CN113033013A - Infrared smoke screen spectrum transmittance simulation method - Google Patents
Infrared smoke screen spectrum transmittance simulation method Download PDFInfo
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- CN113033013A CN113033013A CN202110376868.1A CN202110376868A CN113033013A CN 113033013 A CN113033013 A CN 113033013A CN 202110376868 A CN202110376868 A CN 202110376868A CN 113033013 A CN113033013 A CN 113033013A
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Abstract
The invention relates to the technical field of smoke screen spectral transmittance simulation analysis, and provides an infrared smoke screen spectral transmittance simulation method, which comprises the following steps: establishing a standardized matrix X of n smoke screen component data corresponding to m spectral bands, and determining p principal component vectors under m bands of the standardized matrix X; acquiring the spectral transmittance of infrared smoke screens of k typical wave bands, and determining a PC score subset of p principal component vectors corresponding to the k typical wave bands according to the spectral transmittance of the k typical wave bands, wherein the PC score is a correlation value of the p principal component vectors and each smoke screen component data; and determining the infrared smoke screen spectral transmittance of m spectral bands according to the p principal component vectors and the PC fraction subsets thereof, so that the infrared smoke screen spectral transmittance calculation efficiency can be improved, and the real-time simulation requirement can be met.
Description
Technical Field
The invention relates to the technical field of smoke screen spectral transmittance simulation analysis, in particular to an infrared smoke screen spectral transmittance simulation method.
Background
The spectral transmittance is an important index for evaluating the smoke shielding effect and is also an important physical quantity calculated in the real-time simulation of the interference characteristic. The smoke screen component is complex and comprises a plurality of gas and particulate matter components, and has strong spectral selectivity, so that the required spectral resolution is high when the spectral transmittance is calculated, and the calculation speed is greatly reduced.
Therefore, in view of the above disadvantages, it is desirable to provide an infrared smoke transmittance simulation method capable of improving the efficiency of calculating the infrared smoke transmittance and meeting the real-time simulation requirement.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an infrared smoke screen spectral transmittance simulation method aiming at the defects in the prior art, which can improve the infrared smoke screen spectral transmittance calculation efficiency and meet the real-time simulation requirement.
The technical problem to be solved by the present invention is to provide a method for simulating the spectrum transmittance of an infrared smoke screen, which includes:
establishing a standardized matrix X of n smoke screen component data corresponding to m spectral bands, and determining p principal component vectors under m bands of the standardized matrix X;
acquiring the spectral transmittance of infrared smoke screens of k typical wave bands, and determining a PC score subset of p principal component vectors corresponding to the k typical wave bands according to the spectral transmittance of the k typical wave bands, wherein the PC score is a correlation value of the p principal component vectors and each smoke screen component data;
and determining the infrared smoke screen spectral transmittance of m spectral bands according to the p principal component vectors and the PC fraction subsets thereof.
Further, the step of determining p principal component vectors in m bands of the normalized matrix X includes:
and determining the principal component y-AX, wherein A is an m X m matrix formed by arranging eigenvectors of a covariance matrix with dimension m X m of a data matrix X according to the size of the line eigenvalue in a descending order, and acquiring the first p principal component vectors in the order.
Further, the step of determining the subset of PC scores comprises:
calculating the PC score subset Y by the following expressionp×k：
Wp×Yp×k＝τk；
Wherein, WpIs the first p principal component vectors Y under m bandsp×mPC fraction of (d τ)kIs the spectral transmittance of the infrared smoke screen of k typical wave bands, wherein p < k < m.
Further, the step of determining the infrared smoke transmittance of m spectral bands includes:
calculating the infrared smoke screen spectral transmittance tau of the m spectral bands by the following expressionm：
Wp≈τk×Yp×k T；
τm≈Wp×Yp×m＝τk×Yp×k T×Yp×m；
Wherein, WpIs the first p principal component vectors Y under m bandsp×mPC fraction of (d), T represents the inverse matrix, τkIs the spectral transmittance of the infrared smoke screen of k typical wave bands, wherein p < k < m.
Optionally, the method for simulating the spectral transmittance of the infrared smoke screen provided by the invention further comprises:
and calculating the infrared smoke screen spectral transmittance of the k typical wave bands by a line-by-line calculation method.
