CN114384039B - Cigarette feeding uniformity detection method based on spectrum projection residual error - Google Patents
Cigarette feeding uniformity detection method based on spectrum projection residual error Download PDFInfo
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- 238000001228 spectrum Methods 0.000 title claims abstract description 83
- 235000019504 cigarettes Nutrition 0.000 title claims abstract description 59
- 238000001514 detection method Methods 0.000 title claims abstract description 21
- 241000208125 Nicotiana Species 0.000 claims abstract description 100
- 235000002637 Nicotiana tabacum Nutrition 0.000 claims abstract description 100
- 239000011159 matrix material Substances 0.000 claims abstract description 69
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 61
- 238000000513 principal component analysis Methods 0.000 claims abstract description 12
- 238000007781 pre-processing Methods 0.000 claims abstract description 9
- 238000000034 method Methods 0.000 claims description 38
- 230000003595 spectral effect Effects 0.000 claims description 23
- 238000011426 transformation method Methods 0.000 claims description 5
- DNIAPMSPPWPWGF-UHFFFAOYSA-N Propylene glycol Chemical compound CC(O)CO DNIAPMSPPWPWGF-UHFFFAOYSA-N 0.000 description 12
- 239000007788 liquid Substances 0.000 description 11
- 229960004063 propylene glycol Drugs 0.000 description 6
- 230000008859 change Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 230000000694 effects Effects 0.000 description 4
- 230000009466 transformation Effects 0.000 description 4
- 238000005070 sampling Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000001186 cumulative effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- 239000011229 interlayer Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000004445 quantitative analysis Methods 0.000 description 2
- 125000006850 spacer group Chemical group 0.000 description 2
- 239000007921 spray Substances 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 125000000524 functional group Chemical group 0.000 description 1
- 125000002887 hydroxy group Chemical group [H]O* 0.000 description 1
- -1 hydroxyl compound Chemical class 0.000 description 1
- 239000003550 marker Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses a cigarette charging uniformity detection method based on spectrum projection residual errors, which comprises the following steps: collecting a near infrared spectrum of a cut tobacco sample before feeding to obtain a first near infrared spectrum; collecting a near infrared spectrum of the tobacco shred sample after feeding to obtain a second near infrared spectrum; preprocessing a first near infrared spectrum to obtain a first spectrum matrix, performing principal component analysis on the first spectrum matrix to obtain principal component factors, and constructing a first spectrum projection matrix according to the principal component factors; preprocessing a second near infrared spectrum to obtain a second spectrum, and projecting the second spectrum to a first spectrum projection matrix to obtain a projection residual; and judging the charging uniformity of the cigarettes by using the projection residual errors. The invention can realize simple, rapid and efficient detection of the uniformity of cigarette feeding.
Description
Technical Field
The invention relates to the technical field of near infrared spectrum analysis, in particular to a cigarette feeding uniformity detection method based on spectrum projection residual errors.
Background
The tobacco leaf feeding is a process of spraying feed liquid on tobacco leaves in the production process of cigarettes. The feeding has the effects of improving the quality of cigarettes and improving the physical properties of tobacco leaves, and the feeding uniformity is an important factor affecting the quality of cigarettes. In order to objectively evaluate the uniformity degree of the feed liquid application in the cigarette feeding process, a quick and practical cigarette feeding uniformity detection method needs to be established so as to accurately and efficiently evaluate the uniformity of the feed liquid application in the cigarette feeding process.
Patent CN102023140B discloses a method for measuring 1, 2-propylene glycol content by NIR technology, specifically discloses analyzing sample spectrum data by using principal component method (PCA), modeling and optimizing by Partial Least Squares (PLS), establishing a prediction model of 1, 2-propylene glycol, and measuring 1, 2-propylene glycol content in the cigarette production process by the prediction model. The detection method relates to the establishment of a near infrared quantitative analysis model, and has the advantages of complex steps and low detection efficiency.
Disclosure of Invention
The invention aims to solve the technical problems of complex and low-efficiency cigarette feeding uniformity detection method. The invention provides a method for detecting the uniformity of cigarette feeding based on spectrum projection residual errors, which can realize the rapid and accurate detection of the uniformity of cigarette feeding.
