A method and device for diagnosing smoke of electronic cigarette

Abstract

The present invention discloses a smoke diagnosis method and device for an electronic cigarette, and relates to the technical field of smoke detection. An ejection instruction is issued to an electronic cigarette to make the electronic cigarette eject smoke, and smoke images of the electronic cigarette are photographed at multiple angles at a preset time to obtain a smoke image set, and the smoke volume is calculated based on the smoke image set. At the same preset time, a laser beam is emitted to the smoke particles of the electronic cigarette and scattered light of the smoke particles is received, and the particle size and concentration of the smoke particles are calculated based on the scattered light. The smoke particle content is calculated by the smoke volume and particle concentration, and the smoke quality of the electronic cigarette smoke is diagnosed based on the smoke particle content and the smoke particle size. The volume, particle size, particle concentration and smoke particle content of the electronic cigarette smoke are evaluated by photographing the smoke images of the electronic cigarette at multiple angles and combining the dynamic light scattering technology, so as to realize real-time and non-invasive diagnosis of the quality of the electronic cigarette smoke. The smoke detection cycle is reduced to ensure the accuracy of the detection results.

Description

Technical Field

[0001] The present invention belongs to the technical field of smoke detection, and in particular relates to a smoke diagnosis method and device for an electronic cigarette. Background Art

[0002] An electronic cigarette is an electronic device that simulates a traditional cigarette. The electronic cigarette uses a built-in battery to power the atomizer, which heats the oil to produce steam, and the user inhales the steam through the mouthpiece. Electronic cigarettes are designed to provide the satisfaction of nicotine and reduce the harmful substances produced by the burning of traditional tobacco, but electronic cigarettes are not completely harmless.

[0003] Electronic cigarette smoke detection technology is a key technology to ensure the quality and safety of electronic cigarette products. By monitoring the temperature of electronic cigarettes and controlling the heating performance, the accuracy and stability of the heating temperature of the smoke oil can be ensured to prevent safety hazards caused by overheating. Advanced and efficient chemical analysis methods and professional instruments are used to accurately detect the quality of smoke produced by electronic cigarettes, including the amount of smoke and the content of various substances in the smoke. Advanced chemical analysis methods such as potentiometric titration are used to detect the content of harmful substances such as nicotine and glycerin in the smoke, and the quality of electronic cigarette smoke is comprehensively evaluated to ensure the quality and safety of the product.

[0004] Although the above method solves some problems, there are still some problems. The chemical testing cycle of e-cigarettes is long, which leads to slow quality inspection. Summary of the invention

[0005] The purpose of the present invention is to solve the problem of long chemical detection cycle of electronic cigarettes and to provide a smoke diagnosis method and device for electronic cigarettes.

[0006] In a first aspect of the present invention, a method for diagnosing smoke of an electronic cigarette is first proposed, the method comprising:

[0007] Sending a spray command to the electronic cigarette to make it spray smoke, obtaining a smoke image set by photographing smoke images of the electronic cigarette at multiple angles at a preset time, and calculating the smoke volume of the electronic cigarette according to the smoke image set;

[0008] At the same preset time, a laser beam is emitted to the smoke particles of the electronic cigarette and scattered light of the smoke particles is received, and the particle size and concentration of the smoke particles are calculated according to the scattered light;

[0009] The smoke particle content is calculated by the electronic cigarette smoke volume and the particle concentration, and the smoke quality of the electronic cigarette smoke is diagnosed according to the smoke particle content and the smoke particle diameter.

[0010] Optionally, the smoke image set obtained by shooting smoke images of the electronic cigarette at multiple angles includes:

[0011] The smoke image is converted into a grayscale image, and if the pixel difference value between any adjacent pixel points is greater than the pixel difference threshold, the adjacent pixel points are marked as features;

[0012] If the multiple feature markers are continuous and closed, the area within the multiple feature markers is determined as the target area, and the curve formed by the feature markers is used as the edge;

[0013] The area level corresponding to each target area is determined according to the grayscale average value of each target area; the area level corresponds to the smoke depth.

