Intelligent dust-settling method and system based on dust source identification for precise target spraying

Abstract

The present application relates to the technical field of spray dust-settling, and particularly relates to a precision target spray intelligent dust-settling method and system based on dust source identification, which acquires a dust-free scene image and a real-time shooting image of a fixed dust-settling point, obtains a dust area based on the difference between the dust-free scene image and the real-time shooting image, and then obtains a spray trajectory according to the dust area and a preset forbidden spray area in the dust-free scene image, wherein the spray trajectory is only used for spraying the outer contour of the dust area, and finally, based on the spray trajectory control, the spray dust-settling equipment is controlled to perform one outer spray dust-settling at the fixed dust-settling point, and then the above process is repeated to complete the spray dust-settling. The present application adopts a layered progressive dust-settling strategy, so that the cement plant dust-settling material has the least influence on the equipment and the pollution to the material, and solves the problem that the existing spray dust-settling technology has a greater influence on the cement plant site environment.

Description

Technical Field

[0001] This invention relates to the field of spray dust suppression technology, and in particular to a precise targeted spray intelligent dust suppression method and system based on dust source identification. Background Technology

[0002] Spray dust suppression technology is an environmental protection technology that uses high pressure to atomize liquid into micron- or even nano-sized droplets. By increasing the contact area between the droplets and airborne dust particles, the droplets adhere to each other, agglomerate, and settle under their own weight, thereby purifying the air and suppressing dust dispersion. Currently, this technology is widely used in coal mines, construction sites, ports, and various industrial production sites. Its core control logic is gradually evolving from traditional timed and frequency-based coarse spraying to intelligent and precise control based on sensor feedback.

[0003] However, unlike dust suppression spraying in other fields, cement plant dust mainly consists of silicate materials such as limestone, clinker, and raw meal. These materials are not only extremely hydrophilic but also undergo hydration reactions upon contact with water. In cement plant dust control, cement dust will rapidly hydrate and become viscous upon contact with even a small amount of water, subsequently drying and caking. This leads to two problems: firstly, caking will occur on the surfaces of cement plant equipment or the ground; secondly, excessive water spraying will cause the material's moisture content to exceed the standard, affecting the quality of cement firing.

[0004] Therefore, there is a need for a dust suppression spraying method that can reduce the environmental impact of cement plants. Summary of the Invention

[0005] Therefore, this invention provides a precise targeted spray intelligent dust suppression method and system based on dust source identification, in order to solve the problem that the existing spray dust suppression technology has a significant impact on the on-site environment of cement plants.

[0006] This invention provides a precise targeted spray intelligent dust suppression method based on dust source identification, comprising: Obtain cleanroom scene images and real-time images captured at fixed dust collection points. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained. Based on the dusty area and the pre-defined no-spray area in the cleanroom scene image, the spray trajectory is obtained. The spray trajectory is only used for the outer contour of the dusty area. Based on spray trajectory control, the spray dust suppression equipment is controlled to perform an outer layer of spray dust suppression at a fixed dust suppression point; The process involves repeatedly acquiring cleanroom scene images and real-time images captured at fixed dust suppression points, obtaining the dust area based on the difference between the cleanroom scene images and the real-time images, obtaining the spray trajectory based on the dust area and the preset no-spray area in the cleanroom scene images, and controlling the spray dust suppression equipment to perform one outer layer spray dust suppression at the fixed dust suppression point based on the spray trajectory control.

[0007] In a further embodiment: A cleanroom scene image captured at a fixed dust collection point and a real-time captured image are obtained. Based on the difference between the cleanroom scene image and the real-time captured image, a dust area is obtained, including: Acquire cleanroom scene images and real-time images captured at fixed dust collection points, and perform differential analysis on the cleanroom scene images and real-time images to obtain differential images; The region mask is obtained by filtering the difference image based on an adaptive threshold; Calculate the optical flow vector field of the region mask, and filter the region mask according to the optical flow vector field to obtain the dust mask; Based on the local contrast of the dust mask, the transmittance of the dust mask is verified to obtain the dust area.

[0008] In a further embodiment: calculating the optical flow vector field of the region mask, and filtering the region mask based on the optical flow vector field to obtain a dust mask, including: Divide the region mask into multiple connected domains; Select multiple key points in the connected domain and calculate the optical flow vector for each key point; Based on the consistency of multiple optical flow vectors in each connected region, multiple connected regions are filtered to obtain a dust mask.

