Indoor air particulate matter particle size and dynamic change monitoring method, system and device

Abstract

The application discloses a kind of indoor air particulate matter particle size and particle size dynamic change monitoring method, system and device, method includes: obtaining the multiple laser images of indoor target area;For each laser image Each laser beam, extract the gray value of each pixel point and determine scattering angle;For each pixel point, the gray value and scattering angle corresponding to the same pixel point in multiple laser images are brought into the gray value and particle size characteristic value relationship formula, the particle size characteristic value of air particulate matter at each pixel point is obtained, the relationship between particle size characteristic and particle size distribution is determined to determine the particle size distribution at each pixel point, and then the particle size distribution space information of indoor air particulate matter is determined;According to the particle size distribution at each pixel point corresponding to different time, the particle size dynamic change of indoor air particulate matter is determined, the description and description of particle size information and its change process are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of particulate matter particle size monitoring, in particular to an indoor air particulate matter particle size and dynamic change online monitoring method, system and device. BACKGROUND

[0002] Particulate matter in indoor air and its health hazards: Particulate matter in the air is composed of very small particles and droplets. PM2.5 and PM10 commonly discussed refer to particulate matter with an aerodynamic particle size of less than 2.5 microns and 10 microns, respectively. Among them, PM2.5 can directly penetrate into the bronchioles and lungs due to its extremely small particle size, causing great harm to human health. Therefore, long-term exposure to PM2.5 will increase the morbidity and mortality of humans. Recent studies have confirmed that submicron particulate matter, i.e. PM1.0 with an aerodynamic particle size of less than 1.0 microns, and ultrafine particles (UFP), i.e. particles with a particle size of less than 100 nanometers, are more harmful to health. Most people spend more time indoors (more than 22 hours on average) than outdoors, so the importance of particulate matter in indoor air to human exposure is much higher than that in outdoor air.

[0003] Particulate matter particle size distribution refers to the relationship between the concentration of particulate matter (or aerosol) particles and the particle size, which is an important physical parameter closely related to its source and formation process. The particle size of particulate matter can be represented as the aerodynamic diameter.

[0004] Measurement of air particulate matter particle size distribution:

[0005] In addition to the offline analysis technology of cascade impactor sampling and weighing, atmospheric aerosol particle size resolution includes electrostatic classification method and light scattering method. For example, the aerosol particle size spectrometer determines the online measurement of aerosol particle size in the air according to the light scattering principle, uses a uniform xenon lamp white light source, and uses a 90-degree scattering angle detector to determine the online measurement of aerosol particle size in the air. The typical equipment can measure the range of 0.2-105μm. At present, all online measurement technologies can only measure the particle size of particulate matter at one point in space.

[0006] Measurement technology of outdoor and indoor particulate matter vertical profile:

[0007] Backscattering lidar technology is the main method for determining the vertical profile of outdoor particulate matter concentration. The traditional backscattering lidar has a blind zone near the receiving end and a long transition zone. Although the transition zone can be corrected by the geometric factor, it will bring a large error. In recent years, some scholars have improved the traditional lidar and developed a side scattering lidar, which can greatly overcome the defects of the traditional lidar. Referring to the development of the indoor side scattering lidar (I-Lidar) technology based on the outdoor side scattering lidar technology, a means for continuously monitoring the dynamic changes of the indoor air particulate matter profile concentration is provided, which provides an important tool for studying the sources and exposure of indoor particulate matter. However, the above indoor lidar technology can determine the indoor air particulate matter concentration profile, but lacks the description and depiction of the particle size information and its change process. SUMMARY

[0008] The purpose of the present application is to provide an indoor air particulate matter particle size and dynamic change monitoring method, system and device, which can accurately monitor the particle size and dynamic change process of the indoor air particulate matter based on the principle of multi-angle light scattering difference of particulate matter of different particle sizes, and realize the description and depiction of the particle size information and its change process.

