CN109211803B - Device for rapidly identifying micro plastic based on microscopic multispectral technology - Google Patents
Device for rapidly identifying micro plastic based on microscopic multispectral technology Download PDFInfo
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Abstract
The invention relates to a device for rapidly identifying micro-plastics based on a microscopic multispectral technology, which comprises a multispectral light source, an optical collimation system, a microscope objective, an electric objective table, a light splitting system, a CCD image acquisition device, a data processing device and a computer, wherein the multispectral light source is arranged on the multispectral light source; the wide wavelength light source emitted by the multispectral light source is collimated into parallel light by the first optical collimation system; the microscope objective is focused to focus parallel light to a micro plastic sample placed on the electric objective table; the second optical collimation system is used for collimating the multispectral signals diffusely reflected by the micro-plastic sample; the light splitting system is used for splitting the multispectral signals collimated by the second optical collimating system into an ultraviolet spectrum, a visible spectrum and infrared light; the CCD image acquisition device is used for acquiring three spectral signals and sending the spectral signals to the data processing device; the data processing device is used for amplifying and AD converting the collected signals and then sending the signals to the computer for analysis and comparison.
Description
Technical Field
The invention relates to a device for rapidly identifying micro-plastics based on a microscopic multispectral technology, and relates to the technical field of environmental monitoring and detection of micro-plastics in an environmental medium.
Background
The wide application of plastic products brings great convenience to people. However, the discarded plastic products are accumulated in the environment for a long time, are broken into small plastic fragments by physical and chemical actions, and can be remotely migrated, and a part of the plastic wastes enter the marine environment under the actions of wind power, precipitation, river flow and the like, and are broken into smaller fragments under the physical actions of solar radiation, biological erosion, tide, wave scouring and the like. The prior art defines these plastic fibers, particles and chips with dimensions of 1nm to 5mm as micro-plastics. The micro plastic is widely distributed in the marine environment, and is easier to adsorb organic pollutants and heavy metals due to larger specific surface area. Meanwhile, the micro plastic is easily ingested by marine organisms, causing harm. Micro-plastics are gradually becoming a new type of environmental pollutants and drawing wide attention.
The pollution condition research of the micro plastic needs to detect the existence of the micro plastic in an environment medium, and the subsequent research needs to qualitatively analyze the micro plastic so as to obtain the specific information of the micro plastic pollution. At present, the method for distinguishing the types of plastics at home and abroad mainly comprises a traditional physicochemical method and a novel nondestructive detection method, the traditional physicochemical method is used for distinguishing the types of plastics according to the characteristics of appearance, density, combustion and solubility, the commonly used methods comprise an appearance distinguishing method, a density distinguishing method, a solubility method, a pyrolysis method, combustion distinguishing and a dual thermal analysis method, and the methods all have different defects, so that the method is difficult to be widely popularized. The novel qualitative analysis of the micro-plastic usually uses a scanning electron microscope, an electron microscope for scanning, an infrared spectrum, a Raman spectrum, a thermal desorption gas chromatography-mass spectrum and the like, and the devices are suitable for indoor analysis, generally have the problems of higher analysis cost and higher requirements on analysis environmental conditions, and are difficult to be used for rapid detection of a sampling site.
The plastic has different monomer types, processing techniques, additive components and contents, and has obvious difference in performance characteristics. The spectral analysis technology is a kind of analysis technology for determining the property, structure or content of a substance according to the characteristics of the absorption, emission and scattering spectral lineages of the substance, and has the advantages of sensitivity, rapidness, accuracy, simplicity and the like. The prior art lacks a method for separating, purifying and quantifying the micro-plastic with high efficiency, high accuracy and low cost, and becomes the bottleneck of the related research on the environmental distribution and toxicology of the micro-plastic. Therefore, only by the prior development of novel methods for separation, purification and quantitative analysis of microplastics, the existence, migration and transformation processes of microplastics in the environment and in the living body can be understood.
Disclosure of Invention
Aiming at the problems, the invention aims to provide a device for rapidly identifying the micro plastic based on the microscopic multispectral technology, which has high sensitivity, is simple and feasible, has strong anti-interference capability and high detection efficiency.