[0014] Optionally, the electronic cigarette smoke volume is calculated according to the smoke image set, and the method further includes:

[0015] Extracting feature points of each grayscale image in the smoke image set, and matching the same feature points in grayscale images taken at different angles;

[0016] The depth of the stereoscopic model is determined according to the region level in the grayscale image, and a three-dimensional stereoscopic model of the electronic cigarette smoke is established.

[0017] Optionally, calculating the smoke particle size and smoke particle concentration according to the scattered light includes:

[0018] Preprocessing the scattered light data to obtain scattered light intensity time series data, and fitting the scattered light intensity time series data to obtain an autocorrelation function;

[0019] The diffusion coefficient of the smoke particles is calculated according to the autocorrelation function, and the particle size of the smoke particles is calculated according to the diffusion coefficient;

[0020] The concentration of smoke particles is calculated by calculating the scattered light intensity.

[0021] Optionally, diagnosing the smoke quality of the electronic cigarette smoke according to the smoke particle content and the smoke particle size includes:

[0022] Performing smoke quality diagnosis on the electronic cigarette smoke according to the smoke particle content and the smoke particle size;

[0023] If the smoke particle content is not within the preset particle content range, or the smoke particle size is not within the preset particle size range, the quality of the electronic cigarette smoke is determined to be unqualified.

[0024] In a second aspect of the present invention, a smoke diagnostic device for an electronic cigarette is provided, comprising: an image acquisition module, a particle measurement module and a smoke diagnostic module:

[0025] The image acquisition module is used to send an ejection instruction to the electronic cigarette so that the electronic cigarette ejects smoke, obtain a smoke image set by photographing smoke images of the electronic cigarette at multiple angles at a preset time, and calculate the smoke volume of the electronic cigarette according to the smoke image set;

[0026] The particle measurement module is used to emit a laser beam to the smoke particles of the electronic cigarette at the same preset time and receive scattered light from the smoke particles, and calculate the smoke particle diameter and smoke particle concentration according to the scattered light;

[0027] The smoke diagnosis module is used to calculate the smoke particle content through the electronic cigarette smoke volume and the particle concentration, and perform smoke quality diagnosis on the electronic cigarette smoke according to the smoke particle content and the smoke particle diameter.

[0028] Optionally, the image acquisition module includes an image conversion module, a target area determination module and an area level determination module:

[0029] The image conversion module is used to convert the smoke image into a grayscale image, and if the pixel difference value between any adjacent pixel points is greater than the pixel difference threshold, the adjacent pixel points are marked with features;

[0030] The target region determination module is used to determine the region within the plurality of feature marks as the target region if the plurality of feature marks are continuous and closed, and the curve formed by the feature marks as the edge;

[0031] The area level determination module is used to determine the area level corresponding to the target area according to the grayscale average value of each target area; the area level corresponds to the smoke depth.

[0032] Optionally, the marking adding module further includes a feature point matching module and a three-dimensional modeling module:

[0033] The feature point matching module is used to extract the feature points of each grayscale image in the smoke image set and match the same feature points in the grayscale images taken at different angles;

[0034] The three-dimensional modeling module is used to determine the depth of the stereoscopic model according to the region level in the grayscale image, and to establish a three-dimensional model of the electronic cigarette smoke.

[0035] Optionally, the particle measurement module further includes a preprocessing module, a particle size acquisition module and a particle concentration module:

[0036] The preprocessing module is used to perform preprocessing on the scattered light data to obtain scattered light intensity time series data, and to fit the scattered light intensity time series data to obtain an autocorrelation function;

[0037] The particle size acquisition module is used to calculate the diffusion coefficient of smoke particles according to the autocorrelation function, and calculate the particle size of smoke particles through the diffusion coefficient;

[0038] The particle concentration module is used to calculate the smoke particle concentration through the scattered light intensity.

[0039] Optionally, the smoke diagnosis module includes a particle diagnosis module and a quality judgment module:

[0040] The particle diagnosis module is used to diagnose the smoke quality of the electronic cigarette smoke according to the smoke particle content and the smoke particle diameter;

[0041] The quality judgment module is used to determine that the quality of the electronic cigarette smoke is unqualified if the smoke particle content is not within a preset particle content range, or the smoke particle size is not within a preset particle size range.

