CN114384039A - Cigarette charging uniformity detection method based on spectral projection residual error - Google Patents
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- 235000019504 cigarettes Nutrition 0.000 title claims abstract description 60
- 230000003595 spectral effect Effects 0.000 title claims abstract description 46
- 238000001514 detection method Methods 0.000 title claims abstract description 26
- 241000208125 Nicotiana Species 0.000 claims abstract description 102
- 235000002637 Nicotiana tabacum Nutrition 0.000 claims abstract description 102
- 239000011159 matrix material Substances 0.000 claims abstract description 69
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 62
- 238000001228 spectrum Methods 0.000 claims abstract description 58
- 238000000513 principal component analysis Methods 0.000 claims abstract description 14
- 238000007781 pre-processing Methods 0.000 claims abstract description 10
- 238000000034 method Methods 0.000 claims description 42
- 239000000463 material Substances 0.000 claims description 3
- 238000011426 transformation method Methods 0.000 claims description 3
- 239000007788 liquid Substances 0.000 description 16
- DNIAPMSPPWPWGF-UHFFFAOYSA-N Propylene glycol Chemical compound CC(O)CO DNIAPMSPPWPWGF-UHFFFAOYSA-N 0.000 description 12
- 230000008569 process Effects 0.000 description 10
- 125000006850 spacer group Chemical group 0.000 description 7
- 229960004063 propylene glycol Drugs 0.000 description 6
- 230000008859 change Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
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- 238000004445 quantitative analysis Methods 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 239000000654 additive Substances 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
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- 230000000694 effects Effects 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
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- 238000005457 optimization Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
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- 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
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Abstract
The invention discloses a cigarette charging uniformity detection method based on spectral projection residual errors, which comprises the following steps: acquiring a near infrared spectrum of a tobacco shred sample before feeding to obtain a first near infrared spectrum; acquiring 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 error; and judging the charging uniformity of the cigarettes by using the projection residual errors. The invention can realize simple, quick and efficient detection of the cigarette feeding uniformity.
Description
Technical Field
The invention relates to the technical field of near infrared spectrum analysis, in particular to a cigarette charging uniformity detection method based on spectrum projection residual errors.
Background
The tobacco leaf charging is a process for spraying feed liquid on tobacco leaves in the cigarette production process. The feeding has the functions of improving the quality of cigarettes and the physical properties of tobacco leaves, and the uniformity of the feeding is an important factor influencing the quality of the cigarettes. In order to objectively evaluate the uniformity degree of the feed liquid application in the cigarette feeding process, a rapid and practical cigarette feeding uniformity detection method needs to be established so as to accurately and efficiently evaluate the uniformity degree 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, and specifically discloses a method for analyzing sample spectral data by applying a principal component method (PCA), establishing a prediction model of 1, 2-propylene glycol through modeling and optimization by a partial least squares method (PLS), and measuring the content of 1, 2-propylene glycol in a cigarette production process through the prediction model. The detection method relates to the establishment of a near-infrared quantitative analysis model, and has the advantages of more complex steps and lower detection efficiency.
Disclosure of Invention
The invention aims to solve the technical problems of complexity and low efficiency of a cigarette charging uniformity detection method. The invention provides a cigarette feeding uniformity detection method based on spectral projection residual errors, which can realize quick and accurate detection of cigarette feeding uniformity.
In order to solve the technical problem, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectral projection residual errors, which comprises the following steps: acquiring a near infrared spectrum of a tobacco shred sample before feeding to obtain a first near infrared spectrum; acquiring 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 error; and judging the charging uniformity of the cigarettes by using the projection residual errors.