In order to achieve the purpose, the invention adopts the following technical scheme: a device for rapidly identifying micro-plastics based on a microscopic multispectral technology is characterized by comprising a multispectral light source, a first optical collimation system, a second optical collimation system, a microscope objective, an electric objective table, a light splitting system, a CCD image acquisition device, a data processing device and a computer; the multispectral light source adopts a wide wavelength light source which can cover ultraviolet, visible and near-infrared wave bands, and the wide wavelength light source emitted by the multispectral light source is collimated into parallel light by the first optical collimation system; the micro objective lens is used for focusing parallel light to a micro plastic sample placed on the electric objective table; the second optical collimation system is used for collimating multispectral signals diffusely reflected by the micro-plastic sample; the light splitting system is used for splitting the multispectral signals collimated by the second optical collimating system into an ultraviolet spectrum, a visible spectrum and an infrared spectrum; the CCD image acquisition device is used for acquiring three spectral signals and sending the three spectral signals to the data processing device; and the data processing device is used for amplifying the acquired signals, performing AD conversion on the signals, and then sending the signals to the computer for analysis and comparison to complete the identification of the micro plastic sample.
Further, be provided with electronic objective table control module, sample database and spectral information comparison module in the computer: the electric objective table control module is used for sending signals to control the movement of the electric objective table and recording a movement track; the sample database is provided with ultraviolet, infrared and visible spectrum information of common plastics, common plastic additives, antioxidants, ultraviolet-resistant agents, nucleating agents, antistatic agents and plasticizers, and a spectrum analysis prediction model constructed according to the database information; the spectrum information comparison module is used for acquiring spectrum information of the micro-plastic to be detected and acquiring information of the type, pigment, additive and surface adsorption modification condition of the micro-plastic to be detected according to the constructed sample database and the spectrum analysis model; and comparing the similarity between the sample testing point and the adjacent sample testing points, if the similarity is greater than a set value, determining that the sample testing point and the adjacent sample testing points belong to the same micro plastic particle, and estimating the particle size and length information of the micro plastic sample to be tested according to the distance between the adjacent sample testing points and the movement track information.
Further, the construction process of the spectral analysis prediction model comprises the following steps:
1) preprocessing the spectrums of the selected known samples by adopting an orthogonal signal correction preprocessing technology;
2) selecting a modeling sample and a prediction sample by adopting an SPXY method;
3) selecting a genetic algorithm to extract characteristic wavelengths of the selected samples;
4) a spectral analysis prediction model is constructed by adopting a least square support vector machine;
5) and evaluating the constructed spectral analysis prediction model by adopting the correlation coefficient, the relative analysis error and the root-mean-square error.
Further, the multispectral light source adopts a halogen tungsten lamp.
Further, the light splitting system adopts a planar reflection type grating monochromator.
Further, the data processing device comprises an amplifier and an AD converter, wherein the amplifier is used for amplifying the received signal of the CCD image acquisition device, and the AD converter is used for AD converting the amplified signal and sending the AD converted signal to the computer.
Due to the adoption of the technical scheme, the invention has the following advantages: 1. the invention applies the spectrum technology to the field of micro-plastic detection, utilizes the difference of different micro-plastic reflection spectra to compare with the previously established sample spectrum library to achieve the aim of rapid detection, and has the characteristics of high sensitivity, simplicity, practicability, strong anti-interference capability, high detection efficiency and the like. 2. The whole detection process of the invention has strong anti-interference capability, high reliability of detection result, quick and simple measurement, low cost and wide application range, and can be used for measurement of outdoor environment.
Drawings
FIG. 1 is a schematic diagram of the device for rapidly identifying the micro-plastic based on the micro-multispectral technology.
Detailed Description
The present invention is described in detail below with reference to the attached drawings. It is to be understood, however, that the drawings are provided solely for the purposes of promoting an understanding of the invention and that they are not to be construed as limiting the invention.