[0042] Beneficial effects of the present invention:

[0043] The present invention proposes a smoke diagnosis method for an electronic cigarette, which sends a spray command to an electronic cigarette to make it spray smoke, shoots smoke images of the electronic cigarette at multiple angles at a preset time to obtain a smoke image set, and calculates the smoke volume based on the smoke image set. At the same preset time, a laser beam is emitted to the smoke particles of the electronic cigarette and the scattered light of the smoke particles is received, and the particle size and concentration of the smoke particles are calculated based on the scattered light. The smoke particle content is calculated by the smoke volume and particle concentration, and the smoke quality of the electronic cigarette smoke is diagnosed based on the smoke particle content and the smoke particle size. The volume, particle size, particle concentration and smoke particle content of the electronic cigarette smoke are evaluated by shooting electronic cigarette smoke images at multiple angles and combining dynamic light scattering technology, thereby realizing real-time and non-invasive diagnosis of the quality of electronic cigarette smoke. The smoke detection cycle is reduced to ensure the accuracy of the detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] Figure 1 A flow chart of a smoke diagnosis method for an electronic cigarette is provided for an embodiment of the present invention;

[0046] Figure 2 A schematic structural diagram of a smoke diagnostic device for an electronic cigarette is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the present invention, the description of "first", "second", etc. is only used for descriptive purposes, and cannot be understood as indicating or implying its relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" can explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0048] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0049] The embodiment of the present invention provides a method for diagnosing smoke of an electronic cigarette. Figure 1 , Figure 1 A flow chart of a method for diagnosing smoke of an electronic cigarette provided by an embodiment of the present invention. The method comprises the following steps:

[0050] S101, sending a spray instruction to the electronic cigarette to make it spray smoke, obtaining a smoke image set by photographing smoke images of the electronic cigarette at multiple angles at a preset time, and calculating the smoke volume of the electronic cigarette according to the smoke image set.

[0051] S102, emitting a laser beam to the smoke particles of the electronic cigarette at the same preset time and receiving scattered light of the smoke particles, and calculating the particle size and concentration of the smoke particles according to the scattered light.

[0052] S103, calculating the smoke particle content through the electronic cigarette smoke volume and particle concentration, and performing smoke quality diagnosis on the electronic cigarette smoke according to the smoke particle content and smoke particle size.

[0053] Based on an electronic cigarette smoke diagnosis method provided by an embodiment of the present invention, the electronic cigarette smoke image is photographed at multiple angles and combined with dynamic light scattering technology to evaluate the volume, particle size, particle concentration and smoke particle content of the electronic cigarette smoke, thereby achieving real-time, non-invasive diagnosis of the quality of electronic cigarette smoke, reducing the smoke detection cycle and ensuring the accuracy of the detection results.

[0054] In one implementation, a spray command is issued to the electronic cigarette so that the electronic cigarette sprays smoke; by issuing a spray command to a pressure pump in an experimental environment, the pressure pump is operated to create a pressure difference in the experimental environment to achieve the effect of the electronic cigarette spraying smoke.

[0055] In one implementation, a laser beam is emitted into the electronic cigarette smoke through dynamic light scattering technology, and the laser beam is used to illuminate the sample, and the light scattering intensity of the particles in the sample that changes with time is measured. Then, the size and distribution of the particles are calculated with the help of statistical physics theory. This method will have the advantages of being fast, non-invasive, and accurate.

[0056] In one implementation, smoke image capture and dynamic light scattering technology are performed simultaneously, which can provide richer data support, reduce errors caused by environmental changes or time differences, ensure data accuracy and reliability, and make subsequent calculations more valuable.

[0057] In one implementation, the images in the smoke image set are used to convert the planar images into three-dimensional models, and the smoke volume is calculated based on the three-dimensional model, and the particle content is calculated based on the concentration of the smoke particles, which can provide a more accurate and comprehensive analysis of smoke characteristics.

[0058] In one embodiment, step S101 includes:

[0059] The smoke image is converted into a grayscale image. If the pixel difference value between any adjacent pixels is greater than the pixel difference threshold, the adjacent pixels are marked as features.

[0060] If the multiple feature markers are continuous and closed, the area within the multiple feature markers is determined as the target area, and the curve formed by the feature markers is used as the edge.

