CN117074262B - Pollen real-time monitoring device and method - Google Patents
Pollen real-time monitoring device and method Download PDFInfo
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- CN117074262B CN117074262B CN202311098782.2A CN202311098782A CN117074262B CN 117074262 B CN117074262 B CN 117074262B CN 202311098782 A CN202311098782 A CN 202311098782A CN 117074262 B CN117074262 B CN 117074262B
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
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Abstract
The invention relates to a pollen real-time monitoring device, wherein a first channel, a second channel, a third channel, a fourth channel, a fifth channel and a sixth channel which are communicated with the inside are formed in a shell; the first channel is opposite to the second channel, the third channel is opposite to the fourth channel, and the fifth channel is opposite to the sixth channel. The first channel is provided with a laser emitter, the inner side of the laser emitter is provided with a collimating lens, and the inner side of the collimating lens is provided with a cylindrical lens; the second channel is provided with a first optical detector; the third channel is provided with a second optical detector; the fourth channel is provided with a third optical detector, and the inner side of the third optical detector is provided with a polarizer; the first optical detector, the second optical detector and the third optical detector are respectively and electrically connected with the upper computer; the fifth channel is provided as an air inlet; the sixth passage is provided with a fan that exhausts outward. The method is realized based on the device, can identify the types of partial pollen, and provides an accurate data basis for pollen concentration report and forecast.
Description
Technical Field
The invention relates to the technical field of pollen monitoring, in particular to a pollen real-time monitoring device and method.
Background
In recent years, the incidence of allergic diseases caused by pollen, such as allergic rhinitis and asthma, is gradually rising worldwide. The diameter of the pollen is generally 15-50 mu m, and the micron-sized air-borne pollen is spread along with wind and is easy to be inhaled by human beings, so that a series of allergic reactions are caused and the health of the human beings is endangered. Pollen monitoring is therefore an urgent need in the public health field.
The existing pollen monitoring method is mainly based on manual monitoring. The monitoring personnel collect pollen through the slide and after staining the slide, identify the stained pollen by microscopy and count. The method is simple to operate, but needs a lot of manpower and material resources, and the data measurement is discontinuous. Therefore, it is important to establish an effective full-automatic pollen real-time monitoring method.
At present, the pollen monitoring device is less and can only monitor the total concentration of pollen, for example, chinese patent application CN115308099A discloses a pollen real-time monitoring device, a global intelligent pollen monitoring system and a method. Furthermore, this solution distinguishes pollen from fibrous dust by measuring the intensity of scattered light in both directions, however, many other particles may be identified as pollen in addition to fibrous dust, so that the concentration of pollen is measured too high. Therefore, new detection means are required to be developed, pollen and other particulate matters are effectively distinguished, and the accuracy of pollen concentration monitoring is improved.
Disclosure of Invention
The invention provides a pollen real-time monitoring device and method aiming at the technical problems that pollen and other particulate matters are difficult to effectively distinguish in pollen monitoring and the accuracy of pollen monitoring is low in the prior art.
The technical scheme for solving the technical problems is as follows:
Pollen real-time supervision device includes: a housing; the inside of the shell is provided with a hollow cavity structure;
The shell is provided with a first channel, a second channel, a third channel, a fourth channel, a fifth channel and a sixth channel which are communicated with the inside; the first channel is arranged opposite to the second channel, the third channel is arranged opposite to the fourth channel, and the fifth channel is arranged opposite to the sixth channel;
The first channel is provided with a laser emitter, the inner side of the laser emitter is provided with a collimating lens, and the inner side of the collimating lens is provided with a cylindrical lens; the second channel is provided with a first optical detector; the third channel is provided with a second optical detector; the fourth channel is provided with a third optical detector, and a polarizer is arranged on the inner side of the third optical detector; the first optical detector, the second optical detector and the third optical detector are respectively and electrically connected with the upper computer; the fifth channel is provided as an air inlet; the sixth passage is provided with a fan that exhausts the air outward.
