CN115389450A - Consistency detection method based on terahertz quantum fingerprint spectrum and traditional Chinese medicine detection - Google Patents
Consistency detection method based on terahertz quantum fingerprint spectrum and traditional Chinese medicine detection Download PDFInfo
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Abstract
The invention relates to a consistency detection method based on terahertz quantum fingerprint spectrum and traditional Chinese medicine detection, which comprises the following steps: s1, detecting a sample by using a terahertz time-domain detector to obtain a terahertz time-domain spectrum, and outputting a terahertz frequency-domain spectrum and corresponding data through Fourier transform; s2, dividing a continuous curve of the terahertz frequency domain spectrum into continuously arranged points, wherein the interval between two adjacent points is equal and minimum, the two points cannot be subdivided, and a recombined graph of the points is matched with the curve; s3, dividing the graph into a plurality of continuous frequency bands, combining and assigning information of peak positions, peak heights, peak areas and half peak widths of all points in the frequency bands to form corresponding quantum peaks, and recombining the quantum peaks of all the frequency bands to form a terahertz quantum fingerprint spectrum; and S4, adopting the terahertz quantum fingerprint spectrum and corresponding data to analyze the consistency of the sample and the reference substance. Defects are eliminated through segmentation, matching, segmentation, combination, assignment and erasure, characteristics are highlighted, and detection is more efficient, accurate and stable.
Description
Technical Field
The invention relates to the field of terahertz spectrum detection, in particular to a consistency detection method based on terahertz quantum fingerprint spectrum and traditional Chinese medicine detection.
Background
Terahertz wave is electromagnetic wave with frequency of 0.1-10 THz and wavelength of 3000-30 μm, coincides with millimeter wave in long wave band and infrared light in short wave band, is transition region from macroscopic classical theory to microscopic quantum theory, is transition region from electronics to photonics, and can cover characteristic spectrum of semiconductor, plasma, organism, biological macromolecule and other substances. The basic principle of the terahertz time-domain spectroscopy technology is that femtosecond laser is utilized to excite the surface of a semiconductor to generate terahertz signals, terahertz waves with the frequency range of 0.1-10 THz are emitted, and terahertz electric fields corresponding to detection time are generated to scan a sample. And then, continuous terahertz spectrum curves and optical physical information are obtained by collecting terahertz signals after the sample penetrates or is reflected. The vibration and rotation energy levels of macromolecules are mostly in terahertz wave bands, and the macromolecules, particularly biological and chemical macromolecules, are a substance group with physical properties, so that the structure and physical properties of a substance can be analyzed and identified through characteristic frequency.
The terahertz spectrum output by the terahertz time-domain detector is a continuous curve spectrum, and although various optical physical data based on various frequency points are contained in the terahertz spectrum, the data volume is large, so that reading and operation are not intuitive enough. And the graph is complicated and disordered, and the difference analysis is difficult to carry out. The spectral curves cannot be compared, data analysis is complicated, data points are difficult to distinguish, and subsequent analysis is seriously hindered.
Disclosure of Invention
The invention aims to overcome at least one defect of the prior art, provides a consistency detection method based on terahertz quantum fingerprint spectrum and traditional Chinese medicine detection, and solves the problems that the terahertz frequency domain spectrum has too many peak points and irregular curves and cannot be used for consistency analysis on one hand; on the other hand, the consistency detection method is used for detecting the traditional Chinese medicine, so that the traditional Chinese medicine can be clearer and more intuitive in the consistency analysis process by utilizing the terahertz time-domain spectrum and related data.
The invention adopts the technical scheme that a consistency detection method based on terahertz quantum fingerprint spectrum comprises the following steps: s1, detecting a sample by using a terahertz time-domain detector to obtain a terahertz time-domain spectrum, and outputting a terahertz frequency-domain spectrum and corresponding data through Fourier transform; s2, dividing a continuous curve of the terahertz frequency domain spectrum into continuously arranged points, wherein the interval between two adjacent points is equal and minimum, the two points cannot be subdivided, and a recombined graph of the points is matched with the curve; s3, dividing the graph into a plurality of continuous frequency bands, combining and assigning information of peak positions, peak heights, peak areas and half peak widths of all points in the frequency bands to form corresponding quantum peaks, and recombining the quantum peaks of all the frequency bands to form a terahertz quantum fingerprint spectrum; and S4, adopting the terahertz quantum fingerprint spectrum and corresponding data to analyze the consistency of the sample and the reference substance.
