Particulate optical detection system and method

Abstract

The application provides a particle optical detection system and method, and aims to solve the problem of difficult particle detection. The particle optical detection system comprises a light source for emitting laser light; a lens group for reflecting and expanding the laser light; an absorber for absorbing particles and placing the particles on the light path of the expanded laser light; a microscope group for microscopically enlarging the image of the particles; a filter for filtering the light passing through the microscope group; an image sensor for converting the light filtered by the filter into an electrical signal; and a host computer for calculating and analyzing the electrical signal transmitted by the image sensor to determine the number and composition of the target particles. The particle optical detection system uses an absorber and an image sensor to reduce the difficulty of particle detection; and the particle optical detection method uses big data and a color model to improve the speed of identifying the composition of the particles.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of photoelectricity, in particular to a particulate matter optical detection system and method. BACKGROUND

[0002] Atmospheric particulate matter is a general term for various solid and liquid particulate matter existing in the atmosphere. Various particulate matter is uniformly dispersed in the air to form a relatively stable large suspension system, i.e. an aerosol system. Fine particles in atmospheric particulate matter have a slow settling speed, stay in the atmosphere for a long time, and can be blown to a very far place under the action of atmospheric dynamics, causing pollution in a wide area. When a large amount of fine particles uniformly float in the air, they have a strong scattering and absorption effect on visible light, significantly weakening the light signal and causing a decrease in atmospheric visibility. PM2.5 refers to particulate matter with a diameter of less than or equal to 2.5 microns in the atmosphere, also known as respirable particulate matter. Although PM2.5 is small in volume, it is rich in a large amount of toxic and harmful substances, can be inhaled into the bronchus and alveoli of the human body and deposited, and poses a huge threat to human health.

[0003] In the existing optical detection method of particulate matter, the composition of the particulate matter is determined by analyzing the spectral image of the particulate matter, and the detection speed is limited. The optical detection system of the prior art is relatively complex, and the imaging of the particulate matter is affected by multiple factors, which has a certain detection difficulty. SUMMARY

[0004] The present application provides a particulate matter optical detection system and method, in particular for detecting the content and composition of PM2.5 in the atmosphere and determining the environmental air quality.

[0005] The first aspect of the present application provides a particulate matter optical detection system. The particulate matter optical detection system comprises a light source for emitting laser light; a lens group for reflecting and expanding the laser light emitted by the light source; an absorber for absorbing particulate matter and putting the particulate matter into the light path of the laser light expanded by the lens group; a microscope group for microscopically magnifying the image of the particulate matter; a filter for filtering the light passing through the microscope group; an image sensor for converting the light filtered by the filter into an electrical signal; and a host computer for calculating and analyzing the electrical signal transmitted by the image sensor to determine the number and composition of the target particulate matter.

[0006] Compared with the prior art, the detection sample, i.e. particulate matter, in the particulate matter optical detection system provided by the embodiment of the application is obtained by the absorber in the particulate matter optical detection system, and the spatiality and timeliness of sampling are more flexible; the embodiment of the application uses a microscope group and a filter to pre-process the image of the particulate matter, thereby improving the imaging quality; the embodiment of the application uses an image sensor to convert the light image of the particulate matter into an electrical signal in a corresponding proportional relationship with the light image, thereby reducing the difficulty of obtaining the image of the atmospheric particulate matter.

[0007] The second aspect of the application provides a particulate matter optical detection method. The particulate matter optical detection method comprises: obtaining a colored imaging picture by an image sensor, performing binaryzation processing on the colored imaging picture to obtain a black-and-white image; determining a target particulate matter according to the pixel size of the image of the particulate matter in the black-and-white image, and marking the position of the target particulate matter in the black-and-white image; calculating the number of the target particulate matter in the black-and-white picture to determine the quantity of the target particulate matter; establishing a color model of the image of the target particulate matter; and comparing the color model of the target particulate matter with a particulate matter color model database to determine the composition of the target particulate matter.

[0008] Compared with the prior art, in the particulate matter optical detection method provided by the embodiment of the application, the target particulate matter is automatically identified from the image, and the quantity of the target particulate matter is automatically determined by using the relationship between the size of the target particulate matter and the pixel size of the image sensor, thereby accelerating the identification speed of the target particulate matter; in the embodiment of the application, the artificial intelligence database is used, the content of the color model is established, the color model of the target particulate matter is compared with the content of the particulate matter color model database, and the composition of the target particulate matter is obtained, thereby realizing the rapid identification of the composition of the particulate matter. BRIEF DESCRIPTION OF DRAWINGS

[0009] Figure 1 FIG. 1 is a structural schematic diagram of a particulate matter optical detection system in an embodiment of the application.

[0010] Figure 2 FIG. 2 is a flow schematic diagram of a particulate matter optical detection method in an embodiment of the application.