The method is based on the near infrared spectrum technology, the near infrared spectrum of the tobacco shreds before feeding is utilized to construct a spectrum space, the near infrared spectrum of the tobacco shreds after feeding is projected onto the space, and the uniformity of cigarette feeding is judged through spectrum projection residual errors. According to the method, a near-infrared quantitative analysis model does not need to be established, the charging uniformity can be judged by comparing the difference of the near-infrared spectrums of the tobacco shred samples before and after charging, and the method is simple, rapid and efficient.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette charging uniformity detection method based on a spectrum projection residual error, and the method for judging the charging uniformity of a cigarette by using the projection residual error comprises the following steps:
according to x | | yly||2A two-norm of the projection residual is calculated,
where x represents the two-norm of the projection residual, ylyRepresenting the projection residual;
according to
Calculating the uniformity coefficient of the feeding materials,
wherein CU represents the charging uniformity coefficient, n represents the number of the collected tobacco shred samples after charging, and xiRepresenting the two-norm of the projected residual of the tobacco sample after the ith charge,
the mean value of the projection residual two norms of n tobacco shred samples after charging.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette feeding uniformity detection method based on spectral projection residuals, and the feeding uniformity of tobacco shred samples after feeding is judged and compared according to the value of a feeding uniformity coefficient CU.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette feeding uniformity detection method based on spectral projection residuals, and the pretreatment adopts a standard normal variable transformation method.
According to another specific implementation mode of the invention, the implementation mode of the invention discloses a cigarette charging uniformity detection method based on spectral projection residuals, the method comprises the following steps of performing principal component analysis on a first spectral matrix to obtain principal component factors, and constructing the first spectral projection matrix according to the principal component factors:
performing principal component analysis on the first spectrum matrix to obtain the number of principal components, and selecting a score matrix and a load matrix corresponding to the first q number of principal components;
according to
A third spectral matrix is constructed which is,
wherein, XbnewRepresenting a third spectral matrix, PqRepresents a score matrix, LqRepresenting a load matrix;
according to
A first spectral projection matrix is constructed,
wherein H represents a first spectral projection matrix, I represents an identity matrix,
representing a third spectral matrix XbnewThe generalized inverse matrix of (2).
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectral projection residual errors, and according to yly＝HysObtaining a projection residual, wherein ylyRepresenting the projection residual, ysRepresenting a second spectrum.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectral projection residual errors, and the method further comprises the following steps before the near infrared spectrum of the tobacco shred sample before charging is acquired: collecting tobacco leaves before feeding, and preparing the tobacco leaves before feeding into tobacco shreds before feeding; the method also comprises the following steps before the near infrared spectrum of the tobacco shred sample after charging is collected: and (4) collecting the tobacco leaves after feeding according to a preset time interval, wherein the preset time interval is 4 minutes, and preparing the tobacco leaves after feeding into the cut tobaccos after feeding.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette feeding uniformity detection method based on spectral projection residual errors, and the number of tobacco shred samples after feeding is more than or equal to 30.
According to another specific embodiment of the invention, the embodiment of the invention discloses a cigarette charging uniformity detection method based on spectral projection residual errors, and the width of tobacco shreds before charging and/or tobacco shreds after charging is 1.0 +/-0.1 mm.
Drawings
FIG. 1 shows a flow chart of a method for detecting the uniformity of cigarette charging based on spectral projection residuals according to the present invention;
FIG. 2 illustrates the position of the nozzle spacer and the valve core of the feeder according to an embodiment of the present invention;
FIG. 3 shows a near infrared spectrum of a cut tobacco sample before and after loading in accordance with an embodiment of the present invention;
FIG. 4 shows a near-infrared spectrum of a tobacco sample pre-processed using standard normal variable transformation before and after loading in accordance with an embodiment of the present invention;
FIG. 5 shows a projected residual plot of tobacco samples before and after loading with a spacer and valve element positioned in a third set according to an embodiment of the present invention;
FIG. 6 shows the projected residual error of tobacco samples before and after loading when the position of the spacer and the valve core are set to the third set according to an embodiment of the present invention;
FIG. 7 shows the uniformity of the charge at different positions for the sleeve and core of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure. While the invention will be described in conjunction with the preferred embodiments, it is not intended that features of the invention be limited to these embodiments. On the contrary, the invention is described in connection with the embodiments for the purpose of covering alternatives or modifications that may be extended based on the claims of the present invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be practiced without these particulars. Moreover, some of the specific details have been left out of the description in order to avoid obscuring or obscuring the focus of the present invention. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
It should be noted that in this specification, like reference numerals and letters refer to like items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.
The terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
In the description of the present embodiment, it should be further noted that, unless otherwise explicitly specified and limited, the term "disposed" is to be understood in a broad sense, and the specific meaning of the above terms in the present embodiment can be specifically understood by those skilled in the art.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
FIG. 1 is a flow chart of the cigarette charging uniformity detection method provided by the invention. As shown in fig. 1, the invention provides a cigarette charging uniformity detection method based on spectral projection residual errors, which comprises the following steps:
in step S101, acquiring a near infrared spectrum of a tobacco shred sample before feeding to obtain a first near infrared spectrum;
in the step, near infrared spectrums of a plurality of tobacco shred samples before feeding are collected, namely a first near infrared spectrum is composed of spectrums of a series of tobacco shred samples before feeding, and specifically, spectrum collection parameters comprise wavelength scanning range, resolution and scanning times.
In step S102, acquiring a near infrared spectrum of the tobacco shred sample after feeding to obtain a second near infrared spectrum;
in the step, the near infrared spectrums of the plurality of charged tobacco shred samples are collected, namely, the second near infrared spectrum is composed of spectrums of a series of charged tobacco shred samples, and specifically, the spectrum collection parameters comprise wavelength scanning range, resolution and scanning times.
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 error;
in the step, the second spectrum is composed of a series of spectrums of the preprocessed charged tobacco shred samples, and the second spectrums of the series of charged tobacco shred samples are projected to the first spectrum projection matrix.
In step S105, the charging uniformity of the cigarette is determined by using the projection residual.
Specifically, a Thermo Antaris II Fourier near infrared spectrometer (purchased from Thermo Scientific) is used for collecting near infrared spectrums of the tobacco shred samples before and after feeding. In the spectrum collection process, the relative humidity of the environment is controlled to be 20-80%, the environment temperature is controlled to be 18-26 ℃, the preheating time of the near-infrared spectrometer after starting up is not less than 1 hour, and then the near-infrared spectrum of the tobacco shred sample is collected after the self-checking program of the spectrometer is used for checking the tobacco shred sample to be qualified. Taking a proper amount of cut tobacco and placing the cut tobacco in a sample cup, wherein the acquisition parameters of a near-infrared spectrometer are set as follows: the wavelength scanning range is 4000-10000cm-1Resolution of 8cm-1The tobacco sample was scanned 64 times.
By adopting the technical scheme, the cigarette charging uniformity can be quickly and accurately detected, and the method can be applied to the actual production process of cigarette charging.
As an embodiment of the invention, the method for judging the charging uniformity of the cigarette by using the projection residual error comprises the following steps:
according to x | | yly||2A two-norm of the projection residual is calculated,
where x represents the two-norm of the projection residual, ylyRepresenting the projection residual;
according to
Calculating the uniformity coefficient of the feeding materials,
wherein CU represents the charging uniformity coefficient, n represents the number of the collected tobacco shred samples after charging, and xiRepresenting the two-norm of the projected residual of the tobacco sample after the ith charge,
the mean value of the projection residual two norms of n tobacco shred samples after charging. 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 representing the feeding uniformity.
According to one embodiment of the invention, the feeding uniformity of the tobacco shred samples after feeding is judged and compared according to the numerical value of the feeding uniformity coefficient CU. Specifically, the feeding uniformity of the tobacco shred samples under different settings of the feeding machine is judged by collecting the fed tobacco shred samples under different settings of the feeding machine and comparing the feeding uniformity coefficient CU of the tobacco shred samples with the values. It should be noted that the different settings of the feeder refer to different positions of the valve core and the spacer of the nozzle of the feeder. The cigarette raw material does not contain 1, 2-propylene glycol, 1, 2-propylene glycol is added into the feed liquid and serves as a marker, the content of the 1, 2-propylene glycol is measured on a plurality of fed tobacco shreds, a feeding uniformity coefficient CU is calculated, the feeding uniformity is reflected by the value of the feeding uniformity coefficient CU, and the larger the CU value is, the better the feeding uniformity of the cigarette corresponding to the tobacco shreds is.