The terahertz time-domain detector, namely TDS, obtains the terahertz time-domain spectrum of the sample after transmitting or reflecting the detected sample. The terahertz time-domain spectrum is converted into a frequency-domain signal through Fourier transform to form a terahertz frequency-domain spectrum. The terahertz frequency domain spectrum is also known as a terahertz absorption coefficient spectrum. Due to the waveform disorder of the curve in the terahertz absorption coefficient spectrum, the characteristics of the sample cannot be highlighted, the data size is large, the analysis is difficult, and the image characteristic matching and the data difference analysis required by the subsequent analysis of the sample are hindered.
By dividing the terahertz frequency domain curve, the terahertz frequency domain curve is divided into continuously sequenced points according to frequency points on an abscissa frequency domain, the distances between the points are equal, the points cannot be divided, and the number of the divided points is limited by the acquisition precision of equipment and the minimum recording point which can be divided in a frequency domain. After the segmentation, the continuously ordered points replace the original curve to form a graph consisting of the points. Each point has own coordinate, so that the corresponding characteristic can be independently extracted. When the points on the graph are connected, the formed point line graph is infinitely close to the original curve. And the graph has almost all the characteristics of the terahertz frequency domain curve. Dividing the graph according to a certain frequency band, combining the characteristics of the points in the frequency band range after division, assigning peak points, simplifying erasing and the like, and converting the integral information of the points in each frequency band into quantum peaks, thereby converting the terahertz frequency domain spectrum into a terahertz quantum fingerprint spectrum. Corresponding simplified data can be extracted through the terahertz quantum fingerprint spectrum, the integral optimization of the terahertz frequency domain spectrum and the corresponding data is realized, and the defects of excessive peak points, dense curves, non-intuition and the like of the terahertz frequency domain spectrum are overcome. On one hand, the characteristics of the curve are more visual, on the other hand, the data are more simplified, and the characteristics are more obvious and can be conveniently applied to the consistency analysis of the sample and the reference substance.
The technical scheme is that each frequency band has the same number of points, and each point only belongs to one frequency band; the intervals of each frequency band are equal, the points in the frequency bands are sequentially arranged from left to right, and the corresponding frequencies are from small to large. The curve corresponds to a plurality of points which are sequentially arranged from left to right, and each point has a corresponding terahertz response value; the number of points in each frequency band is consistent. The terahertz frequency domain spectrum is divided into a plurality of points arranged in series. After the sample is detected by the terahertz waves with the frequency of 0.1-10.0 THz, each identifiable frequency on the abscissa corresponds to a point, and the point simultaneously obtains a terahertz response value corresponding to the ordinate. Due to the wide frequency range of terahertz wave detection, a plurality of formed points are densely distributed, which is a main reason for terahertz frequency domain spectrum waveform disorder and corresponding data complexity. The point in the terahertz frequency domain spectrum is always a finite point due to the acquisition amount of the terahertz time-domain detector.
In order to solve the problems of curve peak confusion and waveform disorder of the terahertz frequency domain spectrum, points in a frequency band are integrated and extracted, so that the number of the points is reduced, and excessive interference of the points and data is eliminated. The essence of integrating and extracting curves within a frequency band is that points within the frequency band are integrated and extracted, which is essentially limited by the number of points.
In this technical scheme, in step S3, the peak position, peak height, peak area, and half-peak width information of each point in the frequency band are combined and assigned to form a corresponding quantum peak, which specifically includes the following steps: s311, taking a terahertz response value of a first point from left to right in a frequency band as the peak height of a quantum peak; s312, taking the product of the number of the points in the frequency band and the peak height as the peak area of the quantum peak; and S313, dividing the number of the points in the frequency band by a fixed constant to obtain the half-peak width of the quantum peak.