Optionally, in the process of calculating the spectral transmittance of the infrared smoke screen of the k typical wave bands by a line-by-line calculation method, 100 segments are equally divided in the pressure range of 1atm to 12atm, 10 segments are equally divided in the temperature range of 0 ℃ to 500 ℃, and the method is based on CO2，H2O，H3PO4The absorption of Cu was calculated.
According to the infrared smoke screen spectral transmittance simulation method provided by the embodiment of the invention, spectral transmittance simulation is carried out based on a principal component analysis method, and the original group of related variables is replaced by a small number of irrelevant principal components by checking the linear relation among all variables contained in a multivariate data set, so that the purpose of reducing the dimension is achieved, the algorithm calculation speed is increased, the infrared smoke screen spectral transmittance calculation efficiency is improved, and the real-time simulation requirement is met.
Drawings
Fig. 1 is a schematic flow chart of a simulation method of infrared smoke transmittance according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Example one
As shown in fig. 1, the method for simulating the spectral transmittance of an infrared smoke screen according to the embodiment of the present invention includes the following steps S1 to S3.
In step S1, a normalization matrix X of n smoke component data corresponding to m spectral bands is created, and p principal component vectors in m bands of the normalization matrix X are determined. In this step, a principal component of a typical band is established, m bands are divided for the whole spectral band, the corresponding n smoke components form a data matrix X, and then a m m matrix A is formed by arranging eigenvectors of a covariance matrix with dimension of X being m m according to the size of row eigenvalues in a descending order. The dimensionality reduction is achieved by replacing the m original values with the first p principal components, i.e., determining the first p principal components as principal components of the associated band.
Specifically, assuming that our dataset consists of n path smoke components corresponding to m bands, they are arranged into an n × m data matrix X, i.e.:
X＝(X1，X2，X3，...，Xm)Twhere T denotes transposition.
With y representing the principal component having
y＝AX
Wherein, A is an m × m matrix formed by arranging eigenvectors of a covariance matrix with dimension of m × m of a data matrix X in descending order according to the size of a row eigenvalue, and the eigenvector represents the direction of the maximum variance in the data.
Thus, each principal component provides the largest variation for the last linear combination of bands. The principal components are orthogonal and uncorrelated, and their associated values (i.e., the decomposition coefficients) with the smoke screen on each path are referred to as PC scores. If λiIs the eigenvalue associated with the ith eigenvector, then
Will give the rate of change of the ith principal component description. By definition, since the matrix a is orthogonal, on the basis that the inverse of the orthogonal matrix is equal to its transpose, it can be written as:
X＝ATy
it can also be expressed in the form of a summation as:
where i represents the ith band value and j represents the smoke component value for the jth path. A number of p principal components less than m may generally represent most of the variation in the data. Then, we can achieve the goal of dimensionality reduction by replacing m original values with the first p principal components, i.e., determining the first p principal components as principal components of the relevant band.
In step S2, the infrared smoke transmittance of k typical bands is obtained, and a PC score subset of p principal component vectors corresponding to the k typical bands is determined according to the spectral transmittance of the k typical bands, where the PC score is a correlation value of the p principal component vectors and each smoke component data.
As shown in step S1, the first p principal components may contain most of the spectral information, so we can first calculate the transmittance τ of k typical bandsk。
By line-by-line countingThe infrared smoke transmittance of k typical wave bands is calculated, namely specific transmittance data calculation can be carried out in advance by a line-by-line calculation method (LBL) to establish a wave band lookup table. For the calculation of LBL, the pressure is divided into 100 segments from the range of 1atm to 12atm and 10 segments from the range of 0 to 500 deg.C, and then 4 typical gases and particles (CO) are considered2，H2O，H3PO4Cu) absorption.
First we know that there is a linear function relationship between the PC fraction and the band transmittance, so we can first calculate the first p principal component vectors Y under the whole spectrum, i.e. m bands, as shown in the first stepp×mThen, the PC score W is calculatedp：
Wp×Yp×k＝τk
Herein Yp×kIs a subset of the total principal component PC vector corresponding to k typical bands, k being typically less than m but greater than p, i.e., p < k < m. The inverse matrix is therefore reused to find a least squares solution of the above equation:
Wp≈τk×Yp×k T
where T represents the inverse matrix.
In step S3, the infrared smoke spectral transmittances for the m spectral bands are determined based on the p principal component vectors and their PC score subsets.