[0009] In a further embodiment: the spray trajectory is obtained based on the dusty area and a preset no-spray zone in the cleanroom scene image, including: Based on the dust region, the set of boundary points is obtained; Calculate the local gradient direction for each boundary point in the boundary point set; By filtering out boundary points whose local gradient direction points to the centroid of the dust region, the diffusion outer contour point set is obtained. The spray trajectory is obtained based on the diffusion outer contour point set and the preset no-spray area in the cleanroom scene image.

[0010] In a further embodiment: it also includes: Obtain the dust area corresponding to multiple adjacent outer layer dust suppression sprays, and determine whether dust diffusion is suppressed based on the changes in the dust area corresponding to multiple adjacent outer layer dust suppression sprays. If it is determined that dust diffusion is suppressed, the spray dust suppression equipment is controlled to perform rapid spray dust suppression on the dust area corresponding to the last outer layer of spray dust suppression. The spray intensity of the rapid spray dust suppression is higher than that of the outer layer of spray dust suppression.

[0011] In a further embodiment: obtaining the dust areas corresponding to multiple adjacent outer layer dust suppression sprays, and determining whether dust diffusion is suppressed based on the changes in the dust areas corresponding to multiple adjacent outer layer dust suppression sprays, including: Obtain the dust area and spray parameters corresponding to the current outer layer dust suppression spray and the previous outer layer dust suppression spray; Based on the changes in the dust area corresponding to the two outer spray dust suppressions, the theoretical dust suppression effect that can be achieved based on the spray parameters is verified, and the suppression effect coefficient corresponding to this outer spray dust suppression is obtained. The change in the suppression effect coefficient corresponding to multiple outer layer dust suppression sprays is used to determine whether dust diffusion has been suppressed.

[0012] In a further embodiment: based on the changes in the dust area corresponding to the two outer layer dust suppression operations, the theoretical dust suppression effect achievable by the spray parameters is verified to obtain the suppression effect coefficient corresponding to this outer layer dust suppression, including: Based on the differences in the dust areas corresponding to this outer layer dust suppression, the dust difference areas are obtained; The area change rate is obtained based on the dust difference region; Based on the spray parameters corresponding to this outer layer dust suppression, calculate the theoretical dust suppression rate and spray coverage area; Based on the differences in theoretical dust suppression rate and area change rate, and the crossover ratio of the spray coverage area and the dust difference area, the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained.

[0013] In a further embodiment: the spray trajectory is obtained based on the diffusion outline point set obtained from the dust region; the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained based on the difference between the theoretical dust suppression rate and the area change rate, and the intersection-exchange ratio of the spray coverage area and the dust difference area, including: Obtain the diffusion outer contour point set of the dust region corresponding to the two outer layer dust suppression sprays and the centroid of the dust region; Based on the centroid inside the dust region, the positional relationship of the diffusion outer contour point set of the dust region corresponding to the two outer spray dust suppressions is determined, and the edge shrinkage coefficient is obtained based on the positional relationship. Based on the differences in theoretical dust suppression rate and area change rate, the crossover ratio between the spray coverage area and the dust difference area, and the edge retreat coefficient, the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained.

[0014] In a further embodiment: controlling the spray dust suppression device to rapidly spray dust suppression onto the dust area corresponding to the last outer layer of spray dust suppression, including: Based on the dust area corresponding to the last outer layer dust suppression spray, the dust location and dust load parameters are obtained; The dust suppressant ratio is obtained based on the dust load parameters; Based on the dust suppressant ratio and dust location, the spray dust suppression equipment is controlled to quickly spray dust suppression on the dust area corresponding to the last outer layer of dust suppression.

[0015] This invention also provides a precise targeted spray intelligent dust suppression system based on dust source identification, including a spray dust suppression device and a control module, the control module including: The image acquisition module is used to acquire cleanroom scene images and real-time images taken at fixed dust collection points. The dust area is obtained based on the difference between the cleanroom scene images and the real-time images. The dust analysis module is used to obtain the spray trajectory based on the dust area and the preset no-spray area in the dust-free scene image. The spray trajectory is only used for the outer contour of the dust area. The spray control module is used to control the spray dust suppression equipment to perform an outer layer of spray dust suppression at a fixed dust suppression point based on spray trajectory control; The control module is used to repeatedly acquire cleanroom scene images and real-time images captured at fixed dust suppression points through the image acquisition module, dust suppression analysis module, and spray control module. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained. Based on the dust area and the preset no-spray area in the cleanroom scene image, the spray trajectory is obtained. Based on the spray trajectory control, the spray dust suppression equipment is controlled to perform one outer layer spray dust suppression at the fixed dust suppression point.