Further: the center connecting line of the first channel and the second channel, the center connecting line of the third channel and the fourth channel and the center connecting line of the fifth channel and the sixth channel are intersected at a point in the shell.
Further: the particle size of the particles allowed to pass through the air inlet is smaller than 220 mu m.
The invention also provides a pollen real-time monitoring method, which is realized based on the pollen real-time monitoring device; comprising the following steps:
S1, controlling air flow of a detection area to enter the shell through an air inlet of the pollen real-time monitoring device;
S2, detecting forward scattered light intensity through a first optical detector, detecting side scattered light intensity through a second optical detector and detecting polarized light intensity through a third optical detector;
S3, calculating the particle size, refractive index and polarization degree of the particles;
S4, comparing the calculated particle size, refractive index and polarization degree data of the particles with a set characteristic value range X of pollen particles; if the particle size, refractive index and polarization degree data of the particles are in the characteristic value range X of the pollen particles, judging that the particles in the air flow are pollen, otherwise, judging that the particles in the air flow are not pollen;
S5, when the particles in the air flow are judged to be pollen, comparing the particle size, refractive index and polarization degree of the particles with data in an established pollen database; if the data corresponding to a certain type of pollen in the pollen database is met, reporting the type and concentration of the pollen; if the data corresponding to any type of pollen in the pollen database is not met, the concentration of the pollen is directly reported.
Further: the step S3 includes:
s31, establishing a Mie scattering theoretical model:
In Mie scattering theory, given a particle radius r, an incident light wavelength λ, and a particle relative refractive index m, the Mie coefficients a_n and b_n are used to calculate the intensity of scattered light at a specific angle, wherein:
a_n=[Ψ_n(mρ)Ψ'_n(ρ)-mΨ'_n(mρ)Ψ_n(ρ)]/[Ψ_n(mρ)
Ζ'_n(ρ) - mΨ'_n(mρ)Ζ_n(ρ)]①；
b_n=[mΨ_n(mρ)Ψ'_n(ρ)-Ψ'_n(mρ)Ψ_n(ρ)]/[mΨ_n(mρ)
Ζ'_n(ρ) - Ψ'_n(mρ)Ζ_n(ρ)]②；
where m=the refractive index of the particle/the refractive index of the surrounding medium, ψn (ρ) and ζ_n (ρ) are Riccati-Bessel functions, ψ '_n (ρ) and ζ' _n (ρ) are derivatives of Riccati-Bessel functions, ρ=2pi/λ, n is the order;
S32, assuming the radius of the particles is r0, the refractive index of the particles is c0, and carrying out the formulas ① and ② to obtain a_n and b_n;
S33, calculating scattered light intensity:
Calculating an angle function:
π_n(θ)=P_n^1(cosθ),
τ_n(θ)=dP_n^1(cosθ)/dθ,
Wherein, P_n1 (cos θ) represents is an associated Legend function;
(ii) calculating the elements S1 (θ) and S2 (θ) of the scattering matrix:
S1(θ)=∑[(2n+1)·(a_n·π_n(θ)+b_n·τ_n(θ))/(n(n+1))],
S2(θ)=∑[(2n+1)·(a_n·τ_n(θ)+b_n·π_n(θ))/(n(n+1))],
Wherein n is the order;
(iii) calculating the scattered light intensity I (θ) at angle θ:
I(θ)=I0·(1/2)·(|S1(θ)|²+ |S2(θ)|²),
wherein I0 is the intensity of the incident light, and I (θ) is the intensity of the scattered light at an angle θ;
S34, calculating the error square sum of the calculated I (theta) value and the actual measured value;
S35, calculating the gradient of the error function with respect to each parameter by using a gradient descent algorithm, and adjusting the parameters according to the negative direction of the gradient so as to minimize the error;
S36, randomly selecting a new refractive index c0 and a particle radius r0, repeating the steps S31-S34, and calculating the error square sum of the newly calculated I (theta) value and the actual measured value; accepting the new refractive index c0 and the particle radius r0 if the sum of the squares of the errors of the new calculated I (θ) value and the actual measured value is less than the sum of the squares of the errors of the previous calculated I (θ) value and the actual measured value; otherwise, accept the new parameter with certain probability, this probability is decided by current "temperature" and error difference, its computational formula is:
P=exp (- (objective function value of new solution-objective function value of current solution)/T);