[0011] Figure 3 FIG. 3 is a schematic diagram of a black-and-white picture obtained in step S2. Figure 2

[0012] MAIN ELEMENT SYMBOL EXPLANATION

[0013] DETECTION SYSTEM 100

[0014] LIGHT SOURCE 1

[0015] LENS GROUP 2

[0016] ABSORBER 3

[0017] MICROSCOPE GROUP 4​

[0018] Filter 5

[0019] Image sensor 6

[0020] Black and white picture 60

[0021] Black and white image 600

[0022] Host 7

[0023] Particulate matter 8

[0024] The following detailed description will further describe the present application in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0027] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined purpose, the following will be described in detail in conjunction with the drawings and the preferred embodiments.

[0028] The present application provides a particulate matter optical detection system. The particulate matter optical detection system can be installed in a specific environment according to the needs of the user, and continuously monitor the air environment in the environment. The particulate matter optical detection system can also be a mobile device, which can be moved to different environments according to the needs of the user, and can measure the air quality of different environments in real time.

[0029] Referring to Figure 1 In an embodiment of the present application, the particulate matter optical detection system 100 includes a light source 1, a lens group 2, an absorber 3, a microscope group 4, a filter 5, an image sensor 6, and a host 7.

[0030] The light source 1 is used to emit laser beams. The lens group 2 is used to reflect and expand the laser beams. The lens group 2, for example, comprises one or more expansion lenses used to expand the laser beams incident thereon, one or more collimating lenses used to collimate the laser beams incident thereon, and one or more mirrors used to reflect the laser beams incident thereon. The lens group 2 is located between the light source 1 and the absorber 3. The laser beams emitted by the light source 1 are expanded, collimated and / or reflected by the lens group 2 and then incident on the absorber 3. The absorber 3 is used to absorb the particulate matter 8 and to project the particulate matter 8 into the light path of the laser beams reflected and expanded by the lens group 2. The microscope group 4 is used to microscopically magnify the image of the particulate matter 8. The filter 5 is used to filter the light passing through the microscope group 4 to obtain laser beams of a target wavelength band. The image sensor 6 is used to convert the light filtered by the filter 5 into an electrical signal. The host 7 is used to perform computational analysis on the electrical signal transmitted by the image sensor 6 to determine the quantity and composition of the target particulate matter.

[0031] Specifically, the light source 1 emits laser beams. The laser beams reach the lens group 2, which expands, collimates and / or reflects the laser beams. The expanded, collimated and / or reflected laser beams reach the absorber 3, which absorbs the particulate matter 8 and projects the particulate matter 8 into the light path of the laser beams, so that the laser beams project on the particulate matter 8. The laser beams scattered and reflected by the particulate matter 8 form an image of the particulate matter 8, which is microscopically magnified by the microscope group 4. The light emitted from the microscope group 4 reaches the filter 5, and the stray light around the image of the particulate matter is filtered and removed by the filter 5. The image of the target particulate matter, after being magnified by the microscope group 4, can pass through the filter 5.

[0032] The image sensor 6 converts the light filtered by the filter 5 into an electrical signal in a corresponding proportional relationship, forming an electrical image. The host 7 is electrically connected to the image sensor 6 and performs computational analysis on the electrical image transmitted by the image sensor 6, selects the target particulate matter therefrom, calculates the quantity of the target particulate matter, and determines the composition of the target particulate matter by using a background database.

[0033] In an embodiment of the present application, the light source 1 is an ultraviolet laser, which emits laser beams with a wavelength less than 400 nm. The laser beams have good directivity, high intensity and large output energy.

[0034] In an embodiment of the present application, the light path between the light source 1 and the lens group 2 is at a non-zero angle with the light path between the lens group 2 and the image sensor 6, so as to improve the imaging quality of the image sensor 6. Further, the light rays from the light source 1 to the lens group 2 are not on the same line with the light rays from the lens group 2 to the absorber 3; or in other words, the light rays from the light source 1 to the lens group 2 are at a non-zero angle with the light rays from the lens group 2 to the absorber 3.

[0035] In an embodiment of the present application, the absorber 3 is capable of collecting particulate matters 8 in the atmosphere, in particular particulate matters with a diameter less than or equal to 2.5 μm.

[0036] In an embodiment of the present application, the microscope group 4 is designed for atmospheric particulate matters, in particular particulate matters with a diameter less than or equal to 2.5 μm, and is capable of effectively magnifying the image of the particulate matters with a diameter less than or equal to 2.5 μm, so that the magnified image of the particulate matters with a diameter less than or equal to 2.5 μm can pass through the filter 5. The microscope group 4 may, for example, include one or more microscope objectives for micro-magnifying the image of the particulate matters, but is not limited thereto.