[0009] To achieve the above purpose, the present application provides the following scheme:

[0010] An indoor air particulate matter particle size and dynamic change monitoring method, the method comprising:

[0011] Obtaining a plurality of laser images of a target area in the indoor air; each of the laser images comprises a plurality of laser beams; the plurality of laser images are obtained by a plurality of CCD cameras distributed on the side of the laser beams; the plurality of laser images are images of the same position of the laser beams taken by the plurality of CCD cameras from different angles respectively;

[0012] For each of the laser beams of each of the laser images, extracting the gray value of each pixel point in the laser beam, and determining the scattering angle at each of the pixel points;

[0013] For each of the pixel points, the gray value and the scattering angle of the same pixel point in the plurality of laser images are brought into the gray value and particle size characteristic value relationship formula, and the particle size characteristic value of the air particulate matter at each of the pixel points is obtained;

[0014] For each of the pixel points, the particle size distribution at each of the pixel points is determined according to the particle size characteristic value and the relationship between the particle size characteristic and the particle size distribution; the relationship between the particle size characteristic and the particle size distribution is determined by experiment in advance; the particle size distribution comprises the particle size information of the indoor air particulate matter;

[0015] determine the particle size distribution spatial information of the indoor air particulate matter according to the particle size distribution at each of the pixel points;

[0016] determine the particle size dynamic change of the indoor air particulate matter according to the particle size distribution at each of the pixel points corresponding to different time points.

[0017] Optionally, the relationship between the gray value and the particle size characteristic value is:

[0018]

[0019] wherein g is the particle size characteristic value, θ is the scattering angle, I is the extracted gray value, and p1 and p2 are coefficients.

[0020] Optionally, for each of the pixel points, the gray value and the scattering angle corresponding to the same pixel point in the plurality of laser images are brought into the relationship between the gray value and the particle size characteristic value to obtain the particle size characteristic value of the air particulate matter at each of the pixel points, specifically including:

[0021] The gray value and the scattering angle corresponding to the same pixel point in the plurality of laser images are taken as a data set;

[0022] For each of the data sets, the gray value and the scattering angle in the data set are respectively brought into the relationship between the gray value and the particle size characteristic value to obtain a set of equations to be solved; the set of equations to be solved includes a plurality of equations to be solved;

[0023] The coefficients p1 and p2 and the particle size characteristic value g in the equations to be solved are solved to obtain the particle size characteristic value g corresponding to each of the data sets, i.e., the particle size characteristic value of the air particulate matter at each of the pixel points.

[0024] Optionally, the determination of the particle size distribution spatial information of the indoor air particulate matter according to the particle size distribution at each of the pixel points specifically includes:

[0025] According to the particle size distribution at all of the pixel points of each of the laser beams in the laser image, the gap between different laser beams is linearly interpolated to obtain the particle size distribution spatial information.

[0026] The present application also provides an indoor air particulate matter particle size and particle size dynamic change monitoring system, the system comprises:

[0027] An image acquisition module is configured to acquire a plurality of laser images of an indoor target area; each of the laser images comprises a plurality of laser beams; the plurality of laser images are captured by a plurality of CCD cameras distributed on the sides of the laser beams; the plurality of laser images are images of the same position of the laser beams captured by the plurality of CCD cameras respectively from different angles;

[0028] A gray scale and scattering angle acquisition module is configured to, for each of the laser beams of each of the laser images, extract a gray scale value of each pixel point in the laser beam and determine a scattering angle at each of the pixel points;

[0029] A particle size characteristic value acquisition module is configured to, for each of the pixel points, bring the gray scale values and the scattering angles of the same pixel points in the plurality of laser images into a gray scale value and particle size characteristic value relationship to obtain particle size characteristic values of the air particulate matters at the pixel points;

[0030] A particle size distribution acquisition module is configured to, for each of the pixel points, determine a particle size distribution at the pixel point according to the particle size characteristic values and a relationship between a particle size characteristic and a particle size distribution; the relationship between the particle size characteristic and the particle size distribution is determined in advance through experiments; the particle size distribution comprises indoor air particulate matter particle size information;

[0031] A particle size distribution space information acquisition module is configured to determine indoor air particulate matter particle size distribution space information according to the particle size distributions at each of the pixel points;

[0032] A particle size dynamic change observation module is configured to determine indoor air particulate matter particle size dynamic change according to the particle size distributions at each of the pixel points corresponding to different time points.