Wherein P is the probability of accepting a new solution; exp is an exponential function; t is the current "temperature", which gradually decreases over time; when T is large, it is possible to accept the new solution even if it is worse than the current solution; when T is small, it is only accepted if the new solution is better than the current solution;
then, decrease "T" and repeat this step;
S37, until 'T' is reduced to a set value or the error is reduced to an allowable value, the parameter is close to a global optimal solution, and the particle radius r and the refractive index c of the particles are obtained;
s38, calculating the polarization degree:
Assuming that the scattered light is linearly polarized and the polarization direction is parallel to the transmission axis of the polarizer, the degree of polarization v can be approximately calculated using i_polarized measured by the third optical detector and i_total measured by the first optical detector:
v=I_polarized/I_total；
wherein, I_polarized is polarized light intensity; i_total is the total light intensity, which is equal in magnitude to the forward scattered light intensity.
The pollen real-time monitoring device and method provided by the invention have at least the following beneficial effects or advantages:
the pollen real-time monitoring method provided by the invention is realized based on a pollen real-time monitoring device; controlling the air flow of the detection area to enter the shell through the air inlet of the pollen real-time monitoring device; detecting forward scattered light intensity by the first optical detector, detecting side scattered light intensity by the second optical detector, and detecting polarized light intensity by the third optical detector; calculating the particle size, refractive index and polarization degree of the particles; comparing the calculated particle size, refractive index and polarization degree data of the particles with a set characteristic value range X of pollen particles; if the particle size, refractive index and polarization degree data of the particles are in the characteristic value range X of the pollen particles, judging that the particles in the air flow are pollen, otherwise, judging that the particles in the air flow are not pollen; when the particles in the air flow are judged to be pollen, comparing the particle size, refractive index and polarization degree of the particles with data in a pollen database; if the data corresponding to a certain type of pollen in the pollen database is met, reporting the type and concentration of the pollen; if the data corresponding to any type of pollen in the pollen database is not met, the concentration of the pollen is directly reported. According to the pollen real-time monitoring method, pollen and other particulate matters can be separated by measuring the scattered light intensity and the polarized light intensity, the accuracy of pollen monitoring is improved, and the types of partial pollen can be identified by combining a pollen database, so that an accurate data basis can be provided for establishing an air-sensing sensitized pollen monitoring network and reporting and forecasting pollen concentration.
Drawings
FIG. 1 is a schematic diagram of a pollen real-time monitoring device according to an embodiment of the present invention;
fig. 2 is a flowchart of a pollen real-time monitoring method according to an embodiment of the present invention.
In the drawings, the list of components represented by the various numbers is as follows:
1-first channel, 2-second channel, 3-third channel, 4-fourth channel, 5-fifth channel, 6-sixth channel, 7-laser emitter, 8-collimating lens, 9-cylindrical lens, 10-first optical detector, 11-second optical detector, 12-third optical detector, 13-polarizer.
Detailed Description
The invention provides a pollen real-time monitoring device and method aiming at the technical problems that pollen and other particulate matters are difficult to effectively distinguish in pollen monitoring and the accuracy of pollen monitoring is low in the prior art.
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The embodiment provides a pollen real-time supervision device, see fig. 1, include: a housing; the inside of the shell is provided with a hollow cavity structure. The shell is provided with a first channel 1, a second channel 2, a third channel 3, a fourth channel 4, a fifth channel 5 and a sixth channel 6 which are communicated with the inside; wherein the first channel 1 is opposite to the second channel 2, the third channel 3 is opposite to the fourth channel 4, and the fifth channel 5 is opposite to the sixth channel 6.