In order to solve the technical problems, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectrum projection residual errors, which comprises the following steps: collecting a near infrared spectrum of a cut tobacco sample before feeding to obtain a first near infrared spectrum; collecting a near infrared spectrum of the tobacco shred sample after feeding to obtain a second near infrared spectrum; preprocessing a first near infrared spectrum to obtain a first spectrum matrix, performing principal component analysis on the first spectrum matrix to obtain principal component factors, and constructing a first spectrum projection matrix according to the principal component factors; preprocessing a second near infrared spectrum to obtain a second spectrum, and projecting the second spectrum to a first spectrum projection matrix to obtain a projection residual; and judging the charging uniformity of the cigarettes by using the projection residual errors.
The invention is based on the near infrared spectrum technology, utilizes the near infrared spectrum of the tobacco shred before feeding to construct a spectrum space, projects the near infrared spectrum of the tobacco shred after feeding to the space, and judges the uniformity of cigarette feeding through the spectrum projection residual error. According to the method, a near infrared quantitative analysis model is not required to be established, and the uniformity of feeding can be judged by comparing the difference of near infrared spectrums of tobacco shred samples before and after feeding, so that the method is simple, quick and efficient.
According to another specific embodiment of the invention, the embodiment of the invention discloses a method for detecting the charging uniformity of cigarettes based on a spectrum projection residual, and the method for judging the charging uniformity of the cigarettes by using the projection residual comprises the following steps:
according to x= ||y ly || 2 The two norms of the projection residuals are calculated,
wherein x represents the two norms of the projection residual, y ly Representing a projection residual;
according toCalculating the uniformity coefficient of the feeding,
wherein CU represents a charging uniformity coefficient, n represents the number of collected tobacco shred samples after charging, and x i Representing the second norm of the projection residual of the ith post-addition tobacco sample,is the average value of the projection residual two norms of n fed tobacco shred samples.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette feeding uniformity detection method based on spectrum projection residual errors, and according to the value of a feeding uniformity coefficient CU, the feeding uniformity of tobacco shred samples after feeding is judged and compared.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette feeding uniformity detection method based on spectrum projection residual errors, and a standard normal variable transformation method is adopted for pretreatment.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette feeding uniformity detection method based on spectrum projection residual, which comprises the following steps of:
performing principal component analysis on the first spectrum matrix to obtain the number of principal components, and selecting a scoring matrix and a load matrix corresponding to the first q principal component numbers;
according toA third spectral matrix is constructed and a second spectral matrix is constructed,
wherein X is bnew Representing a third spectral matrix, P q Representing a scoring matrix, L q Representing a load matrix;
according toA first spectral projection matrix is constructed and,
wherein H represents a first spectral projection matrix, I represents an identity matrix,representing a third spectral matrix X bnew Is a generalized inverse matrix of (a).
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectrum projection residual errors, which is based on y ly ＝Hy s Obtaining projection residual error, wherein y ly Representing projection residual, y s Representing a second spectrum.
According to another specific embodiment of the invention, the embodiment of the invention discloses a method for detecting the uniformity of cigarette feeding based on spectrum projection residual errors, and the method further comprises the following steps before collecting the near infrared spectrum of a tobacco shred sample before feeding: collecting tobacco leaves before feeding, and preparing the tobacco leaves before feeding into tobacco shreds before feeding; the method comprises the following steps before collecting the near infrared spectrum of the tobacco shred sample after feeding: and collecting the fed tobacco leaves according to a preset time interval, wherein the preset time interval is 4 minutes, and preparing the fed tobacco leaves into fed tobacco shreds.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectrum projection residual errors, and the number of tobacco shred samples after charging is more than or equal to 30.
According to another specific embodiment of the invention, the embodiment of the invention discloses a method for detecting the uniformity of cigarette feeding based on a spectrum projection residual error, wherein the width of tobacco shreds before feeding and/or tobacco shreds after feeding is 1.0+/-0.1 mm.
Drawings
FIG. 1 shows a flow chart of a cigarette feed uniformity detection method based on spectral projection residuals of the present invention;
FIG. 2 illustrates the position of a feeder nozzle spacer and valve spool in accordance with an embodiment of the present invention;
FIG. 3 shows near infrared spectra of cut tobacco samples before and after addition in accordance with an embodiment of the present invention;
FIG. 4 shows a near infrared spectrum of a cut tobacco sample before and after feeding, which is pretreated by standard normal variable transformation according to an embodiment of the invention;
FIG. 5 shows a projected residual plot of tobacco samples before and after addition with the positions of the sleeve and valve element set to the third set in accordance with an embodiment of the present invention;
FIG. 6 shows the magnitude of projection residuals of tobacco samples before and after addition when the positions of the sleeve and the valve element are set to the third group according to an embodiment of the invention;
FIG. 7 shows the feed uniformity coefficient for the spacer and valve cartridge of the present invention at different positions.