[0061] The area level corresponding to each target area is determined according to the grayscale average value of each target area; the area level corresponds to the smoke depth.

[0062] In one implementation, edge areas are determined by pixel drop values, which helps to achieve automatic segmentation and identification of smoke particle areas, so that computer recognition can reduce computer mis-cutting and missed cutting. Cutting refers to the process of computer recording various areas of the target image.

[0063] In one implementation, the feature labels are continuous and closed; that is, the area surrounded by the feature labels should be a complete and fully closed area, and the areas can share edges if they have common edges.

[0064] In one embodiment, step S101 further includes:

[0065] The feature points of each grayscale image in the smoke image set are extracted, and the same feature points in the grayscale images taken at different angles are matched.

[0066] The depth of the stereo model is determined according to the regional level in the grayscale image, and a three-dimensional stereo model of the electronic cigarette smoke is established.

[0067] In one implementation, the feature points of each grayscale image can be used to better perform three-dimensional modeling, match the feature points corresponding to images at various angles, determine the positional relationship between each image, and determine the depth of the area based on the area level between each area, which is conducive to accurately establishing a three-dimensional model of electronic cigarette smoke and determining the three-dimensional spatial distance of each image.

[0068] In one implementation, the area level corresponding to each target area is determined by the grayscale average value of each target area; for example, when the grayscale average value of the current area is 255, the area level of the current area is level 1, and the grayscale average value is the average value of the pixel values ​​in the target area. The grayscale average value determines the corresponding area level according to the grayscale interval in which it is located.

[0069] In one embodiment, step S102 includes:

[0070] The scattered light data are preprocessed to obtain scattered light intensity time series data, and the autocorrelation function is obtained by fitting the scattered light intensity time series data.

[0071] The diffusion coefficient of smoke particles is calculated based on the autocorrelation function, and the particle size of smoke particles is calculated based on the diffusion coefficient.

[0072] The concentration of smoke particles is calculated by calculating the scattered light intensity.

[0073] In one implementation, the autocorrelation function is I(t) represents the scattered light intensity at time t, I(t+τ) represents the scattered light intensity at time interval τ, represents the average value of the scattered light intensity; as the time interval τ increases, the correlation of the scattered light intensity decreases due to the Brownian motion of the particles.

[0074] In one implementation, the diffusion coefficient is in n represents the refractive index of the medium, θ is the scattering angle, which is the angle between the incident light and the scattered light, and λ 0 is the wavelength of the incident light in free space; the aerodynamic diameter of the smoke particle is calculated from the diffusion coefficient.

[0075] In one implementation, the smoke particle concentration is calculated by I=I 0*N*Q is calculated, where I represents the scattered light intensity, N represents the smoke particle concentration, Q represents the scattering cross section, and I 0 Represents the incident light intensity; the above parameters can be obtained by experimenters through measurement.

[0076] In one embodiment, step S103 includes:

[0077] Diagnose the smoke quality of electronic cigarette smoke by smoke particle content and smoke particle size;

[0078] If the smoke particle content is not within the preset particle content range, or the smoke particle size is not within the preset particle size range, the electronic cigarette smoke quality is judged to be unqualified.

[0079] In one implementation, by accurately measuring the particle content and particle size in the smoke, it can be ensured that the smoke particles released by the electronic cigarette product during use meet safety standards, thereby reducing the flow of inferior products into the market. This judgment method provides a quantitative judgment basis, making the detection of electronic cigarette smoke quality more rigorous and accurate.

[0080] In one implementation, the smoke particle content is obtained by calculating the three-dimensional volume of the three-dimensional model of the smoke and multiplying it by the particle concentration. The smoke particle content and smoke particle size are obtained by the above-mentioned technical means, which can quickly and accurately obtain the test results, reduce the test cycle, and achieve high-quality product testing.

[0081] Based on the same inventive concept, the present invention also provides a smoke diagnosis device for an electronic cigarette. Figure 2 , Figure 2 A schematic structural diagram of a smoke diagnostic device for an electronic cigarette provided by an embodiment of the present invention includes:

[0082] The image acquisition module is used to send an ejection instruction to the electronic cigarette so that the electronic cigarette ejects smoke, obtain a smoke image set by photographing the smoke image of the electronic cigarette at multiple angles at a preset time, and calculate the smoke volume of the electronic cigarette according to the smoke image set.