The first channel 1 is provided with a laser emitter 7, the inner side of the laser emitter 7 is provided with a collimating lens 8, and the inner side of the collimating lens 8 is provided with a cylindrical lens 9; the second channel 2 is provided with a first optical detector 10; the third channel 3 is provided with a second optical detector 11; the fourth channel 4 is provided with a third optical detector 12, and a polarizer 13 is arranged inside the third optical detector 12. The first optical detector 10, the second optical detector 11 and the third optical detector 12 are respectively and electrically connected with the upper computer; the fifth channel 5 is provided as an air inlet, and the particle size of the particles allowed to pass through the air inlet is smaller than 220 μm; the sixth passage 6 is provided with a fan that exhausts outward.
The central connecting line of the first channel 1 and the second channel 2, the central connecting line of the third channel 3 and the fourth channel 4 and the central connecting line of the fifth channel 5 and the sixth channel 6 intersect at a point inside the shell so as to ensure the maximized arrangement of the optical detection area inside the shell.
Example two
As shown in fig. 1 and fig. 2, the present embodiment provides a pollen real-time monitoring method, which is implemented based on a pollen real-time monitoring device; comprising the following steps:
S1, controlling air flow in a detection area to enter the shell through an air inlet of the pollen real-time monitoring device.
Step S2, the forward scattered light intensity is detected by the first optical detector 10, the side scattered light intensity is detected by the second optical detector 11, and the polarized light intensity is detected by the third optical detector 12.
And S3, calculating the particle size and refractive index of the particles.
Specifically, step S3 includes steps S31 to S38:
s31, establishing a Mie scattering theoretical model:
In Mie scattering theory, given a particle radius r, an incident light wavelength λ, and a particle relative refractive index m, the Mie coefficients a_n and b_n are used to calculate the intensity of scattered light at a specific angle, wherein:
a_n=[Ψ_n(mρ)Ψ'_n(ρ)-mΨ'_n(mρ)Ψ_n(ρ)]/[Ψ_n(mρ)
Ζ'_n(ρ) - mΨ'_n(mρ)Ζ_n(ρ)]①；
b_n=[mΨ_n(mρ)Ψ'_n(ρ)-Ψ'_n(mρ)Ψ_n(ρ)]/[mΨ_n(mρ)
Ζ'_n(ρ) - Ψ'_n(mρ)Ζ_n(ρ)]②；
Where m=the refractive index of the particles/the refractive index of the surrounding medium, ψn (ρ) and ζ_n (ρ) are Riccati-Bessel functions, ψ '_n (ρ) and ζ' _n (ρ) are derivatives of Riccati-Bessel functions, ρ=2pi/λ, n is the order.
Step S32, assuming that the radius of the particle is r0, the refractive index of the particle is c0, and the particle is brought into the formulas ① and ② to obtain a_n and b_n.
S33, calculating scattered light intensity:
Calculating an angle function:
π_n(θ)=P_n^1(cosθ),
τ_n(θ)=dP_n^1(cosθ)/dθ,
Wherein, P_n1 (cos θ) represents is an associated Legend function;
(ii) calculating the elements S1 (θ) and S2 (θ) of the scattering matrix:
S1(θ)=∑[(2n+1)·(a_n·π_n(θ)+b_n·τ_n(θ))/(n(n+1))],
S2(θ)=∑[(2n+1)·(a_n·τ_n(θ)+b_n·π_n(θ))/(n(n+1))],
Wherein n is the order;
(iii) calculating the scattered light intensity I (θ) at angle θ:
I(θ)=I0·(1/2)·(|S1(θ)|²+ |S2(θ)|²),
Where I0 is the intensity of the incident light and I (θ) is the intensity of the scattered light at an angle θ.