Detailed Description
Further advantages and effects of the present invention will become apparent to those skilled in the art from the disclosure of the present specification, by describing the embodiments of the present invention with specific examples. While the description of the invention will be described in connection with the preferred embodiments, it is not intended to limit the inventive features to the implementation. Rather, the purpose of the invention described in connection with the embodiments is to cover other alternatives or modifications, which may be extended by the claims based on the invention. The following description contains many specific details for the purpose of providing a thorough understanding of the present invention. The invention may be practiced without these specific details. Furthermore, some specific details are omitted from the description in order to avoid obscuring the invention. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
It should be noted that in this specification, like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
The terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
In the description of the present embodiment, it should also be noted that the term "disposed" should be interpreted broadly unless explicitly stated and defined otherwise, and the specific meaning of the above terms in the present embodiment may be understood in a specific case by those skilled in the art.
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
Fig. 1 is a flow chart of a method for detecting uniformity of cigarette feeding provided by the invention. As shown in fig. 1, the invention provides a method for detecting the uniformity of cigarette feeding based on spectrum projection residual errors, which comprises the following steps:
in step S101, acquiring a near infrared spectrum of a cut tobacco sample before feeding to obtain a first near infrared spectrum;
in this step, a plurality of near infrared spectra of the tobacco shred samples before feeding are collected, namely, a first near infrared spectrum is composed of a series of spectra of the tobacco shred samples before feeding, specifically, the spectrum collection parameters comprise wavelength scanning range, resolution and scanning times.
In step S102, collecting a near infrared spectrum of a tobacco shred sample after feeding to obtain a second near infrared spectrum;
in this step, a plurality of near infrared spectra of the fed cut tobacco samples are collected, namely, the second near infrared spectrum is composed of a series of spectra of the fed cut tobacco samples, and specifically, the spectrum collection parameters include a wavelength scanning range, a resolution and a scanning frequency.
In step S103, preprocessing the first near infrared spectrum to obtain a first spectrum matrix, performing principal component analysis on the first spectrum matrix to obtain principal component factors, and constructing a first spectrum projection matrix according to the principal component factors;
in step S104, preprocessing the second near infrared spectrum to obtain a second spectrum, and projecting the second spectrum to the first spectrum projection matrix to obtain a projection residual;
in this step, the second spectrum is composed of a series of spectra of pretreated cut tobacco samples, and the second spectrum of the series of cut tobacco samples after being fed is projected to the first spectrum projection matrix.
In step S105, the projection residual is used to determine the uniformity of the cigarette charge.
Specifically, a Thermo antarii ii fourier near infrared spectrometer (purchased from Thermo Scientific company) was used to collect near infrared spectra of the cut tobacco sample before and after addition. In the spectrum acquisition process, the relative humidity of the environment is controlled between 20 and 80 percent, the temperature of the environment is controlled between 18 and 26 ℃, the startup preheating time of a near infrared spectrometer is not less than 1 hour, and then the near infrared spectrum of a cut tobacco sample is acquired after the self-checking program of the instrument is checked to be qualified. A proper amount of tobacco shreds are taken and placed in a sample cup, and acquisition parameters of a near infrared spectrometer are set as follows: the wavelength scanning range is 4000-10000cm -1 Resolution of 8cm -1 And (5) scanning the cut tobacco sample, wherein the scanning times are 64 times.
By adopting the technical scheme, the method can realize rapid and accurate detection of the uniformity of cigarette feeding, and can be applied to the actual production process of cigarette feeding.
As one embodiment of the present invention, determining the charge uniformity of a cigarette using a projection residual comprises the steps of:
according to x= ||y ly || 2 The two norms of the projection residuals are calculated,
wherein x represents the two norms of the projection residual, y ly Representing a projection residual;
according toCalculating the uniformity coefficient of the feeding,
wherein CU represents a charging uniformity coefficient, n represents the number of collected tobacco shred samples after charging, and x i Representing the second norm of the projection residual of the ith post-addition tobacco sample,is the average value of the projection residual two norms of n fed tobacco shred samples. The feeding uniformity refers to the consistency degree of the feed liquid content in the cigarettes after feeding, and the feeding uniformity coefficient is an index for representing the feeding uniformity.
