Space dust concentration detection method based on pattern recognition and infrared thermal imaging hybrid algorithm

Abstract

The invention relates to a space dust concentration detection method based on a pattern recognition and infrared thermal imaging mixed algorithm, and belongs to the field of dust concentration detection. The method comprises the following steps: on the basis of an optical image dust concentration identification method, introducing infrared thermal imaging, separating and identifying distribution of background and dust particles by utilizing the infrared thermal imaging, distinguishing and identifying water mist on an optical image, and realizing full-region dust concentration detection in a spraying or high-mist environment; aiming at the defect that water mist and dust cannot be effectively distinguished in the existing image dust concentration identification, an infrared thermal imaging technology is introduced, and a separation algorithm is combined, so that the dust concentration detection of the whole space is realized in a spraying environment.

Description

Technical Field

[0001] The invention belongs to the field of dust concentration detection and relates to a spatial dust concentration detection method using a hybrid algorithm of pattern recognition and infrared thermal imaging. Background Art

[0002] At present, there are many mines, the dust hazards are serious, and pneumoconiosis is prevalent. At the same time, there are many and scattered dust-producing points in the mines. At present, the detection of dust concentration is only a single point detection. The dust concentration detection based on image recognition technology in the ground environment is also in the initial research stage.

[0003] Regarding the impact of image dust concentration recognition technology on moisture in the environment, existing technologies do have some limitations, especially in high-water environments, such as underground coal mines, and in spray dust reduction areas, where this impact is more obvious.

[0004] Existing dust concentration identification technology is mainly based on optical images. The advantages of this method are simple equipment and fast measurement speed, but for moisture in the environment, especially in a high-water environment, it may be difficult to distinguish between dust and moisture due to changes in image reflectivity.

[0005] To solve this problem, researchers have tried to use more complex image processing techniques and machine learning algorithms, such as dust concentration measurement algorithms based on image transmittance. This technology distinguishes between dust and moisture by analyzing the transmittance characteristics of the image and combining other information of the image, such as color and brightness. Although this technology solves the problem to a certain extent, further research and improvement may be needed in certain specific environments and conditions, such as high water content environments.

[0006] In addition, some researchers are trying to use more advanced image recognition techniques, such as deep learning, to distinguish between dust and moisture. 8 This technology can better understand and interpret complex patterns and structures in images, and may provide a more effective way to distinguish between dust and moisture in the future.

[0007] In general, existing image dust concentration recognition technologies face certain challenges when dealing with dust in high-water environments and spray dust fall areas, but researchers are exploring and developing better methods to improve the accuracy and reliability of dust identification.

[0008] Existing image dust concentration recognition technology basically only considers dust concentration measurement based on the optical image itself. This method is difficult to effectively distinguish the interference of water in the environment on dust concentration. Coal mines are high-water environments, especially in areas where spray dust reduction is carried out. A single optical image cannot distinguish between spray and particulate matter. Summary of the invention

[0009] In view of this, the purpose of the present invention is to provide a spatial dust concentration detection method using a hybrid algorithm of pattern recognition and infrared thermal imaging. Infrared thermal imaging combined with optical imaging can effectively remove water mist in the environment, and combined with optical imaging to measure the total dust concentration, rapid full-space dust concentration detection can be achieved. This technology is particularly suitable for high water mist environments with spray dust reduction at underground working surfaces, effectively removing the impact of water mist on image recognition technology.