[0016] The beneficial effects of adopting the above scheme are: This invention provides a precise targeted spray intelligent dust suppression method based on dust source identification. It acquires cleanroom scene images and real-time images taken at fixed dust suppression points. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained. Then, based on the dust area and a preset no-spray zone in the cleanroom scene image, a spray trajectory is obtained. The spray trajectory is only used to spray the outer contour of the dust area. Finally, based on the spray trajectory control, the spray dust suppression equipment is controlled to perform one outer layer spray dust suppression at the fixed dust suppression point, and then the above process is repeated to complete the spray dust suppression. Compared with existing technologies, this invention adopts a layered and progressive dust suppression strategy. Each spray dust suppression targets only the outer contour of the dust area, and through repeated cycles, the spray gradually contracts towards the center of the dust mass, thereby achieving dust suppression. This small-volume, multiple-spray approach effectively controls the spray volume, ensuring that the dust is eliminated in the air and that the water mist completely evaporates or adsorbs the dust before landing. Even if the dust cannot be completely eliminated in one spray, it effectively inhibits the diffusion of dust masses from the edges to the no-spray zone, minimizing material humidification or equipment caking. Meanwhile, this invention identifies dust areas and performs spray dust suppression based on fixed dust suppression points. By setting up no-spray zones, it avoids the locations of equipment and materials, minimizing the impact of dust on equipment caking and material contamination in cement plants. This solves the problem that existing spray dust suppression technologies have a significant impact on the on-site environment of cement plants. Attached Figure Description

[0017] Figure 1 The flowchart of the precise targeted spray intelligent dust suppression method based on dust source identification provided by the present invention; Figure 2 for Figure 1 A detailed step diagram of step S101 is shown below; Figure 3 for Figure 1 A detailed step diagram of step S102 is shown below; Figure 4 for Figure 1 A detailed step diagram of step S104 is shown below; Figure 5 The system architecture diagram of the precision targeted spray intelligent dust suppression system based on dust source identification provided by the present invention; Figure 6 This is a schematic diagram of the structure of the spray dust suppression device in this invention. Detailed Implementation

[0018] 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.

[0019] Please see Figure 1 A specific embodiment of the present invention discloses a precise targeted spray intelligent dust suppression method based on dust source identification, comprising: S101. Obtain the dust-free scene image and the real-time image captured at the fixed dust collection point. Based on the difference between the dust-free scene image and the real-time image, obtain the dust area. S102. Based on the dust area and the preset no-spray area in the dust-free scene image, the spray trajectory is obtained. The spray trajectory is only used for the outer contour of the dust area. S103. Based on spray trajectory control, control the spray dust suppression equipment to perform one outer layer spray dust suppression at a fixed dust suppression point; Repeat steps S101-S103: acquire cleanroom scene images and real-time images captured at fixed dust suppression points; obtain the dust area based on the difference between the cleanroom scene images and the real-time images; obtain the spray trajectory based on the dust area and the preset no-spray area in the cleanroom scene images; and control the spray dust suppression equipment to perform one outer layer spray dust suppression at the fixed dust suppression point based on the spray trajectory control.

[0020] Taking coal mines, steel mills, or construction sites as examples, coal dust has a very strong water-repellent surface. If only water is sprayed, the water droplets will roll off the coal dust like water droplets on a lotus leaf, making it difficult to wet it. Metal ore / gravel dust is generally inert and does not react chemically. Although it will absorb water and become heavier, it is simply a physical mixture. Therefore, dust suppression in coal mines or steel mills and other fields does not need to worry about dust clumping when it comes into contact with water; the only concern is how to add surfactants to make the coal dust "willing" to absorb water.

[0021] Cement plant dust is entirely different. It is not only extremely hydrophilic, but also undergoes a hydration reaction upon contact with water. High concentrations of cement dust, once exposed to sprayed water droplets, will absorb moisture and become viscous within seconds. On one hand, the reacted dust will form layers of hardened slabs on the outer walls of equipment or the inner walls of related pipes. On the other hand, if dust control is inadequate, excessive water mixing into raw materials or finished products will severely affect the final quality of the cement.

[0022] This invention uses a layered, progressive spraying method to dynamically suppress dust as it gradually shrinks from the outside in. This ensures effective dust control while minimizing direct contact between water mist and materials and equipment. This fundamentally avoids the problem of cement dust causing hardening on the ground and equipment surfaces due to hydration reactions. At the same time, it effectively prevents excessive moisture from mixing into raw materials or finished products, ensuring the stability of the cement firing process and product quality.

[0023] Specifically, this invention does not aim to achieve complete, one-time dust suppression. Instead, it targets the edges of dust particles, using a light spray to inhibit diffusion, thereby gradually eliminating dust layer by layer from the outer edge. In each layer of spraying, the spray pressure, flow rate, and particle size can be controlled to eliminate dust in the air, ensuring that the water mist completely evaporates or forms extremely light agglomerates before landing, reducing the moisture content before landing, and preventing contact with materials and equipment, thus avoiding material humidification or equipment caking.

