select it by himself / herself, and this application does not make special restrictions on this.

[0049] Furthermore, the first-order difference of each characteristic absorption peak sequence is used as the adjacent wavelength absorbance difference sequence, and the sum of all data points of the adjacent wavelength absorbance difference sequence is used as the adjacent wavelength absorbance difference index of each characteristic absorption peak sequence. The peak point in each characteristic absorption peak sequence is used as the peak symmetry axis, and missing value filling is performed on each characteristic absorption peak sequence to obtain a symmetric absorption peak sequence. The two data points symmetric about the peak symmetry axis on both sides of the symmetric absorption peak sequence are used as a symmetric point pair. For each symmetric point pair in the symmetric absorption peak sequence, the absolute value of the difference between the two data points of each symmetric point pair is recorded as the absorbance difference index of each symmetric point pair, and the average value of the absorbance difference indices of all symmetric point pairs in each symmetric absorption peak sequence is recorded as the symmetric absorbance difference coefficient of each characteristic absorption peak sequence.

[0050] The absorption interference evaluation coefficient of each sampling point is positively correlated with the adjacent wavelength absorbance difference index and the symmetric absorbance difference coefficient of each characteristic absorption peak sequence of each sampling point, and is negatively correlated with the range of each characteristic absorption peak sequence of each sampling point.

[0051] It should be understood that the lengths on both sides of the peak symmetry axis of the symmetric absorption peak sequence are equal. Filling in missing values is a well-known technique. In this embodiment, the regression filling method is selected for filling in missing values. As other implementation manners, the implementer can select by himself / herself, and this application does not make special restrictions thereon. A positive correlation relationship refers to the relationship between an independent variable and a dependent variable. When the independent variable increases or decreases, the dependent variable will also increase or decrease accordingly, that is, the change directions of the two variables are the same. The positive correlation relationship can be a multiplicative relationship, an additive relationship, a proportional relationship, etc., and this application does not make special restrictions thereon. A negative correlation relationship means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtractive relationship, a divisive relationship, etc., which is determined by the actual application.

[0052] As an embodiment of this application, the range of each characteristic absorption peak sequence is added with a tuning factor to obtain the adjusted range of the characteristic absorption peak sequence. The sum of the adjacent wavelength absorbance difference index and the symmetric absorbance difference coefficient of each characteristic absorption peak sequence is divided by the adjusted range to obtain the difference interference coefficient of the characteristic absorption peak sequence. The average value of the difference interference coefficients of all characteristic absorption peak sequences at each sampling point is recorded as the absorption interference evaluation coefficient of the sampling point. In an embodiment of this application, a schematic diagram for obtaining the absorption interference evaluation coefficient is as Figure 2 shown.

[0053] It should be noted that the tuning factor is a positive number preset by a person. The role of the tuning factor is to prevent the denominator from being 0, resulting in the difference interference coefficient being meaningless. In this embodiment, the value of the tuning factor is 1. As other implementation manners, the implementer can select by himself / herself, and this application does not make special restrictions thereon.

[0054] Furthermore, it should be noted that when the medicinal material cleaning spectral data of the sampling point is severely affected by the scattering of the concave and convex characteristics on the surface of the traditional Chinese medicine, the number of noise points in the corresponding characteristic absorption peak sequence is large, the fluctuation of the absorbance is large, and the adjacent wavelength absorbance difference index value is large; in addition, the scattering chaos will cause the characteristic peaks to deform and destroy the original symmetry, and the absorbance difference index of the symmetric point pairs symmetric about the peak symmetry axis in the characteristic absorption peak sequence increases, making the value of the symmetric absorbance difference coefficient of the characteristic absorption peak sequence increase; the smaller the range of the characteristic absorption peak sequence, the more easily the characteristic absorption peak sequence is interfered by scattering, and finally the value of the absorption interference evaluation coefficient of the sampling point is larger.

[0055] Step S003: Based on the differences in the medicinal material cleaning spectral data between each sampling point and the remaining sampling points in the neighborhood, combine the absorption interference evaluation coefficient to obtain the cleaning difference index of each sampling point.