[0033] Optionally, the gray scale value and particle size characteristic value relationship is as follows:

[0034]

[0035] wherein g is a particle size characteristic value, θ is a scattering angle, I is an extracted gray scale value, and p1 and p2 are coefficients.

[0036] Optionally, the particle size characteristic value acquisition module specifically comprises:

[0037] A data set construction unit is configured to take the gray scale values and the scattering angles of the same pixel points in the plurality of laser images as a data set;

[0038] An equation solving unit is configured to, for each of the data sets, bring the gray scale values and the scattering angles in the data set into the gray scale value and particle size characteristic value relationship to obtain a to-be-solved equation set; the to-be-solved equation set comprises a plurality of to-be-solved equations.

[0039] The particle size characteristic value determination unit is configured to solve the coefficients p1 and p2 and the particle size characteristic value g in the equation to be solved, and obtain the particle size characteristic value g corresponding to each data set, i.e., the particle size characteristic value of the air particulate matter at each pixel point.

[0040] Optionally, the particle size distribution space information acquisition module specifically comprises:

[0041] The particle size distribution space information is obtained by performing linear interpolation on the gaps between different laser beams according to the particle size distribution at all pixel points of each laser beam in the laser image.

[0042] The application further provides an indoor air particulate matter particle size and dynamic change monitoring device, comprising a laser, a plurality of CCD cameras and a processor.

[0043] The laser is configured to emit a laser beam to indoor air.

[0044] The plurality of CCD cameras are arranged on the side of the laser beam and configured to capture laser images of the same position of the laser beam from different angles.

[0045] The processor is configured to execute the method in any one of claims 1 to 4.

[0046] According to the specific embodiments of the application, the following technical effects are achieved:

[0047] The application provides an indoor air particulate matter particle size and dynamic change monitoring method, system and device, which obtains laser images of the same position of a laser beam captured from different angles by a CCD camera, determines the particle size distribution at each pixel point according to the scattering light intensity difference (gray value difference) of each pixel point in the laser images from different angles, and further determines the particle size distribution space information and the dynamic change of the indoor air particulate matter, so as to realize the description and depiction of the particle size information and the change process of the particulate matter. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the drawings needed in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0049] Figure 1 A flowchart of an indoor air particulate matter particle size and dynamic change monitoring method is provided for Embodiment 1 of the application.

[0050] Figure 2 This is a schematic diagram showing the positional relationship between the laser and the CCD camera provided in Embodiment 1 of the present invention;

[0051] Figure 3 This is a schematic diagram illustrating the differences in signals obtained from the same location by CCD cameras at different angles, as provided in Embodiment 1 of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] The purpose of this invention is to provide a method, system, and device for monitoring the particle size and dynamic changes of indoor air particulate matter. By acquiring laser images of the same position of a laser beam taken from different angles by a CCD camera, the particle size distribution at each pixel is determined based on the difference in scattered light intensity (grayscale value difference) of each pixel in the laser images from different angles. This allows for the determination of the spatial information of indoor air particulate matter particle size distribution and the dynamic changes in particle size, thus realizing the characterization and description of particulate matter particle size information and its change process.

[0054] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0055] Example 1

[0056] like Figure 1 As shown in the figure, this embodiment provides a method for monitoring the particle size and dynamic changes of indoor air particulate matter, the method comprising:

[0057] S1: Acquire multiple laser images of an indoor target area; each laser image includes multiple laser beams; the multiple laser images are captured one-to-one by multiple CCD cameras distributed on the sides of the laser beams; the multiple laser images are images of the same position of the laser beams captured by the multiple CCD cameras from different angles. Figure 2 As shown, a laser beam is emitted by a laser device, and a CCD camera is used to collect the scattering signals of air particles in different directions from the side. Figure 2 The relative positions of the laser and the CCD camera are shown. The laser beam direction can be arbitrarily adjusted according to the desired profile direction, and multiple lasers can be set up to acquire two-dimensional or multi-dimensional dynamic information.