Step S3 widens the band to a full spectral range based on the first two steps. Let the transmission be tau for the whole complete spectrummThen, from the first two steps, there are:
τm≈Wp×Yp×m＝τk×Yp×k T×Yp×m
the transmittance in the complete spectral range can be obtained.
According to the infrared smoke screen spectral transmittance simulation method provided by the embodiment of the invention, spectral transmittance simulation is carried out based on a principal component analysis method, and the original group of related variables is replaced by a small number of irrelevant principal components by checking the linear relation among all variables contained in a multivariate data set, so that the purpose of reducing the dimension is achieved, the algorithm calculation speed is increased, the infrared smoke screen spectral transmittance calculation efficiency is improved, and the real-time simulation requirement is met.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. An infrared smoke screen spectrum transmittance simulation method is characterized by comprising the following steps:
establishing a standardized matrix X of n smoke screen component data corresponding to m spectral bands, and determining p principal component vectors under m bands of the standardized matrix X;
acquiring the spectral transmittance of infrared smoke screens of k typical wave bands, and determining a PC score subset of p principal component vectors corresponding to the k typical wave bands according to the spectral transmittance of the k typical wave bands, wherein the PC score is a correlation value of the p principal component vectors and each smoke screen component data;
and determining the infrared smoke screen spectral transmittance of m spectral bands according to the p principal component vectors and the PC fraction subsets thereof.
2. The method of infrared smoke screen spectral transmittance simulation of claim 1, wherein the step of determining p principal component vectors at m bands of a normalization matrix X comprises:
and determining the principal component y-AX, wherein A is an m X m matrix formed by arranging eigenvectors of a covariance matrix with dimension m X m of a data matrix X according to the size of the line eigenvalue in a descending order, and acquiring the first p principal component vectors in the order.
3. The infrared smoke spectral transmittance simulation method of claim 2, wherein the step of determining the subset of PC scores comprises:
calculating the PC score subset Y by the following expressionp×k：
Wp×Yp×k＝τk；
Wherein, WpIs the first p principal component vectors Y under m bandsp×mPC fraction of (d τ)kIs the spectral transmittance of the infrared smoke screen of k typical wave bands, wherein p < k < m.
4. The infrared smoke screen spectral transmittance simulation method of claim 3, wherein the step of determining the infrared smoke screen spectral transmittance of m spectral bands comprises:
calculating the infrared smoke screen spectral transmittance tau of the m spectral bands by the following expressionm：
Wp≈τk×Yp×k T；
τm≈Wp×Yp×m＝τk×Yp×k T×Yp×m；
Wherein, WpIs the first p principal component vectors Y under m bandsp×mPC fraction of (d), T represents the inverse matrix, τkIs the spectral transmittance of the infrared smoke screen of k typical wave bands, wherein p < k < m.
5. The infrared smoke screen spectral transmittance simulation method according to any one of claims 1 to 4, further comprising:
and calculating the infrared smoke screen spectral transmittance of the k typical wave bands by a line-by-line calculation method.
6. The infrared smoke transmittance simulation method according to claim 5, wherein in the calculating of the infrared smoke transmittance of k typical wave bands by the line-by-line calculation method, the pressure is equally divided into 100 segments in the range of 1atm to 12atm, the temperature is equally divided into 10 segments in the range of 0 ℃ to 500 ℃, and the pressure is equally divided into 10 segmentsIn CO2，H2O，H3PO4The absorption of Cu was calculated.
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| CN111445543A (en) * | 2020-04-16 | 2020-07-24 | 东北大学 | Method for encoding convolutional neural network into spectral transmittance |
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| CN102967577A (en) * | 2012-10-18 | 2013-03-13 | 中国人民解放军电子工程学院 | Biological aerosol transmitance testing arrangement based on Fourier transform infrared spectrometer |
| US20180266941A1 (en) * | 2017-03-15 | 2018-09-20 | Canon Kabushiki Kaisha | Analyzer, image capturing apparatus, analyzing method, and storage medium |
| CN110726700A (en) * | 2019-11-06 | 2020-01-24 | 北京环境特性研究所 | Smoke transmittance distribution measurement and acquisition method and device |
| CN111126452A (en) * | 2019-12-03 | 2020-05-08 | 中国科学院国家空间科学中心 | Ground feature spectral curve expansion method and system based on principal component analysis |
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