The manner of extracting the peak height, peak area, and half-peak width information through the steps S311 to S313 is more suitable for the frequency division state with a large number of frequency bands and few points in the frequency band. Or the application of further refined division and comparison aiming at the local frequency bands of the curve. The extraction mode emphasizes the influence of the longitudinal characteristics of the starting point in the frequency band on the whole frequency band, and the smaller the distance is, the closer the formed square wave is to the terahertz frequency domain spectrum.
The technical scheme is that a mode of extracting peak height, peak area and half-peak width information is carried out through steps from S311 to S313, the waveform of a quantum peak is a quasi-rectangle, the maximum value of the quasi-rectangle corresponding to a longitudinal axis is the peak height of the quantum peak, and the distance of the quasi-rectangle on a transverse axis is the half-peak width of the quantum peak; and forming a terahertz quantum fingerprint spectrum represented by square waves. Compared with a terahertz frequency domain spectrum, the terahertz quantum fingerprint spectrum displayed by continuous square waves is visually clearer, and the curve characteristics in each frequency band are obvious.
The technical scheme includes that in the step S3, peak position, peak height, peak area and half-peak width information of each point in a frequency band are combined and assigned to form corresponding quantum peaks, and the method specifically comprises the following steps: s321, taking the terahertz response value of the last point arranged in the frequency band as the peak height of a quantum peak; s322, taking the sum of terahertz response values of all points in a frequency band as the peak area of a quantum peak; and S323, dividing the number of the points in the frequency band by a fixed constant to obtain the half-peak width of the quantum peak.
The extraction of the peak height, the peak area and the half-peak width information is performed through the steps of S321 to S323, and the extraction manner emphasizes the influence of the longitudinal feature of the end point in the frequency band on the whole frequency band. Meanwhile, the combination of the rest points is integrally embodied in the form of peak area. No matter the interval is big or the interval is little, the chromatographic peak that forms can both embody the parameter after these integrations of peak height, peak area and half peak width are drawed one by one, forms terahertz quantum fingerprint spectrum to effectively promoted the commonality and the popularization nature of this kind of mode, combine with current traditional chinese medicine fingerprint spectrum technique easily, make this technique have more commonality in current detection area.
The technical scheme includes that in the step S3, peak position, peak height, peak area and half-peak width information of each point in a frequency band are combined and assigned to form corresponding quantum peaks, and the method specifically comprises the following steps: s331, taking the maximum terahertz response value in the point in the frequency band as the peak height of a quantum peak; s332, taking the sum of terahertz response values of all points in a frequency band as a peak area of a quantum peak; and S333, dividing the number of the points in the frequency band by a fixed constant to obtain the half-peak width of the quantum peak.
The extraction of peak height, peak area and half-peak width information is performed through the steps of S331 to S333, and this extraction manner emphasizes the most prominent response point in the frequency band, and also reflects the peak area in a combined manner for the remaining points. The method is suitable for different distances, and the formed chromatographic peak can also embody the parameters of peak height, peak area and half peak width after integrated extraction.
The technical scheme includes that a mode of extracting information of peak height, peak area and half peak width is carried out through steps S321 to S323 or a mode of extracting information of peak height, peak area and half peak width is carried out through steps S331 to S333, a quantum peak is displayed as a chromatographic peak, a graph in a frequency band is converted into a chromatographic peak with the same peak height, peak area and half peak width, and the graph is converted into a terahertz quantum fingerprint spectrum expressed by a chromatographic outflow curve.
The method has the advantages that the characteristics of each frequency band are selectively highlighted by converting the turbulence curves in the frequency bands into chromatographic peaks, and information except the characteristics is reflected by other shapes of the chromatographic peaks, so that the core characteristics are kept on one hand, interference is eliminated on the other hand, the curves are more visual, the comparison is more convenient, and the subsequent consistency analysis is clearer and more reliable.
According to the technical scheme, the number of the frequency bands is within 100. The more the number of frequency bands is, the more the frequency bands are similar to the original curve, the more the features need to be highlighted, so that the difficulty of comparison and the complexity difficulty are increased; the fewer the number of frequency bands, the more prominent the features, but the more features that are ignored, the greater the chance of ignoring important information during fine contrast, and the number of frequency bands should be within 100 in order to maintain accuracy and validity while eliminating the problem of excessive points.