[0010] In order to achieve the above object, the present invention provides the following technical solutions:

[0011] A spatial dust concentration detection method using a hybrid algorithm of pattern recognition and infrared thermal imaging, the method comprising the following steps:

[0012] Based on the optical image dust concentration identification method, infrared thermal imaging is introduced to separate and identify the background and the distribution of dust particles, distinguish and identify water mist on the optical image, and realize the full-area dust concentration detection in the spray or high fog environment;

[0013] The optical image dust concentration recognition method is specifically as follows:

[0014] Assume that for any point x in space, the optical image RGB value and the corresponding coordinates are the matrix formula I(x), the infrared thermal image is R(x), and in a clean environment without dust and water mist, the background image is J(x), and the dust concentration value C is solved;

[0015] The water mist recognition algorithm of infrared thermal imaging obtained through learning and training, F[J(x), R(x)] = r, the value of the influence factor of fog particles on the transmittance of the image is obtained, and the expression of the ambient light influence solved by the original optical image dust concentration recognition algorithm is A(x). Then the transmittance value of the dust image corresponding to point x is c(x) solved by the following formula (1):

[0016] I(x)=J(x)*[1-c(x)-r]+A(c(x)+r)(1)

[0017] The dust concentration value C is solved from the corresponding relationship between the original dust concentration and the image transmittance;

[0018] The method of separating and identifying the distribution of background and dust particles by infrared thermal imaging is as follows:

[0019] In dust concentration detection, infrared thermal imaging technology uses the thermal radiation characteristics of dust particles to distinguish the thermal radiation intensity of dust particles from the background environment, thereby identifying and locating dust particles; then, by analyzing the thermal radiation intensity of dust, the dust concentration information is obtained.

[0020] Optionally, the infrared thermal imaging technology collects thermal radiation information of dust particles through infrared thermal imaging equipment and converts it into images and graphics for human visual discrimination; by analyzing the thermal radiation characteristics of dust, its physical and chemical properties are inferred to achieve dust concentration detection.

[0021] Optionally, the thermal radiation information includes thermal radiation characteristics of dust particles, thermal radiation intensity of dust particles and radiation temperature of dust particles;

[0022] The thermal radiation characteristics of the dust particles are reflected in their thermal radiation intensity and radiation temperature;

[0023] The thermal radiation intensity of the dust particles is related to their particle size, shape and physical properties;

[0024] The radiation temperature of the dust particles is related to their particle size, shape and physical properties.

[0025] Optionally, the spatial dust concentration detection method is applied in a spray or high fog environment.

[0026] The beneficial effect of the present invention is that: in view of the shortcoming that the existing image dust concentration recognition cannot effectively distinguish between water mist and dust, infrared thermal imaging technology is introduced, combined with a separation algorithm, to realize full-space dust concentration detection in a spray environment.

[0027] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0029] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0030] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0031] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0032] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0033] See also Figure 1 , which is a spatial dust concentration detection method based on a hybrid algorithm of pattern recognition and infrared thermal imaging.

[0034] Based on the method of identifying dust concentration in optical images, infrared thermal imaging is introduced, and an algorithm is designed to use infrared thermal imaging to separate and identify the background and the distribution of dust particles, so as to distinguish and identify water mist in the optical image, thereby achieving the purpose of detecting dust concentration in the entire area in a spray or high fog environment.

[0035] (1) Method of optical image dust concentration recognition

[0036] Assume that for any point x in space, the optical image RGB value and the corresponding coordinates are the matrix formula I(x), the infrared thermal image is R(x), and in a clean environment without dust and water mist, the background image is J(x), and the dust concentration value C is solved;

[0037] The water mist recognition algorithm of infrared thermal imaging obtained through learning and training, F[J(x), R(x)] = r, the value of the influence factor of fog particles on the transmittance of the image is obtained, and the expression of the ambient light influence solved by the original optical image dust concentration recognition algorithm is A(x). Then the transmittance value of the dust image corresponding to point x is c(x) solved by the following formula (1):

[0038] I(x)=J(x)*[1-c(x)-r]+A(c(x)+r)(1)

[0039] Then, the dust concentration value C is solved based on the corresponding relationship between the original dust concentration and the image transmittance.