[0058] S2: for each laser beam of each laser image, extracting the gray value of each pixel point in the laser beam, and determining the scattering angle at each pixel point. The scattering angle is calculated in combination with the position of the camera.

[0059] S3: for each pixel point, the gray value and the scattering angle corresponding to the same pixel point in multiple laser images are brought into the gray value and particle size characteristic value relationship formula, and the particle size characteristic value of the air particulate matter at each pixel point is obtained.

[0060] The gray value of the photo taken by the CCD camera is proportional to the received light energy, and the scattering of laser beams of different particle sizes causes differences in the light energy received by the CCD, so the gray values of the same point in different camera photos can be extracted by software, as shown in Figure 3 The information of the particle size distribution is calculated according to the camera position and the gray value difference and the empirical fitting formula (gray value and particle size characteristic value relationship formula).

[0061] The gray value and particle size characteristic value relationship formula is:

[0062]

[0063] where g is the particle size characteristic value, θ is the scattering angle, I is the extracted gray value, and p1 and p2 are coefficients. The g value is a value related to the particle size and refractive index of the particulate matter, and the g value of different particle sizes is different. The g value of mixed particle size can be regarded as a linear combination of different particle size g values. The relationship between g value and particle size distribution is constructed through pre-experiment, and the particle size distribution is obtained according to the g value.

[0064] The derivation process corresponding to the above gray value and particle size characteristic value relationship formula is as follows:

[0065] When the ratio of particle size to laser wavelength is greater than 0.1, the scattering can be explained by Mie scattering theory. For aerosols with general particle size in the air, the scattering under 532 nm laser irradiation is within the range (particle size to 532 nm wavelength ratio is greater than one), which conforms to Mie scattering theory. The scattering light intensity is related to the camera shooting angle, which can be expressed by Henyey-Greenstein phase function:

[0066]

[0067] Where θ is the angle between the incident direction and the scattering direction, g is the relative intensity of the forward and backward scattering, which is the particle size characteristic value named in the application, and is related to the particle size and the refractive index of the particle. According to the experiment, I and θ are obtained, and then the value of g is obtained. Phg(θ, g) represents the distribution probability of the scattering light energy when the angle of the incident light is θ. The g value of the particle of different particle sizes is different, and therefore the phase function p(θ) (i.e. Phg(θ, g)) of the particle of different particle sizes is also different. This relationship provides a theoretical basis and possibility for detecting the particle size of the particle.

[0068] The principle of detecting the concentration by the indoor side scattering laser radar (I-Lidar) is as follows:

[0069]

[0070] Where E(θ) is the side scattering light energy received by the CCD camera when the scattering angle is θ, which is proportional to the gray value I and can be represented by γI, p(θ) is the aerosol scattering phase function. The remaining variables are known constants, K is a system constant, E l is the total laser energy emitted by the laser emitter within the exposure time, S p is the receiving area of each pixel, β s is the average value of the angular scattering cross section, ρ is the aerosol particle density, c is the proportional coefficient of the PM2.5 particle per unit mass, α is the PM 2.5 particle size, and M is the PM 2.5 concentration, and N atm is the number of molecules per unit volume, β atm is the molecular angular scattering coefficient. d is the differential symbol of the angle.

[0071] E(θ) is replaced by γI, the phase function p(θ) is expressed by the Henyey-Greenstein phase function, and the equation Phg(θ, g) is divided by γ on both sides to obtain the relationship between the gray value and the g value.

[0072] Based on the derived relationship between the gray value and the particle size characteristic value, step S3 specifically includes:

[0073] S31: Taking the gray value and the scattering angle corresponding to the same pixel point in a plurality of laser images as a data set.

[0074] S32: For each data set, the gray value and the scattering angle in the data set are respectively brought into the relationship between the gray value and the particle size characteristic value to obtain a to-be-solved equation group; the to-be-solved equation group includes a plurality of to-be-solved equations.