[0024] Furthermore, in this invention, fixed dust suppression points refer to fixed dust-generating points in cement plants, such as raw material storage yards, conveyor belts, and packaging machines, which are also the points where dust suppression is performed in step S103. It is understood that in practice, spray dust suppression is a three-dimensional problem. To achieve automatic spray dust suppression using AI vision, it is necessary not only to analyze the morphology of the dust from the image but also to analyze its positional coordinates. This embodiment sets fixed dust suppression points to acquire images and limits spray dust suppression to those locations. This not only allows subsequent steps to achieve rapid image analysis of the dust using differential methods but also replaces depth control by pre-selecting and configuring fixed dust suppression points, solving the problem of calculating depth information in image recognition and significantly improving computational efficiency. In addition, by setting no-spray zones in the image at fixed dust suppression points, critical equipment or raw materials can be avoided, thereby minimizing the impact on the cement plant environment.

[0025] For further details, please refer to Figure 2 In one embodiment, step S101, acquiring a dust-free scene image and a real-time captured image from a fixed dust collection point, and obtaining the dust area based on the difference between the dust-free scene image and the real-time captured image, specifically includes: S201. Obtain cleanroom scene images and real-time images captured at fixed dust collection points, and perform differential analysis on the cleanroom scene images and real-time images to obtain differential images. S202. Based on adaptive thresholding, the difference image is filtered to obtain a region mask; S203. Calculate the optical flow vector field of the region mask, and filter the region mask according to the optical flow vector field to obtain the dust mask; S204. Based on the local contrast in the dust mask, verify the transmittance of the dust mask to obtain the dust area.

[0026] Uneven lighting may exist in cement plants, therefore this embodiment selects an adaptive threshold (such as the Otsu algorithm) for differential grading. Simultaneously, since this embodiment primarily focuses on dust reduction at dust edges, it employs optical flow vector field filtering and transmittance verification using local contrast instead of the complex internal texture analysis in existing technologies, improving the recognition speed of dust areas. Specifically, due to the turbulent nature of dust, the motion vector directions of pixels within the dust are chaotic, varying in magnitude, and exhibit low motion consistency. Therefore, if the magnitude of the variance of the optical flow vector within the connected domain of the region mask is greater than a threshold, it can be identified as dust. For example, if the optical flow vector directions within the connected domain of the region mask are highly consistent and have similar magnitudes, it can be considered material from a vehicle or conveyor belt, and thus can be directly removed from the region mask. Furthermore, since cement dust often appears as a grayish-white mist, the contrast of the dust area is significantly lower than that of the background. Therefore, the local contrast in the dust mask can be calculated; if the contrast is lower than a specific multiple of the background contrast, such as 0.3, it can be confirmed as a dust area. In this way, the complex internal texture feature extraction is skipped, and only simple statistical methods are used for verification.

[0027] Furthermore, in a preferred embodiment, the specific process of calculating the optical flow field vector, namely step S203 above, calculating the optical flow vector field of the region mask, and filtering the region mask according to the optical flow vector field to obtain the dust mask, specifically includes: Divide the region mask into multiple connected domains; Select multiple key points in the connected domain and calculate the optical flow vector for each key point; Based on the consistency of multiple optical flow vectors in each connected region, multiple connected regions are filtered to obtain a dust mask.

[0028] This embodiment calculates the optical flow vector field by dividing connected components and selecting key points (such as boundary corners and other feature points). Essentially, it uses sparse optical flow instead of dense optical flow (calculating every pixel). This is because sparse computation only processes a few hundred points, significantly improving the real-time performance of this method. Furthermore, the internal texture of dust is weak, and dense optical flow would generate a large amount of noise and voids. In addition, as will be seen in another embodiment described later, a further objective of dust region identification is to extract the outer contour of the diffusion direction and determine the motion type; therefore, it is not necessary to know the specific displacement of each pixel.

[0029] It is understood that the process of calculating the optical flow field vector is existing technology that can be understood by those skilled in the art, and therefore will not be described in detail.

[0030] Furthermore, in combination Figure 3In one embodiment, step S102, obtaining the spray trajectory based on the dust area and the preset no-spray area in the cleanroom scene image, specifically includes: S301. Obtain the set of boundary points based on the dust region; S302. Calculate the local gradient direction of each boundary point in the boundary point set; S303. Remove boundary points whose local gradient direction points to the centroid of the dust region to obtain the diffusion outer contour point set; S304. Obtain the spray trajectory based on the diffusion outer contour point set and the preset no-spray area in the cleanroom scene image.