[0040] The main innovation of this algorithm lies in the machine learning and process of F[J(x), R(x)] = r, as well as the adjustment and learning of formula (1) based on the original optical image dust concentration recognition algorithm formula for water mist and dust particles, one is the refraction of light, and the other is the diffuse reflection and occlusion of light.

[0041] Optical image dust concentration recognition is mainly based on image processing technology. A common method is the dust concentration measurement algorithm based on image transmittance. This algorithm extracts the transmittance characteristics of the dust image and calculates the transmittance value of the dust image in combination with the image saturation and brightness information. Finally, it establishes a mapping relationship between dust concentration and image transmittance, thus achieving efficient and high-precision measurement of dust concentration.

[0042] Specifically, the algorithm first builds a dust concentration visual measurement experimental platform, collects dust images, and then extracts the transmittance characteristics of the dust images. Then, based on the dark channel theory, the transmittance value of the dust image is calculated by combining the image saturation and brightness information. Finally, the mapping relationship between dust concentration and image transmittance is established by polynomial fitting, thereby achieving high-efficiency and high-precision measurement of dust concentration.

[0043] The research results show that the algorithm can not only effectively measure the dust concentration, but also has an average relative error of only 7.77%, which effectively improves the accuracy and has a larger measurement range. This dust concentration identification method based on image transmittance has been widely used in practical applications, such as real-time online monitoring of the dust concentration generated during the loading and unloading and transportation of particulate materials.

[0044] (2) Application of infrared thermal imaging in dust concentration detection

[0045] Infrared thermal imaging technology is a technology that receives the infrared radiation energy of the target through an infrared detector, then reflects it to the photosensitive element of the infrared detector to obtain an infrared thermal image and display the temperature distribution of the object's surface in different colors.

[0046] In the detection of dust concentration, infrared thermal imaging technology can use the thermal radiation characteristics of dust particles to distinguish the thermal radiation intensity of dust particles from the background environment, thereby realizing the identification and location of dust particles. Then, by analyzing the thermal radiation intensity of dust, the concentration information of dust can be obtained.

[0047] Infrared thermal imaging technology can indeed use the thermal radiation characteristics of dust particles to detect dust concentration. The basic principle of this technology is to collect the thermal radiation information of dust particles through infrared thermal imaging equipment and convert it into images and graphics that can be distinguished by human vision. Since the thermal radiation characteristics of dust particles are affected by their physical and chemical properties, particle size, shape and other factors, by analyzing the thermal radiation characteristics of dust, its physical and chemical properties can be inferred, thereby realizing the detection of dust concentration.

[0048] Specifically, the thermal radiation characteristics of dust particles are mainly reflected in their thermal radiation intensity and radiation temperature. The thermal radiation intensity of dust particles is related to factors such as their particle size, shape, and physical properties, while their radiation temperature is related to factors such as their particle size, shape, and physical properties. In actual detection, infrared thermal imaging equipment can accurately obtain the thermal radiation intensity and radiation temperature information of dust particles, and through data processing and analysis, obtain the physical and chemical properties of dust, and then deduce the concentration of dust.

[0049] In addition, the application of infrared thermal imaging technology in dust concentration detection also has the advantages of non-contact, no interference, fast response speed, and high measurement accuracy. In some special environments, such as high temperature and high dust concentration, infrared thermal imaging technology can also be effectively applied and provide new possibilities for dust concentration detection.

[0050] Specifically, when the temperature of dust particles is higher than the background environment, infrared thermal imaging technology can "light up" the thermal radiation intensity of the dust particles and display it on the thermal image. By comparing the difference between the dust thermal image and the background thermal image, the thermal radiation intensity of the dust particles can be obtained and further converted into dust concentration.

[0051] Implementation Method 1

[0052] Optical image dust concentration recognition method:

[0053] Suppose a point x in the space, the optical image RGB value is [255,150,100], and the corresponding coordinates are (10,20).

[0054] The temperature at this point obtained by the infrared thermal imaging device is 25°C.