[0083] The particle measurement module is used to emit a laser beam to the smoke particles of the electronic cigarette at the same preset time and receive the scattered light of the smoke particles, and calculate the particle size and concentration of the smoke particles based on the scattered light.

[0084] The smoke diagnosis module is used to calculate the smoke particle content through the electronic cigarette smoke volume and particle concentration, and to diagnose the smoke quality of the electronic cigarette smoke according to the smoke particle content and smoke particle size.

[0085] Based on an electronic cigarette smoke diagnostic device provided by an embodiment of the present invention, the electronic cigarette smoke image is photographed at multiple angles and combined with dynamic light scattering technology to evaluate the volume, particle size, particle concentration and smoke particle content of the electronic cigarette smoke, thereby achieving real-time, non-invasive diagnosis of the quality of electronic cigarette smoke, reducing the smoke detection cycle and ensuring the accuracy of the detection results.

[0086] In one embodiment, the image acquisition module includes an image conversion module, a target area determination module and an area level determination module:

[0087] The image conversion module is used to convert the smoke image into a grayscale image. If the pixel difference value between any adjacent pixel points is greater than the pixel difference threshold, the adjacent pixel points are marked with features.

[0088] The target region determination module is used to determine the region within the plurality of feature marks as the target region if the plurality of feature marks are continuous and closed, and the curve formed by the feature marks as the edge.

[0089] The area level determination module is used to determine the area level corresponding to the target area according to the grayscale average value of each target area; the area level corresponds to the smoke depth.

[0090] In one embodiment, the marking adding module further includes a feature point matching module and a 3D modeling module:

[0091] The feature point matching module is used to extract the feature points of each grayscale image in the smoke image set and match the same feature points in the grayscale images taken at different angles.

[0092] The three-dimensional modeling module is used to determine the depth of the three-dimensional model according to the regional level in the grayscale image and establish a three-dimensional model of the electronic cigarette smoke.

[0093] In one embodiment, the particle measurement module further includes a preprocessing module, a particle size acquisition module and a particle concentration module:

[0094] The preprocessing module is used to perform preprocessing on the scattered light data to obtain scattered light intensity time series data, and to fit the scattered light intensity time series data to obtain an autocorrelation function.

[0095] The particle size acquisition module is used to calculate the diffusion coefficient of smoke particles according to the autocorrelation function, and calculate the particle size of smoke particles through the diffusion coefficient.

[0096] The particle concentration module is used to calculate the smoke particle concentration by using the scattered light intensity.

[0097] In one embodiment, the smoke diagnosis module includes a particle diagnosis module and a quality judgment module:

[0098] The particle diagnosis module is used to diagnose the smoke quality of electronic cigarette smoke through smoke particle content and smoke particle size.

[0099] The quality judgment module is used to judge that the quality of the electronic cigarette smoke is unqualified if the smoke particle content is not within the preset particle content range, or the smoke particle size is not within the preset particle size range.

[0100] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for diagnosing smoke of an electronic cigarette, characterized in that: The method comprises: Sending a spray command to the electronic cigarette to make it spray smoke, obtaining a smoke image set by photographing smoke images of the electronic cigarette at multiple angles at a preset time, and calculating the smoke volume of the electronic cigarette according to the smoke image set; At the same preset time, a laser beam is emitted to the smoke particles of the electronic cigarette and scattered light of the smoke particles is received, and the particle size and concentration of the smoke particles are calculated according to the scattered light; The smoke particle content is calculated by the electronic cigarette smoke volume and the particle concentration, and the smoke quality of the electronic cigarette smoke is diagnosed according to the smoke particle content and the smoke particle diameter; The smoke image set obtained by shooting electronic cigarette smoke images from multiple angles includes: The smoke image is converted into a grayscale image, and if the pixel difference value between any adjacent pixel points is greater than the pixel difference threshold, the adjacent pixel points are marked as features; If the multiple feature markers are continuous and closed, the area within the multiple feature markers is determined as the target area, and the curve formed by the feature markers is used as the edge; Determine the area level corresponding to the target area according to the grayscale average value of each target area; the area level corresponds to the smoke depth; The electronic cigarette smoke volume is calculated according to the smoke image set, and the method further comprises: Extracting feature points of each grayscale image in the smoke image set, and matching the same feature points in grayscale images taken at different angles; Determining the depth of the stereoscopic model according to the region level in the grayscale image, and establishing a three-dimensional stereoscopic model of the electronic cigarette smoke; The smoke particle diameter and smoke particle concentration calculated according to the scattered light include: Preprocessing the scattered light data to obtain scattered light intensity time series data, and fitting the scattered light intensity time series data to obtain an autocorrelation function; The diffusion coefficient of the smoke particles is calculated according to the autocorrelation function, and the particle size of the smoke particles is calculated according to the diffusion coefficient; The concentration of smoke particles is calculated by calculating the scattered light intensity.