Preferably, the frequency bands should be between 50 and 100.
The technical scheme is that the fixed constant is 0.9-0.11 times of the total number of the points.
Preferably, the fixed constant is 200, and when the fixed constant is 200, the graphic display effect is prominent, i.e., the characteristic of the peak height is highlighted, and the contrast of the peak areas is not lost.
The technical scheme is that the traditional Chinese medicine detection method comprises the following steps: s41, preparing the traditional Chinese medicine to be detected and the comparative traditional Chinese medicine into a sample and a reference substance respectively; s42, detecting the sample and the reference substance by using a terahertz time-domain detector to obtain terahertz time-domain spectrums of the sample and the reference substance; s43, adopting the consistency detection method based on the terahertz quantum fingerprint spectrum of any one of claims 1 to 9 to respectively obtain the terahertz quantum fingerprint spectrum and corresponding data of the sample and the reference; s44, calculating and obtaining qualitative similarity, quantitative similarity and difference coefficient of the sample and the reference product according to peak height, peak area and half-peak width information of the quantum peak of each frequency band in the corresponding data, and thus carrying out overall consistency analysis; obtaining main difference frequency bands of the sample and the reference through comparison of terahertz quantum fingerprint spectrums, carrying out local consistency analysis through comparison of peak position, peak height, peak area and half-peak width information of each point in the main difference frequency bands in the corresponding data of the sample and the reference, and combining the whole consistency analysis and the local consistency analysis to form consistency evaluation of traditional Chinese medicine detection.
The traditional Chinese medicine has complex composition, consists of a plurality of compounds, belongs to a complex scientific system, and the property of the medicine is the result of the synergistic and comprehensive action of the whole chemical components. The terahertz time-domain spectrum analyzer is used for integrally measuring the traditional Chinese medicine, the systematic and integrity principle of the traditional Chinese medicine is met in principle, but the terahertz frequency-domain spectrum obtained by the traditional Chinese medicine through the terahertz time-domain spectrum analyzer has the problems of many points and incapability of being read visually, the consistency detection method is combined, the characteristics of the obtained curve can be clearer, the simplified and optimized data can be incorporated into detection and comparison analysis of the traditional Chinese medicine, and therefore detection of the traditional Chinese medicine is more efficient, accurate and stable. And facilitates the implementation of subsequent consistency evaluation.
Compared with the prior art, the invention has the beneficial effects that: extracting core characteristics of the terahertz frequency domain curve by segmenting and point matching the terahertz frequency domain curve; and converting the terahertz frequency domain spectrum into a terahertz quantum fingerprint spectrum through steps of segmentation interception, range combination, peak point assignment, erasing simplification and the like. The method realizes simplification and optimization of the terahertz frequency domain spectrum, and overcomes the defects of excessive peak points, dense curves, inconvenience for intuition and the like of the terahertz frequency domain spectrum. The characteristics of the curve are clearer, and the simplified and optimized data can be included in the detection and comparison analysis of the traditional Chinese medicine, so that the detection of the traditional Chinese medicine is more efficient, accurate and stable.
Drawings
Fig. 1 is a terahertz time-domain spectrum of a sample in embodiment 1 of the present invention.
Fig. 2 is a terahertz time-domain spectrum of a control in example 1 of the present invention.
FIG. 3 is a graph showing the superposition and comparison of the terahertz time-domain spectra of the sample and the reference in example 1 of the present invention.
FIG. 4 is a terahertz frequency domain spectrum of a sample in example 1 of the present invention.
FIG. 5 is a terahertz frequency domain spectrum of a control in example 1 of the present invention.
FIG. 6 is a comparison graph of the terahertz frequency domain spectra of the sample and the reference in example 1 of the present invention.
Fig. 7 is a terahertz quantum fingerprint spectrum of a sample in embodiment 1 of the present invention.
Fig. 8 is a terahertz quantum fingerprint spectrum of the reference substance in embodiment 1 of the present invention.
