Estimation method, device and equipment for bulk cargo loading and unloading dust release amount in port environment and medium

Abstract

The invention relates to a method, a device and equipment for estimating the bulk cargo loading and unloading dust release amount of a port environment and a medium, and the method comprises the steps: dividing the port environment through employing a hexahedral grid with a non-uniform volume according to the distance of a bulk cargo loading and unloading interval and a bulk cargo particle value; determining wind erosion information of each hexahedral mesh under single disturbance according to historical wind power information through estimation of a dynamic wind erosion release factor, and determining static wind erosion dust capacity of each hexahedral mesh under single disturbance according to the bulk cargo particle value and the wind erosion information of the bulk cargo; determining a dust loading and unloading coefficient according to the dust release amount and the loading and unloading mode of the bulk cargo particle value during dynamic operation through an attention mechanism; according to the dust release amount, the bulk cargo dust loading and unloading coefficient and the static wind erosion dust amount of each hexahedral mesh under single disturbance, the dynamic dust emission amount is determined; and determining an estimation result of the bulk cargo loading and unloading dust release amount according to the static wind erosion dust amount, the dynamic dust emission amount and the duration of the bulk cargo in the single loading and unloading process.

Description

Technical Field

[0001] The present disclosure relates to the technical field of environmental governance, and particularly to a method, device, equipment and medium for estimating the dust release amount during the bulk cargo handling in a port environment. Background Art

[0002] In a port environment, bulk cargo handling operations are an important part of port operations, involving various types of bulk cargo such as coal, ore, and grain. However, a large amount of dust is often generated during the handling of bulk cargo, and the generated dust not only affects the health of port workers but may also cause long-term adverse effects on the surrounding environment and ecosystem. Therefore, accurately estimating the dust release amount during the bulk cargo handling in a port is of great significance for formulating effective dust control measures, protecting the environment, and ensuring the health of workers.

[0003] In related scenarios, the dust release amount estimation methods often rely on empirical formulas or simple statistical models, which have significant limitations in terms of estimation accuracy and applicability. For example, the specific conditions of the port environment (such as wind speed, wind direction, humidity, etc.) affecting the dust release amount may be ignored, resulting in a large deviation between the estimation result and the actual situation. In addition, it is difficult to consider the contributions of various dynamic factors (such as the use of different handling equipment and changes in the operation mode) during the bulk cargo handling operation to the dust release amount. Summary of the Invention

[0004] The object of the present invention is to provide a method, device, equipment and medium for estimating the dust release amount during the bulk cargo handling in a port environment, aiming to accurately estimate the dust release amount during the bulk cargo handling in a port environment.

[0005] To achieve the above object, in the first aspect of the embodiments of the present disclosure, a method for estimating the dust release amount during the bulk cargo handling in a port environment is provided, including:

[0006] Dividing the port environment by using a hexahedron grid with non-uniform volume according to the first distance between the bulk cargo handling areas in the port environment and the bulk cargo particle values of handling bulk cargo in each of the bulk cargo handling areas, wherein the volume of the hexahedron grid is positively correlated with the second distance to the bulk cargo handling area;

[0007] Determining the wind erosion information of each hexahedron grid under a single disturbance according to the historical wind information of the port environment and the dynamic wind erosion release factor, and determining the static wind erosion dust amount of each hexahedron grid under a single disturbance according to the bulk cargo particle values of handling bulk cargo in each of the bulk cargo handling areas and the wind erosion information;

[0008] Through an attention mechanism, determine the dust loading and unloading coefficient of the bulk cargo during dynamic operation according to the dust release amount of the bulk cargo particles of the bulk cargo during dynamic operation and the loading and unloading method for the bulk cargo.

[0009] Determine the dynamic dust generation amount of each hexahedral grid according to the dust release amount of the bulk cargo particles of the bulk cargo during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under each single disturbance.

[0010] Determine the estimated result of the dust release amount during bulk cargo loading and unloading according to the static wind erosion dust amount, the dynamic dust generation amount of each hexahedral grid, and the duration of the bulk cargo during a single loading and unloading process.

[0011] In a second aspect of the embodiments of the present disclosure, there is provided an apparatus for estimating the dust release amount during bulk cargo loading and unloading in a port environment, the apparatus including:

[0012] A division module, configured to divide the port environment by using hexahedral grids with non-uniform volumes according to the first distance between the bulk cargo loading and unloading areas in the port environment and the bulk cargo particle values of the bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas, wherein the volume of the hexahedral grid is positively correlated with the second distance to the bulk cargo loading and unloading area;

[0013] A first determination module, configured to determine the wind erosion information of each hexahedral grid under a single disturbance according to the historical wind force information of the port environment and the dynamic wind erosion release factor, and determine the static wind erosion dust amount of each hexahedral grid under a single disturbance according to the bulk cargo particle values of the bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas and the wind erosion information;

[0014] A second determination module, configured to determine the dust loading and unloading coefficient of the bulk cargo during dynamic operation and loading and unloading through an attention mechanism according to the dust release amount of the bulk cargo particles of the bulk cargo during dynamic operation and the loading and unloading method for the bulk cargo;

[0015] A third determination module, configured to determine the dynamic dust generation amount of each hexahedral grid according to the dust release amount of the bulk cargo particles of the bulk cargo during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under a single disturbance;

[0016] A fourth determination module, configured to determine the estimated result of the dust release amount during bulk cargo loading and unloading according to the static wind erosion dust amount, the dynamic dust generation amount of each hexahedral grid, and the duration of the bulk cargo during a single loading and unloading process.