As an embodiment of the present invention, the pre-processing of the first near infrared spectrum and the second near infrared spectrum employs a standard normal variable transformation (SNV) method for eliminating the influence of solid particle size, surface scattering, and optical path length change on the near infrared diffuse reflection spectrum, and reducing the measurement error. The formula for calculating the standard normal variable transformation (SNV) is as follows:
wherein y is the near infrared spectrum of the sample, ysIn order to obtain a pre-processed sample spectrum,
m is the number of wavelength points, k is 1,2, …, m.
As an embodiment of the present invention, the principal component analysis of the first spectral matrix by the orthogonal transformation method to obtain the principal component factors, and the construction of the first spectral projection matrix according to the principal component factors includes the following steps:
principal component analysis is carried out on the first spectrum matrix to obtain the number of principal components, and the first q number of principal components are selected to construct a corresponding scoring matrix PqAnd a load matrix Lq；
According to
A third spectral matrix is constructed which is,
wherein, XbnewRepresenting a third spectral matrix, PqRepresents a score matrix, LqRepresenting a load matrix;
according to
A first spectral projection matrix is constructed,
wherein H represents a first spectral projection matrix, I represents an identity matrix,
representing a third spectral matrix XbnewThe generalized inverse matrix of (2).
Principal Component Analysis (PCA) is a statistical method for calculating the number of Principal components in a first spectral matrix and the cumulative contribution of each Principal component to determine the PrincipalThe accumulated contribution rate of the first q principal components in the component numbers at least reaches more than 99.50 percent, and then a scoring matrix P corresponding to the first q principal components is selectedqAnd a load matrix Lq. A group of variables with correlation is converted into a group of linearly uncorrelated variables through orthogonal transformation, and the converted group of variables are principal components. We take only the first q principal components factors to construct the third spectral matrix XbnewAnd the influence of instrument errors and noise is eliminated. Further, the number q of the selected principal component factors in the embodiment of the present invention is 10.
According to y as an embodiment of the present inventionly＝HysObtaining a projection residual, wherein ylyRepresenting the projection residual, ysRepresenting a second spectrum, i.e. a second spectrum ysProjecting to a first spectrum projection matrix H, and calculating to obtain a projection residual y of the spectrumlyThe spectral information of the feed liquid is obtained.
As an embodiment of the invention, before acquiring the near infrared spectrum of the cut tobacco sample before feeding, the method further comprises the following steps: collecting tobacco leaves before feeding, and preparing the tobacco leaves before feeding into tobacco shreds before feeding; the method also comprises the following steps before the near infrared spectrum of the tobacco shred sample after charging is collected: and (4) collecting the tobacco leaves after feeding according to a preset time interval, wherein the preset time interval is 4 minutes, and preparing the tobacco leaves after feeding into the cut tobaccos after feeding. The tobacco leaves before feeding are collected at the inlet of the feeding process, and the tobacco leaves after feeding are sequentially collected at the outlet of the feeding process at a time interval of 4 minutes, so that 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 feeding machine, the time interval of sampling before and after feeding is determined to be 3 minutes and 21 seconds, namely after the time interval of 3 minutes and 21 seconds, the tobacco leaves run from the inlet of the feeding process to the outlet of the feeding process. As an embodiment of the invention, the number of the samples of the cut tobacco after feeding is more than or equal to 30, namely the collected near infrared spectrum times of the cut tobacco after feeding is not less than 30.
Specifically, 11 parts of tobacco shreds before feeding are collected, 11 parts of tobacco shreds after feeding are collected in sequence according to a preset time interval, each part of tobacco shreds is divided into 6 samples, and 1-time near infrared spectrum is collected for each sample, namely the near infrared spectrum of the tobacco shreds before feeding is collected for 66 times, and the near infrared spectrum of the tobacco shreds after feeding is collected for 66 times.