According to the method, the feeding uniformity of the tobacco shred samples after feeding is judged and compared according to the value of the feeding uniformity coefficient CU. Specifically, tobacco shred samples after feeding under different settings of the feeder are collected and compared with the value of the CU (coefficient of uniformity) of the tobacco shred samples after feeding, so that the feeding uniformity of the tobacco shred samples under different settings of the feeder is judged. It should be noted that the different settings of the feeder refer to different positions of the valve core and the sleeve of the nozzle of the feeder. The raw material of the cigarette does not contain 1, 2-propylene glycol, 1, 2-propylene glycol is added into the feed liquid and is used as a marker, and the charging uniformity coefficient CU is calculated by measuring the content of 1, 2-propylene glycol in a plurality of fed cut tobaccos, wherein the value of the charging uniformity coefficient CU reflects the charging uniformity, and the larger the CU value is, the better the charging uniformity of the cigarette corresponding to the cut tobaccos is indicated.
As an embodiment of the present invention, the pretreatment of the first near infrared spectrum and the second near infrared spectrum adopts a standard normal variable transformation method (SNV, standard normal variate transformation) for eliminating the influence of solid particle size, surface scattering, optical path change and the like on the near infrared diffuse reflection spectrum, and reducing the measurement error. The calculation formula of the standard normal variable transformation method (SNV) is as follows:
where y is the near infrared spectrum of the sample, y s For the spectrum of the sample that has been pre-processed,m is the number of wavelength points, k=1, 2, …, m.
As one embodiment of the present invention, the method for obtaining principal component factors by principal component analysis of a first spectrum matrix by using an orthogonal transformation method, and constructing a first spectrum projection matrix according to the principal component factors, includes the steps of:
performing principal component analysis on the first spectrum matrix to obtain principal component numbers, and selecting the first q principal component numbers to construct a corresponding score matrix P q And a load matrix L q ；
According toA third spectral matrix is constructed and a second spectral matrix is constructed,
wherein X is bnew Representing a third spectral matrix, P q Representing a scoring matrix, L q Representing a load matrix;
according toA first spectral projection matrix is constructed and,
wherein H represents a first spectral projection matrix, I represents an identity matrix,representing a third spectral matrixX bnew Is a generalized inverse matrix of (a).
Principal component analysis (Principal ComponentAnalysis, PCA) is a statistical method, which comprises calculating Principal component number of the first spectral matrix and cumulative contribution rate of each Principal component, determining that the cumulative contribution rate of the first q Principal components in the Principal component number is at least 99.50%, and selecting score matrix P corresponding to the first q Principal component numbers q And a load matrix L q . And converting a group of variables with correlation into a group of variables with linear uncorrelation through positive-negative conversion, wherein the converted group of variables is the main component. We take only the first q principal component factors to construct a third spectral matrix X bnew Helping to eliminate the effects of instrument errors and noise. Further, the principal component factor q selected in the embodiment of the present invention is 10.
According to y as one embodiment of the present invention ly ＝Hy s Obtaining projection residual error, wherein y ly Representing projection residual, y s Representing the second spectrum, i.e. the second spectrum y s Projecting to a first spectrum projection matrix H, and calculating to obtain a projection residual y of the spectrum ly The spectrum information of the feed liquid is obtained.
As an embodiment of the present invention, the method further comprises the following steps before collecting the near infrared spectrum of the tobacco shred sample before feeding: collecting tobacco leaves before feeding, and preparing the tobacco leaves before feeding into tobacco shreds before feeding; the method comprises the following steps before collecting the near infrared spectrum of the tobacco shred sample after feeding: and collecting the fed tobacco leaves according to a preset time interval, wherein the preset time interval is 4 minutes, and preparing the fed tobacco leaves into fed tobacco shreds. Tobacco leaves before feeding are collected at the inlet of the feeding procedure, tobacco leaves after feeding are sequentially collected at the outlet of the feeding procedure at time intervals of 4 minutes, the influence of steady-state time fluctuation among different batches of test samples is avoided, and all sampling is ensured to be carried out in a steady-state. According to the running speed of the tobacco leaves on the feeder, the time interval of sampling before and after feeding is determined to be 3 minutes 21s, namely, the time interval of 3 minutes 21s is passed, and the tobacco leaves run from the inlet of the feeding procedure to the outlet of the feeding procedure. As one embodiment of the invention, the number of the fed tobacco shred samples is more than or equal to 30, namely the number of the acquired near infrared spectrum times of the fed tobacco shreds is not less than 30.