[0017] In a third aspect of the embodiments of the present disclosure, there is provided a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the steps of the method described in any one of the first aspects are implemented.

[0018] In a fourth aspect of the embodiments of the present disclosure, there is provided an electronic device, including:

[0019] A memory having a computer program stored thereon;

[0020] A processor for executing the computer program in the memory to implement the steps of the method described in any one of the first aspects.

[0021] The present invention provides a method, device, equipment and medium for estimating the dust release amount during the bulk cargo loading and unloading in a port environment. Compared with the prior art, the following beneficial effects are achieved:

[0022] The port environment is divided using hexahedral grids with non-uniform volumes, and the grid volume is positively correlated with the distance to the bulk cargo loading and unloading area. This division method can more accurately reflect the non-uniformity of dust distribution in the port environment. Especially in the area near the loading and unloading area, the dust concentration is often higher, so the grid division in these areas is more detailed, which helps to improve the estimation accuracy.

[0023] Further, by combining the historical wind information in the port environment and estimating the dynamic wind erosion release factor, the wind erosion information of each hexahedral grid under a single disturbance is determined. Further, based on the bulk cargo particle value and the wind erosion information, the static wind erosion dust amount is calculated. This step considers the direct influence of wind on dust release, making the assessment of dust amount more dynamic and accurate.

[0024] Further, using the attention mechanism, according to the dust release amount and the loading and unloading method during the dynamic operation of the bulk cargo particle value, the dust loading and unloading coefficient of the bulk cargo during the dynamic operation loading and unloading is intelligently determined. This step considers the comprehensive influence of the physical properties of the bulk cargo and the loading and unloading operation on dust release, and improves the intelligent level of determining the dust coefficient.

[0025] Further, by combining the static wind erosion dust amount, the dynamic operation dust coefficient, and the static wind erosion dust amount of each hexahedral grid under a single disturbance, the dynamic dust generation amount of each grid is comprehensively estimated. This step combines static and dynamic factors, and more comprehensively reflects the impact of bulk cargo loading and unloading activities on dust pollution in the port environment.

[0026] Further, based on the static wind erosion dust amount, the dynamic dust generation amount, and the continuous duration of the bulk cargo during a single loading and unloading process, the estimation result of the dust release amount during the bulk cargo loading and unloading is finally determined. This result not only considers the instantaneous situation of dust release, but also considers the time factor, providing comprehensive and accurate data support for the prevention and control of dust pollution in the port environment.

[0027] In summary, through refined environmental division, dynamic assessment of wind erosion dust volume, intelligent determination of dust coefficients, comprehensive estimation of dust generation volume, and comprehensive estimation of dust release volume, high-precision estimation of the dust release volume generated by bulk cargo handling activities in the port environment is achieved, providing strong technical support for the prevention and control of dust pollution in the port environment.

[0028] Other features and advantages of the present disclosure will be described in detail in the following specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific implementation, they are used to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings:

[0030] Figure 1 is a flowchart of a method for estimating the dust release volume of bulk cargo handling in a port environment shown according to an embodiment of the specification.

[0031] Figure 2 is a block diagram of an apparatus for estimating the dust release volume of bulk cargo handling in a port environment shown according to an embodiment of the specification.

[0032] Figure 3 is a block diagram of another apparatus for estimating the dust release volume of bulk cargo handling in a port environment shown according to an embodiment of the specification. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0034] The following provides a detailed description of the specific implementation of the present disclosure with reference to the drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0035] The present disclosure provides a method for estimating the dust release volume of bulk cargo handling in a port environment, which can be applied to a port environment monitoring device, aiming to achieve high-precision estimation of the dust release volume generated by bulk cargo handling activities in the port environment. Figure 1 is a flowchart of a method for estimating the dust release volume of bulk cargo handling in a port environment shown according to an embodiment. The method includes:

[0036] In step S11, according to the first distance between the bulk cargo loading and unloading areas in the port environment and the bulk cargo particle values of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area, the port environment is divided using hexahedral meshes with non-uniform volumes, where the volume of the hexahedral mesh is positively correlated with the second distance to the bulk cargo loading and unloading area;

[0037] Among them, the hexahedral mesh with non-uniform volume divides the port environment into regular hexahedral meshes with different volumes, where the volume of each tetrahedron is inconsistent to adapt to the different distances between different spaces in the port environment and the bulk cargo loading and unloading areas and the different influences of dust. The bulk cargo loading and unloading area is the area in the port for loading and unloading bulk cargo (such as coal, ore, etc.).