And S34, calculating the error square sum of the calculated I (theta) value and the actual measured value.
And S35, calculating the gradient of the error function relative to each parameter by using a gradient descent algorithm, and adjusting the parameters according to the negative direction of the gradient so as to minimize the error.
S36, randomly selecting a new refractive index c0 and a particle radius r0, repeating the steps S31-S34, and calculating the error square sum of the new calculated I (theta) value and the actual measured value; accepting the new refractive index c0 and the particle radius r0 if the sum of the squares of the errors of the new calculated I (θ) value and the actual measured value is less than the sum of the squares of the errors of the previous calculated I (θ) value and the actual measured value; otherwise, accept the new parameter with certain probability, this probability is decided by current "temperature" and error difference, its computational formula is:
P=exp (- (objective function value of new solution-objective function value of current solution)/T);
Wherein P is the probability of accepting a new solution; exp is an exponential function; t is the current "temperature", which gradually decreases over time; when T is large, it is possible to accept the new solution even if it is worse than the current solution; when T is small, it is only accepted if the new solution is better than the current solution;
then, the "T" is lowered and this step is repeated.
And S37, until 'T' is reduced to a set value or the error is reduced to an allowable value, the parameters are close to the global optimal solution, and the particle radius r and the refractive index c of the particles are obtained.
S38, calculating the polarization degree:
Assuming that the scattered light is linearly polarized and the polarization direction is parallel to the transmission axis of the polarizer, the degree of polarization v can be approximately calculated using i_polarized measured by the third optical detector and i_total measured by the first optical detector:
v=I_polarized/I_total；
wherein, I_polarized is polarized light intensity; i_total is the total light intensity, which is equal in magnitude to the forward scattered light intensity.
S4, comparing the calculated particle size, refractive index and polarization degree data of the particles with a set characteristic value range X of pollen particles; if the particle size, refractive index and polarization degree data are within the characteristic value range X of the pollen particles, judging that the particles in the air flow are pollen, otherwise, judging that the particles in the air flow are not pollen.
By using the pollen real-time monitoring device to test a large amount of pollen, the particle size range, the refractive index range and the polarization degree range of pollen particles can be obtained, and the three parameters are utilized to jointly define the characteristic value range X of the pollen particles by combining the particle size range, the refractive index range and the polarization degree range of pollen.
S5, when the particles in the air flow are judged to be pollen, comparing the particle size, refractive index and polarization degree of the particles with data in a pollen database; if the data corresponding to a certain type of pollen in the pollen database is met, reporting the type and concentration of the pollen; if the data corresponding to any type of pollen in the pollen database is not met, the concentration of the pollen is directly reported.
The pollen real-time monitoring device and method provided by the embodiment of the invention have at least the following beneficial effects or advantages:
The pollen real-time monitoring method provided by the embodiment of the invention is realized based on the pollen real-time monitoring device; controlling the air flow of the detection area to enter the shell through the air inlet of the pollen real-time monitoring device; detecting forward scattered light intensity by the first optical detector, detecting side scattered light intensity by the second optical detector, and detecting polarized light intensity by the third optical detector; calculating the particle size, refractive index and polarization degree of the particles; comparing the calculated particle size, refractive index and polarization degree data of the particles with a set characteristic value range X of pollen particles; if the particle size, refractive index and polarization