As an embodiment of the invention, the width of the cut tobacco 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 at different positions are collected by adjusting the positions of the nozzle valve core 1 and the spacer sleeve 2 of the feeder. The change of the position of the intermediate sleeve 2 causes the change of the area of the injection medium channel, thereby influencing the flow of the injection medium; the change of the position of the valve core 1 influences the thickness of a liquid film formed by the feed liquid at the nozzle of the feeder. As shown in figure 2, by arranging the positions of a valve core 1 and a spacing sleeve 2 of a feeder nozzle, the direction of a plus value to an ejection outlet is a positive value, and the direction of a minus value to the opposite direction is a negative value, the positions of the spacing sleeve 2 and the valve core 1 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 leaf samples are respectively collected under each group, wherein 11 tobacco leaf samples are obtained before feeding, 11 tobacco leaf samples are obtained after feeding, a sampling tool is used for collecting the tobacco leaf samples, the influence on the detection result caused by grabbing by hands is avoided, the tobacco leaf samples are put into a sealed container and marked, each sample is about 100g, each tobacco leaf sample is prepared into cut tobacco serving as a sample to be detected, the near infrared spectrum is collected, each sample is collected 6 times, and as shown in fig. 3, a first near infrared spectrum of the tobacco shred sample before feeding and a second near infrared spectrum of the tobacco shred sample after feeding are obtained.
Specifically, the feed liquid contains a hydroxyl compound, and the hydroxyl contains a functional group which can absorb in a near-infrared spectrum region, so that the near-infrared spectrum of the cigarette can be changed after the feed liquid is applied to the cigarette, and as shown in fig. 3, compared with a first near-infrared spectrum of a tobacco shred sample before feeding, a base line of a second near-infrared spectrum of the tobacco shred sample after feeding is shifted upwards. The first spectrum matrix and the second spectrum are obtained after the near infrared spectrum is preprocessed by a standard normal variable transform (SNV), and as shown in figure 4, the influence of a base line on the near infrared spectrum is reduced. The first approximation can be derived from fig. 4The change of the spectrum peak of the infrared spectrum and the second near infrared spectrum is mainly reflected in 7000-6900 cm-1、5400～4440cm-1And (4) a region. As shown in fig. 5, taking the projection residuals under the third set of feeder nozzle parameters as an example, performing principal component analysis on the first spectrum matrix, obtaining 10 principal component factors through orthogonal transformation, selecting the 10 principal component factors to construct a spectrum matrix before feeding, i.e. a first spectrum projection matrix H, and obtaining a series of second spectra y of the tobacco shred sample after feedingsPerforming projection calculation on the first spectrum projection matrix H to obtain a corresponding projection residual spectrum yly. The two-norm of the projection residuals is calculated, as shown in fig. 6, which reflects the magnitude of the projection residuals under the third set of feeder nozzle parameter settings. Observing the influence of the nozzle parameter setting of the feeder, namely the positions of the valve core 1 and the spacer 2, on the cigarette feeding uniformity, as shown in fig. 7, the feeding uniformity coefficient applied to the cigarette feed liquid under the nozzle parameter setting of the first group (-1, 0) feeder is 0.922, the feeding uniformity coefficient applied to the cigarette feed liquid under the nozzle parameter setting of the second group (-1, 1.5) feeder is 0.879, the feeding uniformity coefficient applied to the cigarette feed liquid under the nozzle parameter setting of the third group (0, 0) feeder is 0.935, and the feeding uniformity coefficient applied to the cigarette feed liquid under the nozzle parameter setting of the fourth group (0, 1.5) feeder is 0.903, so that the feeding uniformity is the best when the nozzle parameter setting of the third group feeder is (0, 0), namely the positions of the valve core 1 and the spacer 2 of the feeder.