[0075] S33: solve the coefficient p1 and the coefficient p2 in the equation to be solved and the particle size characteristic value g, to obtain the particle size characteristic value g corresponding to each data set, that is, the particle size characteristic value of the air particulate matter at each pixel point.

[0076] There are several equations to be solved, so the number of laser images obtained is greater than or equal to the number of equations to be solved. That is, the number of equations to be solved is the same as the number of laser images, or the number of equations to be solved is greater than the number of laser images.

[0077] S4: For each pixel point, determine the particle size distribution at each pixel point according to the particle size characteristic value and the relationship between the particle size characteristic and the particle size distribution; the relationship between the particle size characteristic and the particle size distribution is determined in advance through experiments; the particle size distribution includes indoor air particulate matter particle size information.

[0078] The relationship between the particle size characteristic and the particle size distribution is determined in advance through experiments. Specifically, a series of pre-experiments are performed in the laboratory, and a particle generator is used to generate several particles with known particle sizes in sequence to construct a scene with relatively uniform concentration and particle size. In this scene, the particle size and concentration of the particulate matter are known. In this scene, a laser is used to emit a laser beam, a CCD camera is used to capture a laser image, and a particle size characteristic value g is obtained according to steps S1 to S3. By setting multiple scenes, the relationship between the particle size characteristic value g and the particle size distribution can be obtained.

[0079] When monitoring in practice, when a particle size characteristic value g is calculated in step S3, the corresponding particle size distribution of the g value can be determined according to the relationship between g and the particle size distribution. Knowing the particle size distribution can simultaneously obtain the particulate matter concentration and particle size information.

[0080] S5: Determine the particle size distribution spatial information of the indoor air particulate matter according to the particle size distribution at each pixel point.

[0081] The particle size distribution of each point of each laser in the photo is obtained, and then a simple linear interpolation calculation is performed between different laser beams to obtain the spatial information of the particle size distribution.

[0082] Specifically, step S5 includes:

[0083] According to the particle size distribution at all pixel points of each laser beam in the laser image, linear interpolation is performed on the gap between different laser beams to obtain the particle size distribution spatial information.

[0084] S6: Determine the particle size dynamic change of the indoor air particulate matter according to the particle size distribution at each pixel point corresponding to different time points.

[0085] Each frame of the CCD camera is processed, and the particle size distribution is dynamically monitored in multiple dimensions.

[0086] 1 System calibration - pre-experimental construction (g value and particle size relationship)

[0087] 1-1 Set up a wavelength 532 nm green laser in the experimental cabin, emitting a vertical laser beam from bottom to top. Place 3-4 CCD cameras (with external 532 nm filter) at different heights on the side. Use a particle generator to generate several known particle sizes in sequence, and construct a scene with relatively uniform concentration and particle size. Use a particle size spectrometer to measure the particle size. Obtain lateral scattering information in each experimental group. According to the data obtained at different angles in multiple experiments, establish the relationship between gray level and particle size distribution; at the same time, obtain the particle concentration data.

[0088] 1-2 Due to the possible differences in the physicochemical properties of particles generated by the particle generator and environmental atmospheric particles, which may affect the scattering signal, on the basis of 1-1, introduce the actual environmental air into the experimental cabin (the effect of the heavy pollution scene is more obvious due to the high particle concentration, so the signal is strong), construct a scene with relatively uniform concentration and particle size, and measure the particle concentration and particle size in the same way (use 1-1 to obtain parameters), compare the measurement results of the particle size spectrometer, and verify the accuracy of the parameter values of 1-1;

[0089] 2 Real measurement calibration - measurement experiment

[0090] 2-1 Use several artificial emission sources to construct a scene with non-uniform concentration and particle size, and use the same equipment to measure the particle concentration and particle size, to obtain the spatial distribution and dynamic change characteristics of the concentration and particle size;

[0091] 2-2 Use non-vertical laser system effect, and verify the effect of non-vertical profile test in the same way;

[0092] 2-3 Use a column of multiple lasers to generate parallel vertical lasers, and use cameras to synchronously collect scattering signals in the vertical direction of the laser plane, and mathematically interpolate to obtain two-dimensional particle size values (and concentration values) of the laser plane;

[0093] 2-4 Use multiple lasers to form a laser matrix, and use cameras to synchronously collect scattering signals to obtain particle concentration and particle size information of the laser matrix, and mathematically interpolate to obtain three-dimensional spatial particle size values (and concentration values).