[0031] Because this invention uses a progressive dust reduction process from the outside in, only the outward diffusion edges need to be identified when identifying dust areas. This embodiment uses local gradient directions to represent the direction of dust movement. If the gradient direction points outward from the dust area (i.e., from the dust area to the surrounding background), the point is retained as the outer diffusion contour point. If the gradient direction points inward into a binary region, such as the edges of folds or cavities within the dust, the point can be discarded.

[0032] It should be noted that in practice, the gradient of a single image can only represent edges and not the direction of motion. However, in this embodiment, the color of the dust and the background color are known in advance, and most dust edges will inevitably show a diffusion trend. Therefore, the gradient can be used to approximate the direction of the dust by pre-labeling its magnitude (positive or negative). The purpose of this embodiment is only to filter out the edges of dust diffusing outwards, while ignoring cavities inside the dust or the adjacent boundaries of two dust clumps (two dust clumps will inevitably converge into the same dust clump, and the outer layer progression method in this embodiment can ignore such boundaries). Therefore, this embodiment can use the gradient to represent the direction. It is conceivable that in practice, any existing method such as multi-frame comparison and centroid displacement can also be used to determine the outline of dust diffusion.

[0033] Furthermore, while the progressive dust suppression method of this invention can effectively control dust diffusion, the intensity of the dust suppression spray is relatively low due to the need to control dust caking and contamination, resulting in low dust suppression efficiency. However, once dust diffusion is suppressed, the existence of a no-spray zone ensures that spraying will not contaminate the equipment materials, eliminating concerns about dust caking. Therefore, increasing the spray intensity at this point can improve dust suppression efficiency. Thus, this invention also provides an embodiment, please refer to [further details needed]. Figure 1 The precise targeted spray intelligent dust suppression method based on dust source identification in this embodiment also includes: S104. Obtain the dust area corresponding to multiple adjacent outer layer dust suppression sprays, and determine whether dust diffusion is suppressed based on the changes in the dust area corresponding to multiple adjacent outer layer dust suppression sprays. S105. If it is determined that dust diffusion is suppressed, the spray dust suppression equipment is controlled to perform rapid spray dust suppression on the dust area corresponding to the last outer layer of spray dust suppression, wherein the spray intensity of rapid spray dust suppression is higher than that of outer layer spray dust suppression.

[0034] More specifically, in one embodiment, step S105 above, controlling the spray dust suppression device to rapidly spray dust suppression onto the dust area corresponding to the last outer layer of spray dust suppression, specifically includes: Based on the dust area corresponding to the last outer layer dust suppression spray, the dust location and dust load parameters are obtained; The dust suppressant ratio is obtained based on the dust load parameters; Based on the dust suppressant ratio and dust location, the spray dust suppression equipment is controlled to quickly spray dust suppression on the dust area corresponding to the last outer layer of dust suppression.

[0035] In this embodiment, rapid spray dust suppression refers to a spraying method with higher dust suppression efficiency than the outer layer spray dust suppression described above. In practice, this can be distinguished by controlling parameters such as the spray position, spray volume, angle, and pressure of the mist cannon. Specifically, the rapid spray dust suppression process can be a comprehensive dust suppression system that deeply integrates functions such as automatic dosing, remote control, AI visual intelligent recognition, and multi-angle precise spraying by a gimbal. The system uses AI visual recognition technology to capture dust center and dust load parameters such as concentration and transmittance in real time. Through AI-related path planning and automatic obstacle avoidance technology, the dust suppression equipment equipped with mist cannons can be transported to a designated location by a vehicle. By automatically triggering the intelligent spray module in the spray dust suppression equipment, combined with multi-angle control of the gimbal and multi-axis linkage of the robotic arm, precise and dynamic coverage of the dust source can be achieved. At the same time, the automatic dosing module can intelligently adjust the dust suppressant ratio according to the dust load, ensuring dust suppression efficiency under complex working conditions; the remote control function supports centralized scheduling of multiple devices in the central control room, greatly improving the emergency response speed. It is understood that the aforementioned rapid spray dust suppression is not the progressive dust suppression logic of this invention, and therefore can be implemented using any existing method, as long as the dust suppression efficiency is fast, without considering environmental impact. Therefore, this embodiment will not elaborate further.