[0056] It should be noted that, compared with the density of the solvent, the density of traditional Chinese medicine materials is usually smaller, so the traditional Chinese medicine materials often float on the surface of the solvent. Affected by the degree of solvent diffusion, the soaking and cleaning degrees of different positions of the traditional Chinese medicine materials are different. In the areas with less soaking, the cleaning degree is lower, resulting in complex components in the cleaning spectral data of the medicinal materials. When using a near-infrared spectrometer detector for lattice scanning, the soaking container of the traditional Chinese medicine materials will be scanned at equal intervals. In order to evaluate the cleaning effect of the traditional Chinese medicine materials at each sampling point, for any sampling point, the distances between all sampling points and the any sampling point are arranged in ascending order, and the first s sampling points are used as the neighborhood reference points of the any sampling point.

[0057] Furthermore, for each neighborhood reference point of any sampling point, the absolute value of the difference between the absorption interference evaluation coefficient of the any sampling point and each neighborhood reference point is denoted as the anti-interference ability of the any sampling point and each neighborhood reference point, and the distance between the any sampling point and the medicinal material cleaning spectral data of each neighborhood reference point is denoted as the neighborhood light absorption difference coefficient of each neighborhood reference point of the any sampling point. The cleaning difference index of the any sampling point is negatively correlated with the anti-interference ability and positively correlated with the neighborhood light absorption difference coefficient.

[0058] It should be noted that the medicinal material cleaning spectral data of each sampling point is a sequence. The calculation of the distance between sequences and the calculation of the distance between data points are both well-known technologies. The number s of neighborhood reference points of each sampling point is a preset value by humans. In this embodiment, the number of neighborhood reference points of each sampling point is taken as 5. The DTW distance is selected for calculating the distance between sequences, and the Euclidean distance is selected for calculating the distance between sampling points. For the value of the number of neighborhood reference points of each sampling point, the calculation of the distance between sequences, and the calculation of the distance between sampling points, as other implementation manners, the implementer can select according to the actual situation by himself / herself, and this application does not make special restrictions on this.

[0059] As an embodiment of this application, the sum of the anti-interference abilities of each sampling point and all neighborhood reference points is denoted as the fluctuation situation of each sampling point. The anti-interference ability of each neighborhood reference point of the sampling point is divided by the fluctuation situation as the neighborhood interference situation of each neighborhood reference point of the sampling point. The difference between the number 1 and the neighborhood interference situation is denoted as the difference weight of each neighborhood reference point of the sampling point. The neighborhood light absorption difference coefficient of each neighborhood reference point of the sampling point is multiplied by the difference weight as the light absorption anti-interference difference factor of each neighborhood reference point of the sampling point. The sum of the light absorption anti-interference difference factors of all neighborhood reference points of the sampling point is denoted as the cleaning difference index of the sampling point.

[0060] It should be further noted that when the distance between the sampling point and the medicinal material cleaning spectral data of each sampling point in the local comparison area is larger, it indicates that the component differences among the sampling points in the neighborhood of this sampling point are greater, and it is more likely to contain impurities. The medicinal material cleaning spectral data of this sampling point is more likely to be interfered by impurities, and the cleaning difference index value is larger; when the difference between the absorption interference evaluation coefficients of two sampling points is larger, it indicates that the degrees of interference on the medicinal material cleaning spectral data of the two sampling points are more different. When evaluating the degree of interference of the medicinal material cleaning spectral data of each sampling point by impurities, a smaller weight should be set, and the difference weight value is smaller.

[0061] Step S004: Obtain the interference removal balance index of each sampling point according to the cleaning difference index and the absorption interference evaluation coefficient of each sampling point.

[0062] It should be noted that the medicinal material cleaning spectral data will be interfered by impurities on the surface of the medicinal material, surface texture of the medicinal material, environmental noise, etc., resulting in problems such as baseline drift of the medicinal material cleaning spectral data and even the submergence of important characteristic peaks. In order to improve the accuracy of detecting the cleaning effect of the medicinal material, when using the local symmetric reweighted penalized least squares method to correct the baseline of the medicinal material cleaning spectral data, the interference of the surface texture of the medicinal material and environmental noise, etc. should be weakened while retaining the detailed information on the surface of the medicinal material.