FIG. 9 is a graph showing the superposition and comparison of terahertz quantum fingerprint spectra of the sample and the reference in example 1 of the present invention.
FIG. 10 is an enlarged view of a portion of FIG. 7 of the present invention.
FIG. 11 is the terahertz time-domain spectrum of Agastache rugosa in example 2 of the present invention.
Fig. 12 is a terahertz time-domain spectrum of exocarpium citri grandis in embodiment 2 of the present invention.
FIG. 13 is the terahertz frequency domain spectrum of Agastache rugosa in example 2 of the present invention.
Fig. 14 is a terahertz frequency domain spectrum of exocarpium citri rubrum in embodiment 2 of the present invention.
FIG. 15 shows terahertz quantum fingerprint spectra of Agastache rugosa in example 2 of the present invention.
Fig. 16 is a terahertz quantum fingerprint spectrum of exocarpium citri grandis in embodiment 2 of the invention.
FIG. 17 is a comparison graph showing the superposition of terahertz quantum fingerprints of Agastache rugosa and exocarpium Citri rubrum in example 2 of the present invention.
Fig. 18 is a partially enlarged view of fig. 15 in embodiment 2 of the present invention.
FIG. 19 is a flow chart of the consistency detection method of the present invention.
Fig. 20 is a graph formed by dividing a terahertz frequency domain spectral curve of a sample to form points in embodiment 1 of the present invention.
Detailed Description
The drawings are only for purposes of illustration and are not to be construed as limiting the invention. For the purpose of better illustrating the following embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
Example 1
The embodiment is a method for detecting consistency based on terahertz quantum fingerprint spectra, and a terahertz time-domain detector is adopted, namely a TDS is used for respectively detecting a sample and a reference substance in a transmission or reflection mode, so that a terahertz time-domain spectrum of the sample is shown in fig. 1, and a terahertz time-domain spectrum of the reference substance is shown in fig. 2. Through the mode of graph superposition comparison, as shown in fig. 3, the distinguishing characteristics of the two under the terahertz time-domain spectrum are not obvious, and the two curves are overlapped visually, so that the differences cannot be distinguished.
Further, after fourier transform, the terahertz frequency domain spectrum of the sample is obtained as shown in fig. 4, and the terahertz frequency domain spectrum of the reference is obtained as shown in fig. 5, as can be seen from fig. 4 and 5, the peaks of the two curves are disordered and appear in irregular waves, and the curves are greatly changed and have disordered characteristics. By means of graph superposition comparison, as shown in fig. 6, although the difference change appears after the superposition, the terahertz frequency domain spectrum cannot be distinguished by naked eyes at all.
As shown in fig. 20, taking the thz frequency domain spectrum of the sample as an example, the thz frequency domain spectrum curve is divided into 2000 points corresponding to different frequencies, and then the peak position, peak height, peak area, and half-peak width information of each point are extracted, and the same operation is performed on the reference. Then, further dividing the terahertz wave into continuous frequency bands with the same interval, wherein 15 points are arranged in each interval, and the terahertz response value of the first point from left to right in each frequency band is taken as the peak height; as shown in fig. 10, the product of the number of points in the frequency band and the peak height is taken as the peak area; the fixed constant is 200, and the half-peak width is 15/200. Converting the curve shape in the frequency band into a quasi-rectangle, wherein the maximum value of the quasi-rectangle corresponding to a longitudinal axis is the peak height, namely the length of the rectangle parallel to a longitudinal coordinate is the peak height, and the distance of the quasi-rectangle on a transverse axis is half-peak width, namely the width of the rectangle parallel to a transverse coordinate is half-peak width; terahertz quantum fingerprint spectrums of the sample and the reference substance are formed respectively, and fig. 4 corresponds to fig. 7, and fig. 5 corresponds to fig. 8. And then extracting data corresponding to fig. 7 and 8, namely peak height, peak area and half-peak width information of the quantum peak of each frequency band, and calculating and obtaining qualitative similarity, quantitative similarity and difference coefficient of the sample and the reference substance, thereby performing overall consistency analysis.