As shown in fig. 1, the device for rapidly identifying micro-plastics based on the micro-multispectral technology provided by the invention comprises a multispectral light source 1, an optical collimating system 2, a microscope objective (not shown in the figure), an electric objective table 3, a light splitting system 4, a CCD image collecting device 5, a data processing device 6 and a computer 7.
The multispectral light source 1 adopts a wide wavelength light source with the wavelength of 200 nm-2500 nm and capable of covering ultraviolet, visible and near-infrared wave bands, the wide wavelength light source emitted by the multispectral light source 1 is collimated into parallel light by an optical collimation system 2 and focused by a microscope objective to be placed on an electric objective table 3 of a to-be-measured micro plastic sample, multispectral signals diffusely reflected by the micro plastic sample are collimated into parallel light by the optical collimation system 2 and are transmitted to a light splitting system 4, the light splitting system 4 is used for splitting the multispectral signals into ultraviolet spectrum, visible spectrum and infrared spectrum, the three spectral signals after light splitting are collected by a CCD image collecting device 5 and are transmitted to a data processing device 6, the data processing device 6 is used for amplifying the collected signals, performing AD conversion and then transmitting the signals to a computer 7 for analysis and comparison, and rapidly identifying the micro plastic sample. Wherein, computer 7 still connects electronic objective table 3, and computer 7 control electronic objective table 3 carries out continuous movement and can take notes the movement track of electronic objective table 3, realizes the automatic scanning to little plastic sample.
In a preferred embodiment, the multispectral light source 1 may be a tungsten halogen lamp.
In a preferred embodiment, the optical collimating system 2 may employ an entrance slit that confines an incident beam and a lens that changes the incident diverging beam into a parallel beam.
In a preferred embodiment, the light splitting system 4 can be a planar reflective grating monochromator for splitting the composite light of the ultraviolet, visible and infrared spectral regions into monochromatic light.
In a preferred embodiment, the data processing device 6 includes an amplifier for amplifying the received signal of the CCD image pickup device 5 and an AD converter for AD-converting the amplified signal and transmitting the AD-converted signal to the computer 7.
In a preferred embodiment, a motorized stage control module, a sample database and a spectral information comparison module are provided within the computer 7:
the electric objective table control module is used for sending signals to control the movement of the electric objective table and recording the movement track;
the sample database is provided with ultraviolet, infrared and visible spectrum information of common plastics such as polyethylene, polypropylene, polycarbonate, polystyrene, nylon plastics, polyethylene terephthalate, polyvinyl chloride, polymethacrylate, PC and the like, common plastic additives, antioxidants, ultraviolet-resistant agents, nucleating agents, antistatic agents, plasticizers and the like, and a spectrum analysis prediction model constructed according to the database information.
The spectrum information comparison module is used for acquiring spectrum information of the micro-plastic to be detected, preprocessing a spectrum of a sample to be detected by adopting an OSC preprocessing technology, eliminating abnormal samples by adopting a method of combining principal component analysis and Mahalanobis distance, and acquiring information such as the type, pigment, additive, surface adsorption modification condition and the like of the micro-plastic to be detected according to the constructed sample database and the spectrum analysis model; and continuously measuring samples, comparing the similarity between the sample measuring point and the adjacent sample measuring point, if the similarity is more than 90%, determining that the sample measuring point and the adjacent sample measuring point belong to the same micro plastic particle, and estimating the information such as the particle size, the length and the like of the micro plastic according to the information of the distance and the moving track of the adjacent sample measuring points.
In a preferred embodiment, the spectral analysis prediction model is constructed by the following specific method:
1) spectral preprocessing
In this embodiment, the spectrum of 254 known samples is preprocessed by using a preprocessing technique of OSC (Orthogonal Signal Correction), so as to reduce noise, and the number of samples can be selected according to actual needs.
2) Modeling set sample selection
Considering the influence of the property change of the component variable to be predicted, selecting a modeling Sample by using an SPXY method, in this embodiment, selecting 178 samples as a modeling Set by using an SPXY ((Sample Set based on point x-y Distances) method, and remaining 76 samples as a prediction Set, in the method, based on the euclidean distance between Sample spectral variables, uniformly selecting the modeling Sample in a Sample feature space, wherein a euclidean distance calculation formula between two samples is as follows:
in the formula (d)x(i, j) is the Euclidean distance between spectral variables of the sample; dy(i, j) is the Euclidean distance between the sample constituent properties, z is the number of selected modeling lumped samples, and i, j are the two samples that need to be compared.