[0063] Specifically, the interference removal balance index of each sampling point is negatively correlated with the corresponding cleaning difference index and positively correlated with the corresponding absorption interference evaluation coefficient.

[0064] As an embodiment of the present application, the normalized value of the ratio of the absorption interference evaluation coefficient to the cleaning difference index of each sampling point is multiplied by the adjustment coefficient to be recorded as the interference removal balance index of each sampling point.

[0065] It should be understood that the value range of the smoothing parameter of the local symmetric reweighted penalized least squares method is 0 to 10. The adjustment coefficient is a value preset by humans. The function of the adjustment coefficient is to adjust the value range of the interference removal balance index of each sampling point. In this embodiment, the adjustment coefficient takes the value of 10. As other implementation manners, the implementer can select it by himself.

[0066] It should be noted that the larger the cleaning difference index is, the more likely the medicinal material cleaning spectral data at the sampling point is interfered by impurities. When performing baseline correction on the medicinal material cleaning spectral data at this sampling point, a smaller smoothing parameter should be set to retain the detailed information of the medicinal material cleaning spectral data and improve the accuracy of subsequent evaluation of the medicinal material cleaning effect, and the interference removal balance index value is smaller; the larger the absorption interference evaluation coefficient is, the more likely the medicinal material cleaning spectral data at the sampling point is interfered by the surface texture of the medicinal material and environmental noise, etc. When performing baseline correction on the medicinal material cleaning spectral data at this sampling point, a larger smoothing parameter should be set to weaken the interference of the surface texture of the medicinal material and environmental noise, etc., and improve the accuracy of subsequent evaluation of the medicinal material cleaning effect, and the interference removal balance index value is larger.

[0067] Step S005: Calculate the medicinal material cleaning compliance index based on the medicinal material cleaning spectral data of all sampling points and the interference removal balance index, and determine whether the medicinal material cleaning effect meets the standard.

[0068] Take the interference removal balance index of each sampling point as the smoothing parameter of the locally symmetric reweighted penalized least squares method, and use the locally symmetric reweighted penalized least squares method to perform baseline correction on the medicinal material cleaning spectral data of each sampling point, and output the corrected medicinal material cleaning data of each sampling point.

[0069] In order to obtain the cleaning effect of Chinese medicinal materials at each sampling moment, take the similarity between the corrected medicinal material cleaning data of each sampling point and the standard medicinal material cleaning data as the medicinal material cleaning index of each sampling point, and the medicinal material cleaning compliance index is positively correlated with the medicinal material cleaning indexes of all sampling points.

[0070] As an embodiment of the present application, take the average value of the medicinal material cleaning indexes of all sampling points as the medicinal material cleaning compliance index.

[0071] It should be noted that the standard medicinal material cleaning data is obtained from an existing database. Both the corrected medicinal material cleaning data and the standard medicinal material cleaning data are a sequence, and the calculation of the similarity between sequences is a well-known technology. In this embodiment, the cosine similarity is selected to calculate the similarity between sequences. As other implementation manners, the implementer can select it by himself / herself, and the present application does not make special restrictions on this. The greater the similarity between the corrected medicinal material cleaning data and the standard medicinal material cleaning data at each sampling point, the more likely the cleaning effect at each sampling point has met the standard, and the larger the medicinal material cleaning compliance index value.

[0072] Furthermore, when the medicinal material cleaning compliance index is greater than or equal to the cleaning qualified threshold, it is determined that the medicinal material cleaning effect meets the standard; otherwise, it is determined that the medicinal material cleaning effect does not meet the standard.

[0073] It should be understood that the cleaning qualified threshold is a preset value by humans. In this embodiment, the cleaning qualified threshold is taken as 0.8. As other implementation manners, the implementer can select it by himself / herself, and this application does not make special restrictions on this.