[0037] In an embodiment of the present application, the filter 5 is a single pinhole filter, which is particularly suitable for atmospheric particulate matters, and is capable of filtering stray light around the image of the atmospheric particulate matters, so as to facilitate the image sensor 6 to accurately distinguish the imaging size. The stray light includes diffracted light from the light source, scattered light from the absorber, reflected light from the microscope group, etc.

[0038] In an embodiment of the present application, the photosensitive range of the image sensor 6 matches the light wave range of the light source 1. If the light source 1 is an ultraviolet laser, the image sensor 6 is capable of sensing light with a wavelength less than 400 nm.

[0039] In an embodiment of the present application, the image sensor 6 is a complementary metal oxide semiconductor (CMOS) image sensor, which is capable of integrating a pixel array and a peripheral support circuit (such as an image sensor core, a single clock, all timing logic, programmable functions and an analog-to-digital converter) on the same chip, and has the advantages of small size, light weight, low power consumption, easy programming and easy control. The CMOS image sensor includes a plurality of pixels arranged in a matrix. Each pixel is square, and the pixel size of the CMOS image sensor is defined as the side length of the square. In an embodiment, the pixel size of the CMOS image sensor is 0.7 μm, but is not limited thereto.

[0040] Compared with the prior art, the sample to be detected in the particulate optical detection system 100 provided in the embodiments of the present application, i.e., the particulate 8, is obtained by the absorber 3 in the particulate optical detection system 100, and the spatiality and timeliness of sampling are more flexible; the microscope group 4 and the filter 5 are used in the embodiments of the present application to pre-process the image of the particulate 8, thereby improving the imaging quality; the image sensor 6 is used in the embodiments of the present application to convert the light image of the particulate 8 into an electrical signal in a corresponding proportional relationship with the light image, thereby reducing the difficulty of obtaining the image of the atmospheric particulate.

[0041] An embodiment of the present application provides a particulate optical detection method. The particulate optical detection method can be detected by using the particulate optical detection system as shown in Figure 1 Figure 2 The particulate optical detection method comprises the following contents.

[0042] Step S1, obtaining a color picture.

[0043] Specifically, the color picture is obtained by the image sensor 6, and the color picture comprises color images of a plurality of particulates.

[0044] Step S2, performing binaryzation processing on the color picture to obtain a black-and-white picture.

[0045] Specifically, the host 7 judges the gray scale of the pixels in the color picture, and all the pixels with a gray scale greater than or equal to a threshold value are determined to belong to the particulate, and the gray scale value is represented by 255; otherwise, the pixel points are excluded from the particulate, and the gray scale value is 0, representing the background or the exceptional object area, thereby obtaining a black-and-white picture. The black-and-white picture comprises black-and-white images of the plurality of particulates.

[0046] Figure 3 For Figure 2 a schematic diagram of the black-and-white picture obtained in step S2. The size of the coordinate axis in the figure and the image size of the particulate in the figure do not represent the real proportion of the imaging picture of the image sensor. The black-and-white picture 60 has a coordinate system composed of mutually perpendicular X-axis and Y-axis. Figure 3 In the figure, only a black-and-white image 600 of one particulate is schematically drawn. The black-and-white image 600 of the particulate has a clear and accurate position in the coordinate system.

[0047] Step S3, determining a target particulate in the black-and-white picture.

[0048] ​Specifically, the host 7 judges the number of pixels of the black-and-white image 600 of the particle in the black-and-white picture 60, and determines whether the particle is the target particle if the diameter of the target particle is less than or equal to A1 and the pixel size of the image sensor is A2, i.e., whether the black-and-white image of the particle is less than or equal to A1 / A2 pixels. If yes, the particle is determined to be the target particle, and the position of each target particle in the black-and-white picture is marked.

[0049] In an embodiment of the present application, the diameter of the target particle is less than or equal to 2.5 μm (i.e., A1=2.5 μm), and the pixel size of the image sensor is 0.7 μm (i.e., A2=0.7 μm), so that the particle with a black-and-white image less than or equal to 3.57 pixels in the black-and-white picture is the target particle. In other embodiments, the sizes of A1 and A2 are not limited to this.

[0050] Step S4: calculating the number of target particles in the black-and-white picture.

[0051] Specifically, the host 7 calculates the number of position marks of each target particle in the black-and-white picture to determine the number of target particles.

[0052] Step S5: establishing a color model of the target particle by means of the color picture and the black-and-white picture.

[0053] Specifically, the host 7 acquires a color image of the target particle in the color picture according to the position of the target particle in the black-and-white picture, and establishes a color model of the target particle based on the color image of the target particle in the color picture.

[0054] In an embodiment, the host 7 analyzes the hue, saturation and intensity of the color image of the target particle in the color picture to establish a hue-saturation-intensity (HSI) color model of the target particle. In other embodiments, other color models, such as a hue-saturation-value (HSV) color model, can be established by analyzing other parameters of the color image of the target particle in the color picture.