Through the comparison of the graphics overlay, as shown in fig. 9, the numbers on the graph correspond to the numbers of each frequency band, and after the graphics overlay, it can be clearly seen from the distance between two peak points in each frequency band that some frequency bands have obvious differences, for example, the frequency band with the number of 17. Then, all main difference frequency bands of the sample and the reference substance are arranged, local consistency analysis is carried out through comparison of information of peak positions, peak heights, peak areas and half peak widths of all points in the main difference frequency bands in the corresponding data of the sample and the reference substance, and the overall consistency analysis and the local consistency analysis are combined to form consistency evaluation of traditional Chinese medicine detection.
Example 2
Grinding two traditional Chinese medicines to be detected, namely the wrinkled giant hyssop and the red tangerine peel into powder respectively, weighing 200-400mg of samples respectively after the particle size of the ground powder is not more than 100 mu m, adding polyethylene or PTFE to prepare mixed powder of 5-30% of the traditional Chinese medicines to be detected in percentage by mass, and preparing the detection sheet by 1-10t of pressure. A terahertz time-domain detector is adopted to detect the two slices respectively in a transmission mode, the obtained terahertz time-domain spectrums of the agastache rugosa and the exocarpium citri rubrum are respectively shown in the graph 11 and the graph 12, and then the corresponding terahertz frequency-domain spectrums are respectively shown in the graph 13 and the graph 14 through Fourier transform. Fig. 13 and 14 are then divided, replacing fig. 13 and 14, respectively, with said pattern of dots.
Dividing the two graphs consisting of points into 68 frequency bands, wherein each interval has 30 points, and the terahertz response value with the largest numerical value in the points in the frequency bands is taken as the peak height; and taking the sum of terahertz response values of all points in the frequency band as a peak area. The fixed constant is 200, and the half-peak width is 30/200. As shown in fig. 18, corresponding points in a frequency band are converted into chromatographic peaks with the same peak height, peak area and half-peak width, so that the curves of fig. 13 and 14 are converted into terahertz quantum fingerprint spectrograms 15 and 16 expressed by chromatographic curves. Then, data corresponding to fig. 15 and 16, that is, information of peak height, peak area, and half-peak width of the quantum peak of each frequency band is extracted, and qualitative similarity, quantitative similarity, and difference coefficient of the sample and the reference are calculated, so as to perform overall consistency analysis.
Next, by comparing the graphs in the superimposed manner, as shown in fig. 17, the numbers on the graph correspond to the numbers of each frequency band, and the difference existing between fig. 15 and fig. 16 can be clearly seen through the interval between the two peak points after the graphs are superimposed, for example, in the frequency band with the number of 26, the obvious interval exists between the two peak points. Then, all main difference frequency bands of the exocarpium citri rubrum and the agastache rugosus are sorted out, local consistency analysis is carried out through comparison of information of peak positions, peak heights, peak areas and half peak widths of all points in the main difference frequency bands in the corresponding data of the sample and the reference substance, and the overall consistency analysis and the local consistency analysis are combined to form consistency evaluation of traditional Chinese medicine detection.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the technical solutions of the present invention, and are not intended to limit the specific embodiments of the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention claims should be included in the protection scope of the present invention claims.
Claims (10)
1. A consistency detection method based on terahertz quantum fingerprint spectrum is characterized by comprising the following steps:
s1, detecting a sample by using a terahertz time-domain detector to obtain a terahertz time-domain spectrum, and outputting a terahertz frequency-domain spectrum and corresponding data through Fourier transform;
s2, dividing a continuous curve of the terahertz frequency domain spectrum into continuously arranged points, wherein the interval between two adjacent points is equal and minimum, the two points cannot be divided again, and a graph formed by point recombination is matched with the curve;
s3, dividing the graph into a plurality of continuous frequency bands, combining and assigning information of peak positions, peak heights, peak areas and half peak widths of all points in the frequency bands to form corresponding quantum peaks, and recombining the quantum peaks of all the frequency bands to form a terahertz quantum fingerprint spectrum;
and S4, adopting the terahertz quantum fingerprint spectrum and corresponding data to analyze the consistency of the sample and the reference substance.