[0074] The embodiment of the present application provides a method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials combined with spectral technology. The method includes: dividing the characteristic absorption peak sequence based on the medicinal material cleaning spectral data of each sampling point, analyzing the severe fluctuations and the asymmetry of the peaks of the medicinal material cleaning spectral data caused by the interference of the medicinal material surface texture and environmental noise, etc., calculating the absorption interference evaluation coefficient of each sampling point based on the symmetry of each characteristic absorption peak sequence and the smoothness of the fluctuations of each sampling point to measure the interference degree of the medicinal material cleaning spectral data by the medicinal material surface texture and environmental noise, etc.; considering that the components in the medicinal material cleaning spectral data of the sampling points with poor cleaning effect of the medicinal materials are complex and different from the medicinal material cleaning spectral data of the surrounding sampling points, based on the difference between the medicinal material cleaning spectral data of each sampling point and the medicinal material cleaning spectral data of the remaining sampling points in the neighborhood, combining the absorption interference evaluation coefficient to obtain the cleaning difference index of each sampling point, setting a smaller weight for the sampling points with larger differences in the absorption interference evaluation coefficient in the neighborhood, and improving the reliability of evaluating the interference degree of the medicinal material cleaning spectral data of each sampling point by impurities; the cleaning difference index represents the interference degree of the medicinal material cleaning spectral data of the sampling point by impurities, and the absorption interference evaluation coefficient represents the interference degree of the medicinal material cleaning spectral data of the sampling point by the medicinal material surface texture and environmental noise, etc. Considering the retention of the cleaning detail information of the medicinal material cleaning spectral data of the sampling point and the removal of the interference of the medicinal material surface texture, environmental noise, etc., obtaining the interference removal balance index of each sampling point according to the cleaning difference index and the absorption interference evaluation coefficient of each sampling point, and using it as the smoothing parameter of the locally symmetric reweighted penalized least squares method, improving the reliability of determining the smoothing parameter; using the locally symmetric reweighted penalized least squares method to perform baseline correction on the medicinal material cleaning spectral data of each sampling point, and outputting the corrected medicinal material cleaning data of each sampling point, while retaining the cleaning detail information of the medicinal material cleaning spectral data, removing the interference of the medicinal material surface texture and environmental noise, etc. as much as possible, and avoiding the problems of under-correction or overfitting in the baseline correction of the medicinal material cleaning spectral data of each sampling point; calculating the medicinal material cleaning compliance index according to the corrected medicinal material cleaning data of all sampling points to judge whether the medicinal material cleaning effect meets the standard, and improving the accuracy of evaluating the medicinal material cleaning effect.

[0075] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of code, or a part thereof that contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. In the description corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0076] For those skilled in the art, it is apparent that the present application is not limited to the details of the above-described exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the basic characteristics of the present application. Therefore, in any aspect, the above-described embodiments of the present application should be considered exemplary and non-limiting.

Claims

1. A method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials combined with spectral technology, characterized in that The method includes the following steps: Collect the medicinal material cleaning spectral data of each sampling point; Divide the characteristic absorption peak sequences according to the medicinal material cleaning spectral data, and obtain the adjacent wavelength absorbance difference index of each characteristic absorption peak sequence based on the stationarity of the fluctuations of each characteristic absorption peak sequence; obtain the symmetric absorbance difference coefficient of each characteristic absorption peak sequence based on the symmetry of each characteristic absorption peak sequence; the absorption interference evaluation coefficient of each sampling point is positively correlated with the adjacent wavelength absorbance difference index and the symmetric absorbance difference coefficient of each characteristic absorption peak sequence of each sampling point, and is negatively correlated with the range of each characteristic absorption peak sequence of each sampling point; For any sampling point, sort the distances between all sampling points and the any sampling point in ascending order, and use the first preset number of sampling points as the neighborhood reference points of the any sampling point; obtain the anti-interference ability of each neighborhood reference point of each sampling point based on the difference in the absorption interference evaluation coefficients between each sampling point and the neighborhood reference points, and obtain the neighborhood absorbance difference coefficient of each neighborhood reference point of each sampling point based on the difference in the medicinal material cleaning spectral data between each sampling point and the neighborhood reference points; the cleaning difference index of each sampling point is negatively correlated with the anti-interference ability and positively correlated with the neighborhood absorbance difference coefficient; Obtain the interference removal balance index of each sampling point according to the cleaning difference index and the absorption interference evaluation coefficient of each sampling point; the interference removal balance index of each sampling point is negatively correlated with the corresponding cleaning difference index and positively correlated with the corresponding absorption interference evaluation coefficient; Calculate the medicinal material cleaning compliance index according to the medicinal material cleaning spectral data and the interference removal balance index of all sampling points, and judge whether the medicinal material cleaning effect meets the standard.