[0036] The key issue is how to determine whether dust dispersion has been suppressed. Therefore, combining... Figure 4 The present invention also provides a preferred embodiment, wherein step S104, obtaining the dust area corresponding to adjacent multiple outer layer dust suppression sprays, and determining whether dust diffusion is suppressed based on the changes in the dust area corresponding to adjacent multiple outer layer dust suppression sprays, specifically includes: S401. Obtain the dust area and spray parameters corresponding to the current outer layer dust suppression spray and the previous outer layer dust suppression spray; S402. Based on the changes in the dust area corresponding to the two outer layer dust suppressions, the theoretical dust suppression effect that can be achieved by the spray parameters is verified to obtain the suppression effect coefficient corresponding to this outer layer dust suppression. S403. Based on the changes in the suppression effect coefficient corresponding to multiple outer layer dust suppression sprays, determine whether dust diffusion has been suppressed.

[0037] It is conceivable that images used to determine whether dust has been suppressed are captured simultaneously with the spraying process. Influenced by factors such as the water mist affecting light and the delay in dust agglomeration, relying solely on image changes to judge dust suppression is prone to error. Therefore, this invention integrates a dual verification mechanism of image recognition and spray physical parameters. It introduces spray parameters (such as coverage area, concentration, and duration) to calculate the theoretical dust suppression effect, and verifies it by comparing it with actual image changes, generating an objective suppression effect coefficient.

[0038] Specifically, in a preferred embodiment, step S402, based on the change in the dust area corresponding to the two outer layer dust suppression operations, verifies the theoretical dust suppression effect achievable by the spray parameters to obtain the suppression effect coefficient corresponding to the current outer layer dust suppression, specifically includes: Based on the differences in the dust areas corresponding to this outer layer dust suppression, the dust difference areas are obtained; The area change rate is obtained based on the dust difference region; Based on the spray parameters corresponding to this outer layer dust suppression, calculate the theoretical dust suppression rate and spray coverage area; Based on the differences in theoretical dust suppression rate and area change rate, and the crossover ratio of the spray coverage area and the dust difference area, the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained.

[0039] In this embodiment, the dust difference area refers to the image difference between the dust areas acquired in two separate acquisitions. The spray coverage area refers to the image area covered by the spray in the real-time captured image. Since a fixed dustfall point mode is adopted, the calculation method for the spray coverage area can be determined by experimental calibration. The theoretical dust suppression rate can be calculated using any existing method. For example, in one embodiment, the theoretical dust suppression rate is calculated using the following formula: in, The theoretical dust suppression rate, Represents the natural constant. The coefficients are preset empirical coefficients obtained through experimental calibration, and all other parameters in the formula are spray parameters: For spray flow rate, This represents an estimated dust concentration (calculated based on the grayscale values ​​of the dust image). This refers to the spray's effective time. denoted as droplet diameter.

[0040] The difference between the theoretical dust suppression rate and the area change rate is mainly used to quantify the deviation between the expected effect of spray dust suppression and the actual feedback. Its function is to accurately eliminate visual illusions caused by environmental interferences such as water mist reflection, light refraction, and delayed dust agglomeration. The intersection-geometry ratio of the spray coverage area and the dust difference area is used to measure the spatiotemporal matching degree between the spray action and the actual dust dissipation location. Its function is to verify whether the spray truly hit the target area, and its advantage is that it can identify invalid operations such as spray misses or spray deviations. The suppression effect coefficient can be calculated arbitrarily by weighted summation based on the above parameters.

[0041] Furthermore, in one of the preceding embodiments, the spray trajectory is obtained based on the diffusion outline point set obtained from the dust region. Building upon this, the present invention also provides a more preferred embodiment, wherein the steps of obtaining the dust suppression effect coefficient corresponding to the current outer layer spray based on the difference between the theoretical dust suppression rate and the area change rate, and the intersection-exchange ratio of the spray coverage area and the dust difference area, specifically include: Obtain the diffusion outer contour point set of the dust region corresponding to the two outer layer dust suppression sprays and the centroid of the dust region; Based on the centroid inside the dust region, the positional relationship of the diffusion outer contour point set of the dust region corresponding to the two outer spray dust suppressions is determined, and the edge shrinkage coefficient is obtained based on the positional relationship. Based on the differences in theoretical dust suppression rate and area change rate, the crossover ratio between the spray coverage area and the dust difference area, and the edge retreat coefficient, the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained.