2. The electronic cigarette smoke diagnosis method according to claim 1, characterized in that: Diagnosing the smoke quality of the electronic cigarette smoke according to the smoke particle content and the smoke particle diameter includes: Performing smoke quality diagnosis on the electronic cigarette smoke according to the smoke particle content and the smoke particle size; If the smoke particle content is not within the preset particle content range, or the smoke particle size is not within the preset particle size range, the quality of the electronic cigarette smoke is determined to be unqualified.

3. An electronic cigarette smoke diagnostic device, characterized in that: The device comprises an image acquisition module, a particle measurement module and a smoke diagnosis module: The image acquisition module is used to send an ejection instruction to the electronic cigarette so that the electronic cigarette ejects smoke, obtain a smoke image set by photographing smoke images of the electronic cigarette at multiple angles at a preset time, and calculate the smoke volume of the electronic cigarette according to the smoke image set; The particle measurement module is used to emit a laser beam to the smoke particles of the electronic cigarette at the same preset time and receive scattered light from the smoke particles, and calculate the smoke particle diameter and smoke particle concentration according to the scattered light; The smoke diagnosis module is used to calculate the smoke particle content through the electronic cigarette smoke volume and the particle concentration, and perform smoke quality diagnosis on the electronic cigarette smoke according to the smoke particle content and the smoke particle diameter; The image acquisition module includes an image conversion module, a target area determination module and an area level determination module: The image conversion module is used to convert the smoke image into a grayscale image, and if the pixel difference value between any adjacent pixel points is greater than the pixel difference threshold, the adjacent pixel points are marked with features; The target region determination module is used to determine the region within the plurality of feature marks as the target region if the plurality of feature marks are continuous and closed, and the curve formed by the feature marks as the edge; The area level determination module is used to determine the area level corresponding to the target area according to the grayscale average value of each target area; the area level corresponds to the smoke depth; The marking module also includes a feature point matching module and a 3D modeling module: The feature point matching module is used to extract the feature points of each grayscale image in the smoke image set and match the same feature points in the grayscale images taken at different angles; The three-dimensional modeling module is used to determine the depth of the stereoscopic model according to the region level in the grayscale image, and to establish a three-dimensional model of the electronic cigarette smoke; The particle measurement module also includes a preprocessing module, a particle size acquisition module and a particle concentration module: The preprocessing module is used to perform preprocessing on the scattered light data to obtain scattered light intensity time series data, and to fit the scattered light intensity time series data to obtain an autocorrelation function; The particle size acquisition module is used to calculate the diffusion coefficient of smoke particles according to the autocorrelation function, and calculate the particle size of smoke particles through the diffusion coefficient; The particle concentration module is used to calculate the smoke particle concentration through the scattered light intensity.

4. The smoke diagnostic device for an electronic cigarette according to claim 3, characterized in that: The smoke diagnosis module includes a particle diagnosis module and a quality judgment module: The particle diagnosis module is used to diagnose the smoke quality of the electronic cigarette smoke according to the smoke particle content and the smoke particle diameter; The quality judgment module is used to determine that the quality of the electronic cigarette smoke is unqualified if the smoke particle content is not within a preset particle content range, or the smoke particle size is not within a preset particle size range.

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