[0094] In this embodiment, the gray value of the photo taken by the CCD camera is proportional to the received light energy, and the scattering of the laser beam by particles of different sizes causes differences in the light energy received by the CCD, so that the gray values of the same point in photos taken by different cameras can be extracted by software, and the information of the particle size distribution can be calculated according to the camera positions, the gray value differences and an empirical fitting formula, so that the particle size information and its change process can be described.

[0095] Embodiment 2

[0096] The embodiment provides an indoor air particulate matter particle size and dynamic change monitoring system, and the system comprises:

[0097] An image acquisition module is configured to acquire a plurality of laser images of a target area indoors; each of the laser images comprises a plurality of laser beams; the plurality of laser images are captured by a plurality of CCD cameras distributed on the sides of the laser beams one by one; and the plurality of laser images are images of the same position of the laser beams captured by the plurality of CCD cameras respectively from different angles.

[0098] A gray value and scattering angle acquisition module is configured to extract a gray value of each pixel point in each laser beam of each laser image, and determine a scattering angle at each pixel point.

[0099] A particle size characteristic value acquisition module is configured to, for each pixel point, bring the gray values and the scattering angles of the same pixel point in the plurality of laser images into a gray value-particle size characteristic value relationship formula, to obtain particle size characteristic values of air particulate matters at the pixel points.

[0100] The gray value-particle size characteristic value relationship formula is as follows:

[0101]

[0102] Wherein, g is a particle size characteristic value, θ is a scattering angle, I is an extracted gray value, and p1 and p2 are coefficients.

[0103] The particle size characteristic value acquisition module specifically comprises:

[0104] A data set construction unit is configured to take the gray values and the scattering angles of the same pixel point in the plurality of laser images as a data set.

[0105] An equation solving unit is configured to, for each data set, bring the gray values and the scattering angles in the data set into the gray value-particle size characteristic value relationship formula, to obtain a to-be-solved equation group; and the to-be-solved equation group comprises a plurality of to-be-solved equations.

[0106] The particle size characteristic value determination unit is configured to solve the coefficients p1 and p2 and the particle size characteristic value g in the equation to be solved, and obtain the particle size characteristic value g corresponding to each data set, i.e., the particle size characteristic value of the air particulate matter at each pixel point.

[0107] The particle size distribution acquisition module is configured to determine the particle size distribution at each pixel point according to the particle size characteristic value and the relationship between the particle size characteristic and the particle size distribution.

[0108] The particle size distribution spatial information acquisition module is configured to determine the particle size distribution spatial information of the indoor air particulate matter according to the particle size distribution at each pixel point.

[0109] The particle size distribution spatial information is obtained by performing linear interpolation on the gap between different laser beams according to the particle size distribution at all pixel points of each laser beam in the laser image.

[0110] The particle size dynamic change observation module is configured to determine the particle size dynamic change of the indoor air particulate matter according to the particle size distribution at each pixel point corresponding to different time points.

[0111] Embodiment 3

[0112] As shown in Figure 2 , the embodiment provides an indoor air particulate matter particle size and particle size dynamic change monitoring device, which comprises a laser, a plurality of CCD cameras and a processor (not shown in the figure). Figure 2

[0113] The laser is configured to emit a laser beam to indoor air.

[0114] The plurality of CCD cameras are arranged on the side of the laser beam and are configured to capture laser images of the same position of the laser beam from different angles.

[0115] The processor is configured to execute the method of any one of claims 1 to 4.