2. The method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials by combining spectroscopic techniques according to claim 1, wherein, The specific method for dividing the characteristic absorption peak sequences is as follows: Adopt a peak detection algorithm to extract all peak points in the medicinal material cleaning spectral data, take the midpoint between each peak point and the next adjacent peak point in the medicinal material cleaning spectral data as a segmentation point, and divide each medicinal material cleaning spectral data into multiple characteristic absorption peak sequences.

3. The method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials by combining spectral technology according to claim 1, wherein, The specific method for obtaining the adjacent wavelength absorbance difference index of each characteristic absorption peak sequence is as follows: Take the first-order difference of each characteristic absorption peak sequence as the adjacent wavelength absorbance difference sequence, and take the sum of all data points of the adjacent wavelength absorbance difference sequence as the adjacent wavelength absorbance difference index of each characteristic absorption peak sequence.

4. The method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials combined with spectral technology according to claim 1, wherein The specific method for obtaining the symmetric absorbance difference coefficient of each characteristic absorption peak sequence is as follows: Take the peak point in each characteristic absorption peak sequence as the peak symmetry axis, fill in the missing values of each characteristic absorption peak sequence to obtain the symmetric absorption peak sequence, and take two data points symmetric about the peak symmetry axis on both sides of the symmetric absorption peak sequence as the symmetric point pairs; For each symmetric point pair in the symmetric absorption peak sequence, record the absolute value of the difference between the two data points of each symmetric point pair as the absorbance difference index of each symmetric point pair, and record the average value of the absorbance difference indices of all symmetric point pairs in each symmetric absorption peak sequence as the symmetric absorbance difference coefficient of each characteristic absorption peak sequence.

5. The method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials combined with spectroscopic technology according to claim 1, characterized in that, The anti-interference ability of each neighborhood reference point of each sampling point is the absolute value of the difference between the absorption interference evaluation coefficients of each sampling point and each neighborhood reference point.

6. The method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials by combining spectral technology according to claim 1, wherein The neighborhood light absorption difference coefficient of each neighborhood reference point of each sampling point is the distance between the medicinal material cleaning spectral data of each sampling point and each neighborhood reference point.

7. The method for evaluating the cleaning effect of traditional Chinese medicine processed medicinal materials by combining spectral technology according to claim 1, characterized in that, The specific method for calculating the medicinal material cleaning compliance index and determining whether the medicinal material cleaning effect meets the standard includes: Taking the interference removal balance index of each sampling point as the smoothing parameter of the locally symmetric reweighted penalized least squares method, and using the locally symmetric reweighted penalized least squares method to perform baseline correction on the medicinal material cleaning spectral data of each sampling point, and outputting the corrected medicinal material cleaning data of each sampling point; Taking the similarity between the corrected medicinal material cleaning data of each sampling point and the standard medicinal material cleaning data as the medicinal material cleaning index of each sampling point, and the medicinal material cleaning compliance index is positively correlated with the medicinal material cleaning indexes of all sampling points; When the medicinal material cleaning compliance index is greater than or equal to the preset cleaning qualification threshold, it is determined that the medicinal material cleaning effect meets the standard, otherwise, it is determined that the medicinal material cleaning effect does not meet the standard.

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