3) Characteristic wavelength extraction
The model is built by adopting full wavelength, so that the complexity and the calculation load of the model can be greatly increased, the prediction precision of the model is reduced, and independent variables and co-linear variables are introduced. Therefore, the invention selects a genetic algorithm to extract the characteristic wavelength. The genetic algorithm is a self-adaptive global probability search algorithm, natural selection and genetic mechanisms in the biology world are used for reference, poor variables are continuously eliminated through selection, crossing and mutation, good variables are reserved, and the optimal result is finally achieved.
4) Establishing a spectral analysis prediction model
The invention adopts a Least square Support Vector Machine (LS-SVM) to construct a spectral analysis prediction model, and the principle is that data is mapped from a low dimension to a high dimension while function fitting is carried out, then the solution is carried out according to a minimum loss function in a high-dimensional space with equality constraint, and finally a linear fitting function is obtained, and the specific process is as follows:
let training sample set D { (x)k，yk)|k＝1，2，…，N}，xk∈Rn，yk∈R,xkIs input data, ykIs the output data. The function estimation problem in weight ω space is converted to the derivation of the following equation:
the constraint conditions are as follows:
wherein the content of the first and second substances,
is a kernel space mapping function, gamma is a penalty factor, ekFor error variables, b is the amount of deviation and the penalty function J is the sum of the SSE error and the regularization amount.
From the above equation, a Lagrangian function can be defined:
in the formula, the Lagrangian function multiplier ak∈ R is called a support value, and L is calculated for omega, b, ek，akThe partial derivative of (c) is equal to 0, and ω, e is eliminated, resulting in a matrix equation:
wherein
According to Mercer conditions, there are:
kernel function Ψ (x)k，xl) Polynomial kernels, multilayer perception kernels, B-spline kernels, RBF kernels and the like can be adopted, and the function estimation of the least square support vector machine is as follows:
5) model evaluation
And performing performance evaluation on the established spectral analysis prediction model by using the correlation coefficient, the relative analysis error and the root-mean-square error, which is the prior art and is not described herein again.
The following describes in detail the use effect of the micro-plastic rapid identification device based on the micro-multispectral technology by using specific embodiments, and the specific process is as follows:
respectively preparing polyethylene, polypropylene, polycarbonate, polystyrene and nylon plastics, and carrying out a sample database establishment experiment.
And then, a known micro plastic sample is adopted to carry out an experiment, the stability of the device is checked, the test is repeated for 10 times, the correct recognition rate is 95%, and the device has good stability.
10g of different plastic particle samples are mixed, 1g of the plastic particle samples are taken for detection, the test is repeated for 3 times, and the total recognition rate reaches 90%.
The micro plastic sample in the environment medium is detected by the device, the polyethylene plastic and the polyvinyl chloride plastic box polypropylene plastic are identified, the detection result is consistent with the result of the Fourier transform infrared spectrum detection, and the reliability of the device is further explained.
The above embodiments are only used for illustrating the present invention, and the structure, connection mode, manufacturing process, etc. of the components may be changed, and all equivalent changes and modifications performed on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.