[0116] The operation process of the device according to the embodiment for executing the monitoring method is as follows:

[0117] ​Firstly, the laser beam is photographed by a CCD camera, and the measured information is obtained by extracting the gray value of the laser beam in the photo or video. The fitting coefficient obtained by the pre-experiment is used to correct the gray value to obtain the scattering light intensity (the scattering light intensity is proportional to the gray value I, which can be represented by γI). Then, according to the difference of the scattering light intensity obtained by the CCD at the same point at different angles, the particle size distribution is calculated, and the particle concentration and particle size are determined, so that the spatial distribution information of the particle mass concentration and particle size can be obtained.

[0118] Specifically, step 1: according to the experimental site area and the measurement dimension (two-dimensional or three-dimensional), the laser is placed, and the CCD camera is vertically installed. The number of lasers and CCD cameras is adjusted according to the measurement site and resolution requirements.

[0119] For measuring two-dimensional (planar) particle size distribution information collection, the laser can be placed in a row with a spacing of 20-40 cm, and for measuring three-dimensional (spatial) particle size distribution information, the laser can be placed in a matrix.

[0120] Step 2: turn on the laser to emit a laser beam; at the same time, the CCD camera synchronously photographs the laser image emitted by the laser.

[0121] Step 3: extract the gray value I of the laser beam in the image photographed by the camera, and bring the scattering angle and the gray value I into the relationship between the gray value and g to obtain the particle size characteristic value g.

[0122] Step 4: a series of pre-experiments are carried out in the laboratory, and a particle generator is used to generate several particles with known particle sizes in turn to construct a scene with relatively uniform concentration and particle size, and the relationship between g value and particle size distribution is obtained.

[0123] Step 5: using the relationship between g value and particle size distribution obtained in step 4, the g value obtained in step 5 is converted into particle size distribution.

[0124] Step 6: each point of each laser in the photo is processed according to the above steps, and a simple linear interpolation calculation is performed between different laser beams to obtain the spatial information of the particle size distribution. Each frame of the video photographed by the CCD is processed, and the particle size distribution can be dynamically monitored in multiple dimensions.

[0125] Steps 3 to 6 are executed in a processor.

[0126] In this specification, each embodiment focuses on the difference from other embodiments, and the same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0127] The principles and implementation manners of the present application are described by using specific examples in the present application, and the above examples are only used to help understand the method of the present application and its core idea; meanwhile, for the general technical personnel in the art, the specific implementation manners and application ranges will be changed according to the idea of the present application. In conclusion, the content of the present specification should not be understood as the limitation of the present application.

Claims

1. A method for monitoring the particle size and dynamic change of indoor air particulate matter, characterized in that, The method comprises: acquiring a plurality of laser images of an indoor target area; each of the laser images comprises a plurality of laser beams; the plurality of laser images are captured by a plurality of CCD cameras distributed on the sides of the laser beams; the plurality of laser images are images of the same position of the laser beams captured by the plurality of CCD cameras respectively from different angles; for each of the laser beams of each of the laser images, extracting the gray value of each pixel point in the laser beam and determining the scattering angle at each of the pixel points; for each of the pixel points, bringing the gray value and the scattering angle corresponding to the same pixel point in the plurality of laser images into a gray value-particle size characteristic value relationship to obtain the particle size characteristic value of the air particulate matter at each of the pixel points; for each of the pixel points, determining the particle size distribution at each of the pixel points according to the particle size characteristic value and the relationship between the particle size characteristic and the particle size distribution; the relationship between the particle size characteristic and the particle size distribution is determined in advance through experiments; the particle size distribution comprises indoor air particulate matter particle size information; determining the particle size distribution space information of the indoor air particulate matter according to the particle size distribution at each of the pixel points; determining the dynamic change of the particle size of the indoor air particulate matter according to the particle size distribution at each of the pixel points corresponding to different time instants; wherein the gray value-particle size characteristic value relationship is: wherein g is a particle size characteristic value, is a scattering angle, I is the extracted gray value, p 1 ，p 2is a coefficient; wherein the bringing the gray value and the scattering angle corresponding to the same pixel point in the plurality of laser images into the gray value-particle size characteristic value relationship to obtain the particle size characteristic value of the air particulate matter at each of the pixel points specifically comprises: taking the gray value and the scattering angle corresponding to the same pixel point in the plurality of laser images as a data set; for each of the data sets, bringing the gray value and the scattering angle in the data set into the gray value-particle size characteristic value relationship respectively to obtain a system of equations to be solved; the system of equations to be solved comprises a plurality of equations to be solved; coefficients in the equation to be solved p 1 and coefficients p 2 and the particle size characteristic value g are solved to obtain the particle size characteristic value g corresponding to each of the data sets, i.e. the particle size characteristic value of the air particulate matter at each of the pixel points.