degree data of the particles are in the characteristic value range X of the pollen particles, judging that the particles in the air flow are pollen, otherwise, judging that the particles in the air flow are not pollen; when the particles in the air flow are judged to be pollen, comparing the particle size, refractive index and polarization degree of the particles with data in a pollen database; if the data corresponding to a certain type of pollen in the pollen database is met, reporting the type and concentration of the pollen; if the data corresponding to any type of pollen in the pollen database is not met, the concentration of the pollen is directly reported. According to the pollen real-time monitoring method, pollen and other particulate matters can be separated by measuring the scattered light intensity and the polarized light intensity, the accuracy of pollen monitoring is improved, and the types of partial pollen can be identified by combining a pollen database, so that an accurate data basis can be provided for establishing an air-sensing sensitized pollen monitoring network and reporting and forecasting pollen concentration.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (1)
1. A pollen real-time monitoring method is realized based on a pollen real-time monitoring device; the method is characterized in that: the pollen-based real-time monitoring device comprises: a housing; the inside of the shell is provided with a hollow cavity structure;
The shell is provided with a first channel, a second channel, a third channel, a fourth channel, a fifth channel and a sixth channel which are communicated with the inside; the first channel is arranged opposite to the second channel, the third channel is arranged opposite to the fourth channel, and the fifth channel is arranged opposite to the sixth channel;
The first channel is provided with a laser emitter, the inner side of the laser emitter is provided with a collimating lens, and the inner side of the collimating lens is provided with a cylindrical lens; the second channel is provided with a first optical detector; the third channel is provided with a second optical detector; the fourth channel is provided with a third optical detector, and a polarizer is arranged on the inner side of the third optical detector; the first optical detector, the second optical detector and the third optical detector are respectively and electrically connected with the upper computer; the fifth channel is provided as an air inlet; the sixth channel is provided with a fan for exhausting outwards;
The method comprises the following steps:
S1, controlling air flow of a detection area to enter the shell through an air inlet of the pollen real-time monitoring device;
S2, detecting forward scattered light intensity through a first optical detector, detecting side scattered light intensity through a second optical detector and detecting polarized light intensity through a third optical detector;
S3, calculating the particle size, refractive index and polarization degree of the particles;
S4, comparing the calculated particle size, refractive index and polarization degree data of the particles with a set characteristic value range X of pollen particles; if the particle size, refractive index and polarization degree data of the particles are in the characteristic value range X of the pollen particles, judging that the particles in the air flow are pollen, otherwise, judging that the particles in the air flow are not pollen;
S5, when the particles in the air flow are judged to be pollen, comparing the particle size, refractive index and polarization degree of the particles with data in an established pollen database; if the data corresponding to a certain type of pollen in the pollen database is met, reporting the type and concentration of the pollen; if the data corresponding to any type of pollen in the pollen database is not met, directly reporting the concentration of the pollen;
wherein, the step S3 includes:
s31, establishing a Mie scattering theoretical model:
In Mie scattering theory, given a particle radius r, an incident light wavelength λ, and a particle relative refractive index m, the Mie coefficients a_n and b_n are used to calculate the intensity of scattered light at a specific angle, wherein:
a_n=[Ψ_n(mρ)Ψ'_n(ρ)-mΨ'_n(mρ)Ψ_n(ρ)]/[Ψ_n(mρ)
Ζ'_n(ρ) - mΨ'_n(mρ)Ζ_n(ρ)]①；
b_n=[mΨ_n(mρ)Ψ'_n(ρ)-Ψ'_n(mρ)Ψ_n(ρ)]/[mΨ_n(mρ)
Ζ'_n(ρ) - Ψ'_n(mρ)Ζ_n(ρ)]②；