[0042] This embodiment further introduces an edge retreat coefficient to determine whether dust is suppressed. Specifically, as mentioned earlier, the outer contour of dust diffusion has been captured using a set of diffusion contour points. In this embodiment, due to the progressive dust suppression strategy of this invention, it is only necessary to determine whether the diffusion contour is suppressed when determining whether dust is suppressed. Furthermore, the diffusion contour point set itself represents the diffusion properties of the dust. This embodiment reuses this data, naturally improving the accuracy of the suppression effect judgment. Essentially, this embodiment compares the positional changes of the diffusion contour points during two dust suppression sprays, combining the centroid of the dust region (judging whether dust shrinkage occurs by whether the later diffusion contour point is located inside the previous diffusion contour point), and quantifies this using an edge retreat coefficient. For example, the edge retreat coefficient can be the sum of the distances between the previous and subsequent diffusion contour points and their corresponding centroids, or it can be the number of subsequent diffusion contour points located inside the previous diffusion contour point.

[0043] Combination Figure 5As shown, the present invention also provides a precise targeted spray intelligent dust suppression system based on dust source identification, including a spray dust suppression device 510 and a control module 520, the control module 520 including: Image acquisition module 521 is used to acquire cleanroom scene images and real-time captured images taken at fixed dust collection points, and to obtain the dust area based on the difference between the cleanroom scene images and the real-time captured images. The dust analysis module 522 is used to obtain the spray trajectory based on the dust area and the preset no-spray area in the dust-free scene image. The spray trajectory is only used for the outer contour of the dust area. The spray control module 523 is used to control the spray dust suppression equipment to perform an outer layer of spray dust suppression at a fixed dust suppression point based on spray trajectory control; The control module is used to repeatedly acquire cleanroom scene images and real-time images captured at fixed dust suppression points through the image acquisition module, dust suppression analysis module, and spray control module. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained. Based on the dust area and the preset no-spray area in the cleanroom scene image, the spray trajectory is obtained. Based on the spray trajectory control, the spray dust suppression equipment is controlled to perform one outer layer spray dust suppression at the fixed dust suppression point.

[0044] The control module 520 provided in the above embodiments is a computer program product that can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can be found in the corresponding content in the above method embodiments, and will not be repeated here.

[0045] Combination Figure 6 As shown, the aforementioned dust suppression spray device 510 includes a mounting platform 511, a spray duct 512, a first camera 513, and a second camera 514. The mounting platform consists of a control box and a platform mounted on the control box. The control box integrates relevant control hardware and a dosing module, and can be directly mounted on automated vehicles or other equipment in cement plants. The spray duct is connected to the mounting platform and is used to adjust the spray angle under the control of the platform. The first camera is connected to the spray duct and moves with it. The shooting angle of the first camera is consistent with the spray angle of the spray duct, and it is used to collect real-time images based on fixed dust suppression points in this invention. The second camera is connected to the control box of the mounting platform and acts as a weather station to perform comprehensive image recognition tasks, such as automatic navigation and visual secondary verification.

[0046] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0047] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A precise targeted spray intelligent dust suppression method based on dust source identification, characterized in that, include: Obtain cleanroom scene images and real-time images captured at fixed dust collection points. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained. Based on the dusty area and the pre-defined no-spray area in the cleanroom scene image, the spray trajectory is obtained. The spray trajectory is only used for the outer contour of the dusty area. Based on spray trajectory control, the spray dust suppression equipment is controlled to perform an outer layer of spray dust suppression at a fixed dust suppression point; The process involves repeatedly acquiring cleanroom scene images and real-time images captured at fixed dust suppression points, obtaining the dust area based on the difference between the cleanroom scene images and the real-time images, obtaining the spray trajectory based on the dust area and the preset no-spray area in the cleanroom scene images, and controlling the spray dust suppression equipment to perform one outer layer spray dust suppression at the fixed dust suppression point based on the spray trajectory control.

2. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 1, characterized in that, Acquire cleanroom scene images and real-time images captured at fixed dust collection points. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained, including: Acquire cleanroom scene images and real-time images captured at fixed dust collection points, and perform differential analysis on the cleanroom scene images and real-time images to obtain differential images; The region mask is obtained by filtering the difference image based on an adaptive threshold; Calculate the optical flow vector field of the region mask, and filter the region mask according to the optical flow vector field to obtain the dust mask; Based on the local contrast of the dust mask, the transmittance of the dust mask is verified to obtain the dust area.

3. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 2, characterized in that, Calculate the optical flow vector field of the region mask, and filter the region masks based on the optical flow vector field to obtain the dust mask, including: Divide the region mask into multiple connected domains; Select multiple key points in the connected domain and calculate the optical flow vector for each key point; Based on the consistency of multiple optical flow vectors in each connected region, multiple connected regions are filtered to obtain a dust mask.

4. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 1, characterized in that, Based on the dusty area and the pre-defined no-spray zone in the cleanroom scene image, the spray trajectory is obtained, including: Based on the dust region, the set of boundary points is obtained; Calculate the local gradient direction for each boundary point in the boundary point set; By filtering out boundary points whose local gradient direction points to the centroid of the dust region, the diffusion outer contour point set is obtained. The spray trajectory is obtained based on the diffusion outer contour point set and the preset no-spray area in the cleanroom scene image.

5. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 1, characterized in that, Also includes: Obtain the dust area corresponding to multiple adjacent outer layer dust suppression sprays, and determine whether dust diffusion is suppressed based on the changes in the dust area corresponding to multiple adjacent outer layer dust suppression sprays. If it is determined that dust diffusion is suppressed, the spray dust suppression equipment is controlled to perform rapid spray dust suppression on the dust area corresponding to the last outer layer of spray dust suppression. The spray intensity of the rapid spray dust suppression is higher than that of the outer layer of spray dust suppression.

6. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 5, characterized in that, Obtain the dust areas corresponding to multiple adjacent outer layer dust suppression sprays, and determine whether dust diffusion is suppressed based on the changes in the dust areas corresponding to multiple adjacent outer layer dust suppression sprays, including: Obtain the dust area and spray parameters corresponding to the current outer layer dust suppression spray and the previous outer layer dust suppression spray; Based on the changes in the dust area corresponding to the two outer spray dust suppressions, the theoretical dust suppression effect that can be achieved based on the spray parameters is verified, and the suppression effect coefficient corresponding to this outer spray dust suppression is obtained. The change in the suppression effect coefficient corresponding to multiple outer layer dust suppression sprays is used to determine whether dust diffusion has been suppressed.

7. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 6, characterized in that, Based on the changes in the dust area corresponding to the two outer layer dust suppression operations, the theoretical dust suppression effect achievable by the spray parameters was verified to obtain the suppression effect coefficient corresponding to this outer layer dust suppression, including: Based on the differences in the dust areas corresponding to this outer layer dust suppression, the dust difference areas are obtained; The area change rate is obtained based on the dust difference region; Based on the spray parameters corresponding to this outer layer dust suppression, calculate the theoretical dust suppression rate and spray coverage area; Based on the differences in theoretical dust suppression rate and area change rate, and the crossover ratio of the spray coverage area and the dust difference area, the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained.

8. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 7, characterized in that, The spray trajectory is obtained based on the diffusion contour point set derived from the dust region; the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained based on the differences in theoretical dust suppression rate and area change rate, and the intersection-exchange ratio of the spray coverage area and the dust difference area, including: Obtain the diffusion outer contour point set of the dust region corresponding to the two outer layer dust suppression sprays and the centroid of the dust region; Based on the centroid inside the dust region, the positional relationship of the diffusion outer contour point set of the dust region corresponding to the two outer spray dust suppressions is determined, and the edge shrinkage coefficient is obtained based on the positional relationship. Based on the differences in theoretical dust suppression rate and area change rate, the crossover ratio between the spray coverage area and the dust difference area, and the edge retreat coefficient, the suppression effect coefficient corresponding to this outer layer spray dust suppression is obtained.

9. The precise targeted spray intelligent dust suppression method based on dust source identification according to claim 5, characterized in that, Controlling the spray dust suppression equipment to rapidly spray dust into the dust area corresponding to the last outer layer of dust suppression, including: Based on the dust area corresponding to the last outer layer dust suppression spray, the dust location and dust load parameters are obtained; The dust suppressant ratio is obtained based on the dust load parameters; Based on the dust suppressant ratio and dust location, the spray dust suppression equipment is controlled to quickly spray dust suppression on the dust area corresponding to the last outer layer of dust suppression.

10. A precise targeted spray intelligent dust suppression system based on dust source identification, characterized in that, This includes a dust suppression spray system and a control module. The control module includes: The image acquisition module is used to acquire cleanroom scene images and real-time images taken at fixed dust collection points. The dust area is obtained based on the difference between the cleanroom scene images and the real-time images. The dust analysis module is used to obtain the spray trajectory based on the dust area and the preset no-spray area in the dust-free scene image. The spray trajectory is only used for the outer contour of the dust area. The spray control module is used to control the spray dust suppression equipment to perform an outer layer of spray dust suppression at a fixed dust suppression point based on spray trajectory control; The control module is used to repeatedly acquire cleanroom scene images and real-time images captured at fixed dust suppression points through the image acquisition module, dust suppression analysis module, and spray control module. Based on the difference between the cleanroom scene images and the real-time images, the dust area is obtained. Based on the dust area and the preset no-spray area in the cleanroom scene image, the spray trajectory is obtained. Based on the spray trajectory control, the spray dust suppression equipment is controlled to perform one outer layer spray dust suppression at the fixed dust suppression point.

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