[0055] In an environment without dust and water mist, the RGB value of the background image is [250, 140, 90].

[0056] The trained infrared thermal imaging water mist recognition algorithm outputs a value of 0.1 for the influence factor of fog particles on image transmittance.

[0057] Calculate the dust image transmittance value at point x according to formula (1):

[0058] Ambient light impact expression: A(x) = (255-250) / 255 = 0.02

[0059] Dust image transmittance value: T(x) = 0.9*0.9*(1-0.02)*(1-0.1) = 0.78

[0060] According to the established mapping relationship between dust concentration and image transmittance, the dust concentration at point x is 5 mg / m 3 .

[0061] Infrared thermal imaging:

[0062] The infrared thermal imaging device obtains the temperature of this point as 25℃, and the background ambient temperature is 20℃.

[0063] Since the temperature of dust particles is higher than the background environment, this point appears as an obvious high-temperature area on the infrared thermal image.

[0064] Combined with optical image analysis, it was confirmed that the high-temperature area was dust particles, not water mist or background.

[0065] In practical applications, this method can realize dust concentration detection in the entire area under high dust concentration environments, such as spray or high fog environments, thereby providing important data support for dust control and safe production.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A spatial dust concentration detection method using a hybrid algorithm of pattern recognition and infrared thermal imaging, characterized in that: The method comprises the following steps: Based on the optical image dust concentration identification method, infrared thermal imaging is introduced to separate and identify the background and the distribution of dust particles, distinguish and identify water mist on the optical image, and realize the full-area dust concentration detection in the spray or high fog environment; The optical image dust concentration recognition method is specifically as follows: Assume that for any point x in space, the optical image RGB value and the corresponding coordinates are the matrix formula I(x), the infrared thermal image is R(x), and in a clean environment without dust and water mist, the background image is J(x), and the dust concentration value C is solved; The water mist recognition algorithm of infrared thermal imaging obtained through learning and training, F[J(x), R(x)] = r, the value of the influence factor of fog particles on the transmittance of the image is obtained, and the expression of the ambient light influence solved by the original optical image dust concentration recognition algorithm is A(x). Then the transmittance value of the dust image corresponding to point x is c(x) solved by the following formula (1): I(x)=J(x)*[1-c(x)-r]+A(c(x)+r) (1) The dust concentration value C is solved from the corresponding relationship between the original dust concentration and the image transmittance; The method of separating and identifying the distribution of background and dust particles by infrared thermal imaging is as follows: In dust concentration detection, infrared thermal imaging technology uses the thermal radiation characteristics of dust particles to distinguish the thermal radiation intensity of dust particles from the background environment, thereby identifying and locating dust particles; then, by analyzing the thermal radiation intensity of dust, the dust concentration information is obtained.

2. The spatial dust concentration detection method of the hybrid algorithm of pattern recognition and infrared thermal imaging according to claim 1 is characterized in that: The infrared thermal imaging technology collects the thermal radiation information of dust particles through infrared thermal imaging equipment and converts it into images and graphics for human visual discrimination; by analyzing the thermal radiation characteristics of dust, its physical and chemical properties are inferred to achieve dust concentration detection.

3. The spatial dust concentration detection method based on the hybrid algorithm of pattern recognition and infrared thermal imaging according to claim 1 is characterized in that: The thermal radiation information includes the thermal radiation characteristics of the dust particles, the thermal radiation intensity of the dust particles and the radiation temperature of the dust particles; The thermal radiation characteristics of the dust particles are reflected in their thermal radiation intensity and radiation temperature; The thermal radiation intensity of the dust particles is related to their particle size, shape and physical properties; The radiation temperature of the dust particles is related to their particle size, shape and physical properties.

4. The spatial dust concentration detection method of the hybrid algorithm of pattern recognition and infrared thermal imaging according to claim 3 is characterized in that: The spatial dust concentration detection method is applied in a spray or high fog environment.

Images