2. The consistency detection method based on the terahertz quantum fingerprint spectrum as claimed in claim 1, wherein each frequency band has the same number of points, and each point belongs to only one frequency band; the intervals of each frequency band are equal, the points in the frequency bands are sequentially arranged from left to right, and the corresponding frequencies are from small to large.
3. The consistency detection method based on the terahertz quantum fingerprint spectrum according to claim 2, wherein in the step S3, peak position, peak height, peak area and half-peak width information of each point in a frequency band are merged and assigned to form a corresponding quantum peak, and the method specifically comprises the following steps:
s311, taking a terahertz response value of a first point from left to right in a frequency band as the peak height of a quantum peak;
s312, taking the product of the number of the points in the frequency band and the peak height as the peak area of the quantum peak;
and S313, dividing the number of the points in the frequency band by a fixed constant to obtain the half-peak width of the quantum peak.
4. The consistency detection method based on the terahertz quantum fingerprint spectrum is characterized in that the waveform of the quantum peak is similar to a rectangle, the maximum value of the similar rectangle corresponding to a longitudinal axis is the peak height of the quantum peak, and the distance of the similar rectangle on a horizontal axis is the half-peak width of the quantum peak; the terahertz quantum fingerprint spectrum expressed by square waves is formed.
5. The terahertz quantum fingerprint spectrum-based consistency detection method as claimed in claim 2, wherein in step S3, the peak position, peak height, peak area and half-peak width information of each point in the frequency band are merged and assigned to form a corresponding quantum peak, and the method specifically comprises the following steps:
s321, taking the terahertz response value of the last point arranged in the frequency band as the peak height of a quantum peak;
s322, taking the sum of terahertz response values of all points in a frequency band as the peak area of a quantum peak;
and S323, dividing the number of the points in the frequency band by a fixed constant to obtain the half-peak width of the quantum peak.
6. The consistency detection method based on the terahertz quantum fingerprint spectrum according to claim 2, wherein in step S3, peak position, peak height, peak area and half-peak width information of each point in a frequency band are merged and assigned to form a corresponding quantum peak, and the method specifically comprises the following steps:
s331, taking the maximum terahertz response value in the point in the frequency band as the peak height of a quantum peak;
s332, taking the sum of terahertz response values of all points in a frequency band as a peak area of a quantum peak;
and S333, dividing the number of the points in the frequency band by a fixed constant to obtain the half-peak width of the quantum peak.
7. The method according to any one of claims 5 or 6, wherein the quantum peak is displayed as a chromatographic peak, the pattern within a frequency band is converted into a chromatographic peak with the same peak height, peak area and half peak width, and the pattern is converted into a terahertz quantum fingerprint expressed by a chromatographic outflow curve.
8. The consistency detection method based on the terahertz quantum fingerprint spectrum according to any one of claims 1 to 6, wherein the number of the frequency bands is within 100.
9. The method for detecting the consistency based on the terahertz quantum fingerprint spectrum according to any one of claims 3, 5 and 6, wherein the fixed constant is 0.9-0.11 times of the total number of points in the graph.
10. A traditional Chinese medicine detection method is characterized by comprising the following steps:
s41, preparing the traditional Chinese medicine to be detected and the comparative traditional Chinese medicine into a sample and a reference substance respectively;
s42, detecting the sample and the reference substance by using a terahertz time-domain detector to obtain terahertz time-domain spectrums of the sample and the reference substance;
s43, adopting the consistency detection method based on the terahertz quantum fingerprint spectrum of any one of claims 1 to 9 to respectively obtain the terahertz quantum fingerprint spectrum and corresponding data of the sample and the reference;
s44, calculating and obtaining qualitative similarity, quantitative similarity and difference coefficient of the sample and the reference product according to peak height, peak area and half-peak width information of the quantum peak of each frequency band in the corresponding data, and thus carrying out overall consistency analysis; obtaining main difference frequency bands of the sample and the reference through comparison of terahertz quantum fingerprint spectrums, carrying out local consistency analysis through comparison of peak position, peak height, peak area and half-peak width information of each point in the main difference frequency bands in the corresponding data of the sample and the reference, and combining the whole consistency analysis and the local consistency analysis to form consistency evaluation of traditional Chinese medicine detection.
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