where m=the refractive index of the particle/the refractive index of the surrounding medium, ψn (ρ) and ζ_n (ρ) are Riccati-Bessel functions, ψ '_n (ρ) and ζ' _n (ρ) are derivatives of Riccati-Bessel functions, ρ=2pi/λ, n is the order;
S32, assuming the radius of the particles is r0, the refractive index of the particles is c0, and carrying out the formulas ① and ② to obtain a_n and b_n;
S33, calculating scattered light intensity:
Calculating an angle function:
π_n(θ)=P_n^1(cosθ),
τ_n(θ)=dP_n^1(cosθ)/dθ,
Wherein, P_n1 (cos θ) represents is an associated Legend function;
(ii) calculating the elements S1 (θ) and S2 (θ) of the scattering matrix:
S1(θ)=∑[(2n+1)·(a_n·π_n(θ)+b_n·τ_n(θ))/(n(n+1))],
S2(θ)=∑[(2n+1)·(a_n·τ_n(θ)+b_n·π_n(θ))/(n(n+1))],
Wherein n is the order;
(iii) calculating the scattered light intensity I (θ) at angle θ:
I(θ)=I0·(1/2)·(|S1(θ)|²+|S2(θ)|²),
wherein I0 is the intensity of the incident light, and I (θ) is the intensity of the scattered light at an angle θ;
S34, calculating the error square sum of the calculated I (theta) value and the actual measured value;
S35, calculating the gradient of the error function with respect to each parameter by using a gradient descent algorithm, and adjusting the parameters according to the negative direction of the gradient so as to minimize the error;
S36, randomly selecting a new refractive index c0 and a particle radius r0, repeating the steps S31-S34, and calculating the error square sum of the newly calculated I (theta) value and the actual measured value; accepting the new refractive index c0 and the particle radius r0 if the sum of the squares of the errors of the new calculated I (θ) value and the actual measured value is less than the sum of the squares of the errors of the previous calculated I (θ) value and the actual measured value; otherwise, accept the new parameter with certain probability, this probability is decided by current "temperature" and error difference, its computational formula is:
P=exp (- (objective function value of new solution-objective function value of current solution)/T);
wherein P is the probability of accepting a new solution; exp is an exponential function; t is the current "temperature", which gradually decreases over time; then, decrease "T" and repeat this step;
S37, until 'T' is reduced to a set value or the error is reduced to an allowable value, obtaining the particle radius r and the refractive index c of the particulate matters by using a global optimal solution as a parameter;
s38, calculating the polarization degree:
Assuming that the scattered light is linearly polarized and the polarization direction is parallel to the transmission axis of the polarizer, the degree of polarization v is calculated using i_polarized measured by the third optical detector, i_total measured by the first optical detector:
v=I_polarized/I_total；
wherein, I_polarized is polarized light intensity; i_total is the total light intensity, which is equal in magnitude to the forward scattered light intensity.
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| JP2005283152A (en) * | 2004-03-26 | 2005-10-13 | Shinei Kk | Pollen sensor |
| CN109900621A (en) * | 2019-03-25 | 2019-06-18 | 中兴仪器（深圳）有限公司 | A kind of multi-angle polarized light scatter PM2.5 aerosol particles by micro measuring device |
| CN110849817A (en) * | 2019-10-21 | 2020-02-28 | 中国科学院大气物理研究所 | A system for measuring polarization optical properties and optical particle size spectrum of single particles |
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| US4173415A (en) * | 1976-08-20 | 1979-11-06 | Science Spectrum, Inc. | Apparatus and process for rapidly characterizing and differentiating large organic cells |
| CN104807738B (en) * | 2015-03-24 | 2017-05-03 | 中国科学院上海光学精密机械研究所 | Device for detecting shapes of single aerosol particles in real time |
| CN108254295B (en) * | 2018-01-15 | 2020-07-24 | 南京大学 | Method and device for positioning and representing spherical particles |
| CN114675297A (en) * | 2022-03-11 | 2022-06-28 | 中国科学院大气物理研究所 | Unattended multi-wavelength Raman-Mie scattering laser radar detection system |
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| JP2005283152A (en) * | 2004-03-26 | 2005-10-13 | Shinei Kk | Pollen sensor |
| CN109900621A (en) * | 2019-03-25 | 2019-06-18 | 中兴仪器（深圳）有限公司 | A kind of multi-angle polarized light scatter PM2.5 aerosol particles by micro measuring device |
| CN110849817A (en) * | 2019-10-21 | 2020-02-28 | 中国科学院大气物理研究所 | A system for measuring polarization optical properties and optical particle size spectrum of single particles |
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