The method disclosed by the invention is used for rapidly judging whether the cigarettes are fed or not based on the near infrared spectrum technology and obtaining the uniformity of the feed liquid application in the cigarette feeding process by the method of spectrum projection residual error, and the method is simple, rapid and efficient without obtaining a chemical detection value and establishing a near infrared quantitative analysis model, can be applied to the actual production process of cigarette feeding and can be used for effectively detecting the additives in the cigarette processing process according to the actual needs of the production process. Furthermore, the setting of the nozzle parameters of the feeder can be realized through the detection of the feeding uniformity, so that the most uniform position of the feed liquid is applied to the nozzle of the cigarette feeder, and the consistency of the quality of the cigarette products is effectively guaranteed.
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 more detailed description of the invention, taken in conjunction with the specific embodiments thereof, and that no limitation of the invention is intended thereby. Various changes in form and detail, including simple deductions or substitutions, may be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (9)
1. A cigarette charging uniformity detection method based on spectral projection residual errors is characterized by comprising the following steps:
acquiring a near infrared spectrum of a tobacco shred sample before feeding to obtain a first near infrared spectrum;
acquiring 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 error;
and judging the charging uniformity of the cigarette by using the projection residual error.
2. The method for detecting cigarette charging uniformity based on spectral projection residuals according to claim 1, wherein the step of judging the cigarette charging uniformity by using the projection residuals comprises the following steps:
according to x | | yly||2Calculating a two-norm of the projection residual,
where x represents the two-norm of the projection residual, ylyRepresenting the projection residual;
according to
Calculating the uniformity coefficient of the feeding materials,
wherein CU represents the charging uniformity coefficient, n represents the number of the collected tobacco shred samples after charging, and xiRepresenting the two-norm of the projected residual of the tobacco sample after the ith charge,
the mean value of the projection residual two norms of n tobacco shred samples after charging.
3. The method for detecting cigarette charging uniformity based on spectral projection residuals according to claim 2, wherein the charging uniformity of the tobacco shred samples after charging is judged and compared according to the value of the charging uniformity coefficient CU.
4. The method for detecting cigarette charging uniformity based on spectral projection residuals according to claim 1, wherein the preprocessing employs a standard normal variable transformation method.
5. The method for detecting cigarette charging uniformity based on spectral projection residuals according to claim 1, wherein the step of performing principal component analysis on the first spectral matrix to obtain principal component factors, and the step of constructing the first spectral projection matrix according to the principal component factors comprises the following steps:
performing principal component analysis on the first spectrum matrix to obtain the number of principal components, and selecting a score matrix and a load matrix corresponding to the first q number of principal components;
according to
A third spectral matrix is constructed which is,
wherein, XbnewRepresenting a third spectral matrix, PqRepresents the score matrix, LqRepresenting the load matrix;
according to
-constructing said first spectral projection matrix,
wherein H represents a first spectral projection matrix, I represents an identity matrix,
representing the third spectral matrix XbnewThe generalized inverse matrix of (2).
6. The method of claim 5, wherein the method comprises the steps of,
according to yly＝HysObtaining the projection residual error, and obtaining the projection residual error,
wherein, ylyRepresenting the projection residual, ysRepresenting the second spectrum.
7. The method of claim 1, wherein the method comprises the steps of,
the method also comprises the following steps before the near infrared spectrum of the tobacco shred sample before charging is collected: collecting tobacco leaves before feeding, and preparing the tobacco leaves before feeding into tobacco shreds before feeding;
the method also comprises the following steps before the step of collecting the near infrared spectrum of the tobacco shred sample after charging: and collecting the tobacco leaves after feeding according to a preset time interval, wherein the preset time interval is 4 minutes, and preparing the tobacco leaves after feeding into the cut tobacco after feeding.
8. The method for detecting cigarette charging uniformity based on spectral projection residuals according to claim 1, wherein the number of tobacco shred samples after charging is greater than or equal to 30.
9. The method for detecting cigarette charging uniformity based on spectral projection residuals, according to claim 1, wherein the width of the tobacco shreds before charging and/or the tobacco shreds after charging is 1.0 ± 0.1 mm.
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