Claims (5)
1. A device for rapidly identifying micro-plastics based on a microscopic multispectral technology is characterized by comprising a multispectral light source, a first optical collimation system, a second optical collimation system, a microscope objective, an electric objective table, a light splitting system, a CCD image acquisition device, a data processing device and a computer;
the multispectral light source adopts a wide wavelength light source which can cover ultraviolet, visible and near-infrared wave bands, and the wide wavelength light source emitted by the multispectral light source is collimated into parallel light by the first optical collimation system;
the micro objective lens is used for focusing parallel light to a micro plastic sample placed on the electric objective table;
the second optical collimation system is used for collimating multispectral signals diffusely reflected by the micro-plastic sample;
the light splitting system is used for splitting the multispectral signals collimated by the second optical collimating system into an ultraviolet spectrum, a visible spectrum and an infrared spectrum;
the CCD image acquisition device is used for acquiring three spectral signals and sending the three spectral signals to the data processing device;
the data processing device is used for amplifying and AD converting the collected signals and then sending the signals to the computer for analysis and comparison to complete the identification of the micro plastic sample;
wherein, be provided with electronic objective table control module, sample database and spectral information in the computer and compare the module:
the electric objective table control module is used for sending signals to control the movement of the electric objective table and recording a movement track;
the sample database is provided with ultraviolet, infrared and visible spectrum information of common plastics, common plastic additives, antioxidants, ultraviolet-resistant agents, nucleating agents, antistatic agents and plasticizers, and a spectrum analysis prediction model constructed according to the database information;
the spectrum information comparison module is used for acquiring spectrum information of the micro plastic sample and acquiring the type, pigment, additive and surface adsorption modification condition information of the micro plastic sample according to the constructed sample database and the spectrum analysis model; and comparing the similarity between a certain sample point and an adjacent sample point, if the similarity is greater than a set value, determining that the sample point and the adjacent sample point belong to the same micro plastic particle, and estimating the particle size and length information of the micro plastic sample to be measured according to the distance between the adjacent sample points and the movement track information.
2. The device for rapidly identifying the micro-plastic based on the micro-multispectral technology as claimed in claim 1, wherein the construction process of the spectral analysis prediction model comprises the following steps:
1) preprocessing the spectrums of the selected known samples by adopting an orthogonal signal correction preprocessing technology;
2) selecting a modeling sample and a prediction sample by adopting an SPXY method;
3) selecting a genetic algorithm to extract characteristic wavelengths of the selected samples;
4) a spectral analysis prediction model is constructed by adopting a least square support vector machine;
5) and evaluating the constructed spectral analysis prediction model by adopting the correlation coefficient, the relative analysis error and the root-mean-square error.
3. The device for rapidly identifying the micro-plastics based on the micro-multispectral technology as claimed in claim 1 or 2, wherein the multispectral light source adopts a halogen tungsten lamp.
4. The device for rapidly identifying the micro-plastics based on the microscopic multispectral technology as claimed in claim 1 or 2, wherein the light splitting system adopts a planar reflective grating monochromator.
5. The device for rapidly identifying the micro-plastics based on the microscopic multispectral technology as claimed in claim 1 or 2, wherein the data processing device comprises an amplifier and an AD converter, the amplifier is used for amplifying the received signal of the CCD image acquisition device, the AD converter is used for AD converting the amplified signal and sending the AD converted signal to the computer.
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| CN109211803B (en) * | 2018-09-17 | 2020-10-09 | 中国科学院生态环境研究中心 | Device for rapidly identifying micro plastic based on microscopic multispectral technology |
| CN110261346A (en) * | 2019-06-27 | 2019-09-20 | 浙江大学 | A method of quickly detecting PVC content in soil based near infrared spectrum |
| CN110197486B (en) * | 2019-07-02 | 2021-04-06 | 清华大学 | X-ray grating comprehensive imaging information extraction method, system and storage medium |
| EP3842787B1 (en) * | 2019-12-23 | 2023-04-26 | Sick Ag | Spectral sensor |
| CN112611566A (en) * | 2020-11-27 | 2021-04-06 | 中国航发四川燃气涡轮研究院 | Online particle detection method and device in high-temperature and high-speed airflow based on spectrum identification |
| CN113484261A (en) * | 2021-06-18 | 2021-10-08 | 北京市农林科学院 | Ultraviolet detection method for polyethylene terephthalate micro-plastic |
| IT202100029888A1 (en) * | 2021-11-25 | 2023-05-25 | Univ Degli Studi Di Firenze | METHOD OF IDENTIFICATION OF MICROPARTICLES, PARTICULARLY MICROPLASTICS, IN ENVIRONMENTAL MATRIX |
| CN114998664A (en) * | 2022-07-18 | 2022-09-02 | 中国科学院烟台海岸带研究所 | Rapid detection method and device for micro-plastic in seawater by multiple optical platforms |
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