[0055] Step S6: determining the composition of the target particle.

[0056] Specifically, the host 7 comprises a memory (not shown in the figure) and a processor (not shown in the figure) electrically connected to the memory. The memory is used to store one or more computer programs. The one or more computer programs are configured to be executed by the processor. The one or more computer programs comprise a plurality of instructions which, when executed by the processor, can implement the function of determining the composition of the target particulate matter. A database of color models of a plurality of particulate matters of different compositions is pre-stored in the memory. The color model of the target particulate matter is input into the host 7, and the color model of the target particulate matter is compared with the color model database of the particulate matter pre-stored in the memory by the processor, so that the processor automatically screens out the color model of the particulate matter of the known composition matching the color model of the target particulate matter, and determines the composition of the target particulate matter. The memory can include random access memory, hard disk, optical disk, U disk, etc. The processor can include a graphics processor, an image signal processor, a digital signal processor, etc.

[0057] Compared with the prior art, in the particulate matter optical detection method provided in the embodiments of the present application, the relationship between the size of the target particulate matter and the pixel size of the image sensor is utilized to automatically identify the target particulate matter from the image and automatically determine the number of the target particulate matter, thereby accelerating the identification speed of the target particulate matter. In the embodiments of the present application, an artificial intelligence database is used, and the composition of the target particulate matter is obtained by establishing a color model and comparing the color model of the target particulate matter with the content of the particulate matter color model database, thereby realizing the rapid identification of the composition of the particulate matter.

[0058] The above embodiments are only used to illustrate the technical solutions of the present application and not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A particulate optical detection system, characterized by, The application relates to a device for detecting the composition of particles in the air, comprising, a light source for emitting laser light; a lens group for reflecting and expanding the laser light; an absorber for absorbing particles and putting the particles into the light path of the laser light expanded by the lens group; a microscope group for microscopically enlarging the image of the particles; a filter for filtering the light passing through the microscope group; an image sensor for converting the light filtered by the filter into an electric signal; and a host computer for calculating and analyzing the electric signal transmitted by the image sensor, obtaining a colorful imaging picture through the image sensor, carrying out binary processing on the colorful imaging picture to obtain a black-and-white picture, determining target particles according to the pixel size of the image of the particles in the black-and-white picture, marking the position of the target particles in the black-and-white picture, calculating the number of the target particles in the black-and-white picture, establishing a color model of the target particles, and comparing the color model of the target particles with a particle color model database to determine the composition of the target particles. The wavelength of the laser light is less than 400 nm.

2. The particulate matter optical detection system of claim 1, wherein, The light path between the light source and the lens group and the light path between the lens group and the image sensor form a non-zero included angle.

3. The particulate matter optical detection system of claim 1, wherein, The absorber can capture particles with a diameter less than or equal to 2.5 microns in the air.

4. The particulate matter optical detection system of claim 1, wherein, The image of the target particles can pass through the filter after being enlarged by the microscope group.

5. The particulate matter optical detection system of any of claims 1-4, wherein, The filter is a single pinhole filter for filtering stray light around the image of the particles.

6. The particulate matter optical detection system of claim 5, wherein, The image sensor can sense light with a wavelength less than 400 nm.

7. The particulate matter optical detection system of any of claims 1-4, wherein, The application further relates to a method for detecting the composition of particles in the air, comprising the steps of:

8. A method of optical detection of particulate matter, characterized by, obtaining a colorful picture through an image sensor, wherein the colorful picture comprises colorful images of a plurality of particles; carrying out binary processing on the colorful picture to obtain a black-and-white picture, wherein the black-and-white picture comprises black-and-white images of the plurality of particles; judging whether each of the particles is a target particle according to the pixel number of the black-and-white image of each of the particles; calculating the number of the target particles in the black-and-white picture; establishing a color model of the target particles by means of the colorful picture and the black-and-white picture; and comparing the color model of the target particles with a preset particle color model database to determine the composition of the target particles. The particles with a diameter less than or equal to A1 are defined as the target particles, and the pixel size of the image sensor is A2, wherein the step of judging whether each of the particles is the target particle comprises the step of judging whether the black-and-white image of the particle is less than or equal to A1 / A2 pixels; if yes, the particle is determined as the target particle.

9. The particulate matter optical detection method of claim 8, wherein, The step of judging whether each of the particles is the target particle further comprises the step of marking the position of each of the target particles in the black-and-white picture.

10. The method according to claim 8 or 9, wherein ​ The color model of the target particle is established by acquiring a color image of the target particle in the color picture according to the position of the target particle in the black-and-white picture, and establishing the color model of the target particle based on the color image of the target particle in the color picture.

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