2. The method of claim 1, wherein, the determining the particle size distribution space information of the indoor air particulate matter according to the particle size distribution at each of the pixel points specifically comprises: performing linear interpolation on the gaps between different laser beams according to the particle size distribution at all of the pixel points of each of the laser beams in the laser images to obtain the particle size distribution space information.

3. The indoor air particulate matter particle size and particle size dynamic change monitoring system according to any one of claims 1 to 2, characterized in that, The system comprises: an image acquisition module configured to acquire a plurality of laser images of an indoor target area; each of the laser images comprises a plurality of laser beams; the plurality of laser images are captured by a plurality of CCD cameras distributed on the sides of the laser beams; the plurality of laser images are images of the same position of the laser beams captured by the plurality of CCD cameras respectively from different angles; a gray value and scattering angle acquisition module configured to, for each of the laser beams of each of the laser images, extract the gray value of each pixel point in the laser beam and determine the scattering angle at each of the pixel points; The particle size characteristic value acquisition module is configured to, for each pixel point, bring the gray value and the scattering angle corresponding to the same pixel point in the multiple laser images into a gray value and particle size characteristic value relationship formula, and obtain the particle size characteristic value of the air particulate matter at each pixel point. The gray value and particle size characteristic value relationship formula is: wherein g is a particle size characteristic value, is a scattering angle, I is the extracted gray value, p 1 ，p 2 is a coefficient; The particle size characteristic value acquisition module specifically includes: The data set construction unit is configured to take the gray value and the scattering angle corresponding to the same pixel point in the multiple laser images as a data set. The equation solving unit is configured to, for each data set, bring the gray value and the scattering angle in the data set into the gray value and particle size characteristic value relationship formula, and obtain a to-be-solved equation group. The to-be-solved equation group includes multiple to-be-solved equations. A particle size characteristic value determination unit is configured to determine coefficients in the equation to be solved p 1 and coefficients p 2 and particle size characteristic value g, to obtain the particle size characteristic value g corresponding to each data set, i.e., the particle size characteristic value of air particulate matter at each pixel point. The particle size distribution acquisition module is configured to, for each pixel point, determine the particle size distribution at each pixel point according to the particle size characteristic value and a relationship between a particle size characteristic and a particle size distribution. The relationship between the particle size characteristic and the particle size distribution is determined in advance through experiments. The particle size distribution includes indoor air particulate matter particle size information. The particle size distribution space information acquisition module is configured to determine the particle size distribution space information of the indoor air particulate matter according to the particle size distribution at each pixel point. The particle size dynamic change observation module is configured to determine the particle size dynamic change of the indoor air particulate matter according to the particle size distribution at each pixel point corresponding to different time points.

4. The system of claim 3, wherein, The particle size distribution space information acquisition module specifically includes: According to the particle size distribution at all pixel points of each laser beam in the laser image, the gap between different laser beams is linearly interpolated to obtain the particle size distribution space information.

5. An indoor air particulate matter particle size and particle size dynamic change monitoring device, characterized in that, The laser device includes a laser, multiple CCD cameras, and a processor. The laser is configured to emit a laser beam to indoor air. The multiple CCD cameras are arranged on the side of the laser beam and are configured to capture laser images of the same position of the laser beam from different angles. The processor is configured to execute the method in any one of claims 1 to 2.

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