Specifically, 11 parts of tobacco shreds before feeding are collected, 11 parts of tobacco shreds after feeding are sequentially collected according to preset time intervals, each part of tobacco shreds is divided into 6 samples, and each sample is collected for 1 time with a near infrared spectrum, namely, the near infrared spectrum of the tobacco shred sample before feeding is collected for 66 times, and the near infrared spectrum of the tobacco shred sample after feeding is collected for 66 times.
As one embodiment of the invention, the width of the tobacco shreds before and/or after feeding is 1.0mm, and the error is not more than 0.1mm, so that the measurement error is as small as possible.
According to the invention, tobacco leaf samples before and after feeding in different positions are collected by adjusting the positions of the nozzle valve core 1 and the interlayer 2 of the feeding machine. The change of the position of the interlayer 2 causes the change of the area of the channel of the injection medium, thereby affecting the flow rate of the injection medium; the position change of the valve core 1 influences the thickness of a liquid film formed by the feed liquid at the nozzle of the feeding machine. As shown in FIG. 2, by setting the positions of the nozzle valve core 1 and the valve core 2 of the feeding machine, the direction of the spray outlet is positive, the direction of the spray outlet is negative, the positions of the valve core 1 and the valve core 2 of the feeding machine are respectively a first group (-1, 0), a second group (-1, 1.5), a third group (0, 0) and a fourth group (0, 1.5), 22 tobacco samples are respectively collected at each group, wherein 11 tobacco samples before feeding and 11 tobacco samples after feeding are collected by using a sampling tool, the detection result is prevented from being influenced by hand gripping, the tobacco samples are filled into a sealed container and marked, each sample is about 100g, each tobacco sample is prepared into tobacco as a sample to be detected, near infrared spectrum collection is carried out on each sample, and a first near infrared spectrum of the tobacco sample before feeding and a second near infrared spectrum of the tobacco sample after feeding are obtained as shown in FIG. 3.
Specifically, the liquid contains hydroxyl compound, and hydroxyl contains functional group capable of generating absorption in near infrared spectrum region, so that the change of near infrared spectrum of cigarette can be caused after the liquid is applied on cigarette, as shown in figure 3, compared with the first near infrared spectrum of tobacco sample before charging, the second near infrared spectrum of tobacco sample after chargingThe baseline of the spectrogram shifts upward. The first spectrum matrix and the second spectrum are obtained after the near infrared spectrum is preprocessed by a standard normal variable transformation (SNV), as shown in fig. 4, so that the influence of the base line on the near infrared spectrum is reduced. It can be seen from FIG. 4 that the variation of the spectral peaks of the first near infrared spectrum and the second near infrared spectrum is mainly reflected in 7000 to 6900cm -1 、5400～4440cm -1 An area. As shown in fig. 5, taking projection residual errors under the third group of feeder nozzle parameter setting as an example, performing principal component analysis on the first spectrum matrix, obtaining a principal component factor number of 10 through orthogonal transformation, selecting the 10 principal component factors to construct a spectrum matrix before feeding, namely a first spectrum projection matrix H, and obtaining a series of second spectrums y of the tobacco shred samples after feeding s Performing projection calculation on the first spectrum projection matrix H to obtain a corresponding projection residual spectrum y ly . The second norm of the projection residual is calculated, as shown in fig. 6, reflecting the magnitude of the projection residual at the third set of feeder nozzle parameter settings. Observing the effect of the feeder nozzle settings, i.e., the positions of the valve element 1 and the sleeve 2, on the uniformity of the cigarette feed, as shown in fig. 7, the feed uniformity coefficient applied by the cigarette feed at the first set (-1, 0) of feeder nozzle settings was 0.922, the feed uniformity coefficient applied by the cigarette feed at the second set (-1, 1.5) of feeder nozzle settings was 0.879, the feed uniformity coefficient applied by the cigarette feed at the third set (0, 0) of feeder nozzle settings was 0.935, and the feed uniformity coefficient applied by the cigarette feed at the fourth set (0, 1.5) of feeder nozzle settings was 0.903, so the feed uniformity was the best when the feed uniformity coefficient applied by the cigarette feed at the third set (0, 1.5) of feeder nozzle settings, i.e., the positions of the feeder nozzle valve element 1 and the sleeve 2, was (0).
The method is simple, quick and efficient, can be applied to the actual production process of cigarette feeding, and can be used for effectively detecting additives in the cigarette processing process according to the actual requirements of the production process. Further, the setting of the parameters of the nozzle of the feeding machine can be realized through the detection of the feeding uniformity, so that the nozzle of the cigarette feeding machine is adjusted to the position where the feed liquid is applied most uniformly, and the consistency of the quality of the cigarette products is effectively ensured.
While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those skilled in the art that the foregoing is a further detailed description of the invention with reference to specific embodiments, and it is not intended to limit the practice of the invention to those descriptions. Various changes in form and detail may be made therein by those skilled in the art, including a few simple inferences or alternatives, without departing from the spirit and scope of the present invention.
Claims (7)
1. The cigarette charging uniformity detection method based on the spectrum projection residual error is characterized by comprising the following steps of:
collecting a near infrared spectrum of a cut tobacco sample before feeding to obtain a first near infrared spectrum;
collecting a near infrared spectrum of the tobacco shred sample after feeding to obtain a second near infrared spectrum;
preprocessing the first near infrared spectrum to obtain a first spectrum matrix, performing principal component analysis on the first spectrum matrix to obtain principal component factors, and constructing a first spectrum projection matrix according to the principal component factors;
preprocessing the second near infrared spectrum to obtain a second spectrum, and projecting the second spectrum to the first spectrum projection matrix to obtain a projection residual, wherein the second spectrum consists of a series of preprocessed spectra of the fed tobacco shred samples;
judging the charging uniformity of the cigarettes by utilizing the projection residual errors,
principal component analysis is carried out on the first spectrum matrix to obtain principal component factors, and the first spectrum projection matrix is constructed according to the principal component factors, and the method comprises the following steps:
performing principal component analysis on the first spectrum matrix to obtain the number of principal components, and selecting a scoring matrix and a load matrix corresponding to the first q principal component numbers;
according toA third spectral matrix is constructed and a second spectral matrix is constructed,
wherein X is bnew Representing a third spectral matrix, P q Representing the scoring matrix, L q Representing the load matrix;
according toThe first spectral projection matrix is constructed and,
wherein H represents a first spectral projection matrix, I represents an identity matrix,representing the third spectral matrix X bnew Is a generalized inverse matrix of (a),
the method for judging the charging uniformity of the cigarettes by utilizing the projection residual errors comprises the following steps of:
according to x= ||y ly || 2 A two-norm of the projection residual is calculated,
wherein x represents the two norms of the projection residual, y ly Representing a projection residual;
according toCalculating the uniformity coefficient of the feeding,
wherein CU represents a charging uniformity coefficient, n represents the number of collected tobacco shred samples after charging, and x i Representing the second norm of the projection residual of the ith post-addition tobacco sample,is the average value of the projection residual two norms of n fed tobacco shred samples.
2. The method for detecting the uniformity of cigarette feeding based on the spectrum projection residual error according to claim 1, wherein the uniformity of feeding of the tobacco shred samples after feeding is judged and compared according to the value of the feeding uniformity coefficient CU.
3. The method for detecting the uniformity of cigarette feeding based on the spectrum projection residual error as in claim 1, wherein the preprocessing adopts a standard normal variable transformation method.
4. The method for detecting the uniformity of cigarette feeding based on the spectrum projection residual error as claimed in claim 1, wherein,
according to y ly ＝Hy s The projection residual is obtained and the projection residual is obtained,
wherein y is ly Representing the projection residual, y s Representing the second spectrum.
5. The method for detecting the uniformity of cigarette feeding based on the spectrum projection residual error as claimed in claim 1, wherein,
the method further comprises the following steps before the collection of the near infrared spectrum of the tobacco shred sample before feeding: collecting tobacco leaves before feeding, and preparing the tobacco leaves before feeding into tobacco shreds before feeding;
the method further comprises the following steps before the collection of the near infrared spectrum of the tobacco shred samples after feeding: and collecting the fed tobacco leaves according to a preset time interval, wherein the preset time interval is 4 minutes, and preparing the fed tobacco leaves into fed tobacco shreds.
6. The method for detecting the uniformity of cigarette feeding based on the spectrum projection residual error as claimed in claim 1, wherein the number of the tobacco shred samples after feeding is more than or equal to 30.
7. The method for detecting the uniformity of cigarette feeding based on the spectral projection residual error according to claim 1, wherein the width of the tobacco shred sample before feeding and/or the tobacco shred sample after feeding is 1.0+/-0.1 mm.
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