[0038] In the embodiment of the present disclosure, the division of the hexahedral mesh with non-uniform volume aims to more accurately simulate the port environment, especially the wind erosion dust diffusion near the bulk cargo loading and unloading area. The volume size of the mesh is adjusted according to the distance to the bulk cargo loading and unloading area. The closer the distance, the smaller the mesh volume, so as to more finely capture the details of dust diffusion; the farther the distance, the gradually increasing mesh volume to reduce the computational amount.

[0039] For example: Suppose there are two bulk cargo loading and unloading areas A and B in the port, which are at a certain distance from each other. Near area A, hexahedral meshes with smaller volumes are used for division to accurately simulate the dust diffusion generated during the loading and unloading of bulk cargo in area A; while in the area far from areas A and B, hexahedral meshes with larger volumes are used to reduce the computational amount.

[0040] In step S12, according to the historical wind force information of the port environment and the dynamic wind erosion release factor, the wind erosion information of each hexahedral mesh under a single perturbation is determined, and according to the bulk cargo particle values of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and the wind erosion information, the static wind erosion dust amount of each hexahedral mesh under a single perturbation is determined;

[0041] Among them, the dynamic wind erosion release factor, as a quantitative index, is used to estimate the rate at which bulk cargo particles are released into the air under the action of wind force. The historical wind force information is the wind force data such as wind speed and wind direction in the port area in the past time. A single perturbation refers to a specific bulk cargo loading and unloading operation or wind force event. The wind erosion information is the information used to describe the degree or rate of the bulk cargo particles in the hexahedral mesh being affected by wind erosion. The static wind erosion dust amount is used to represent the total amount of bulk cargo particles released into the air by wind erosion under a single perturbation.

[0042] In the embodiments of the present disclosure, based on historical wind force information and in combination with a kinetic model, the rate at which bulk cargo particles are eroded and released by the wind under different wind force conditions is estimated. This step is the basis for predicting the amount of dust diffusion near the bulk cargo loading and unloading area. For example: Suppose the historical wind force information in the port area shows that the dominant wind direction is north and the wind speed is moderate during a certain period. According to this information and in combination with the kinetic wind erosion release factor model, the rate at which particles are eroded and released into the air by the north wind during the loading and unloading of bulk cargo in Area A of the bulk cargo loading and unloading area can be estimated during this period.

[0043] Furthermore, based on the estimation results of the kinetic wind erosion release factor and in combination with the specific location of the bulk cargo loading and unloading area and the particle values of the bulk cargo being loaded and unloaded, the wind erosion information of each hexahedral grid under a single disturbance is determined. This step is the key to combining the wind force influence with the characteristics of bulk cargo particles. For example: Suppose a bulk cargo loading and unloading operation is carried out in Area A, and at the same time, the port area is disturbed by a north wind. According to the estimation results in Step 2 and the bulk cargo particle values in Area A, the wind erosion information of each hexahedral grid under this north wind disturbance can be determined, including the particle release rate, etc.

[0044] Furthermore, in combination with the bulk cargo particle values and wind erosion information of each bulk cargo loading and unloading area, by methods such as integration or accumulation, the static wind erosion dust amount of each hexahedral grid under a single disturbance is calculated. This step is an important basis for evaluating the degree of dust pollution in the port environment. For example: Suppose when loading and unloading bulk cargo in Area A, the wind erosion information of each hexahedral grid is determined through Step 3. In combination with the bulk cargo particle values in Area A, the total static wind erosion dust amount in Area A during a single loading and unloading operation can be obtained by accumulating the dust release amounts of each grid. This total amount can be used to evaluate the contribution degree of Area A to the dust pollution in the port environment.

[0045] In step S13, through the attention mechanism, based on the dust release amount of the bulk cargo particles during dynamic operation and the loading and unloading method for the bulk cargo, the dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading is determined;

[0046] Among them, the dust loading and unloading coefficient, as a quantitative index, is used to describe the ease or rate of dust release during the dynamic loading and unloading of bulk cargo.

[0047] In the embodiments of the present disclosure, using the attention mechanism, in combination with the dust release amount of the bulk cargo particles (such as particle size, shape, density, etc.) during dynamic operation and the loading and unloading method for the bulk cargo (such as shovel loading, dumping, etc.), the dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading is determined. This step takes into account the physical characteristics of the bulk cargo and the influence of the loading and unloading operation on dust release, providing a basis for subsequent estimation of the dynamic dust generation amount.

[0048] For example: Suppose a certain bulk cargo has relatively large particles and a high density, and the dust emission during the loading process is relatively small. Using the attention mechanism, the physical properties of this bulk cargo and its dust emission pattern during the loading operation can be identified, thereby determining that its dust loading and unloading coefficient is relatively low. On the contrary, if the bulk cargo particles are fine and the density is low, and the dust emission during the dumping process is large, then its dust loading and unloading coefficient will be high.

[0049] In step S14, according to the dust emission amount of the bulk cargo particles during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under a single disturbance, determine the dynamic dust generation amount of each hexahedral grid;

[0050] Among them, the dynamic dust generation amount is used to estimate the dust emission amount directly caused by the bulk cargo loading and unloading activities during the dynamic operation process.

[0051] In the embodiment of the present disclosure, according to the dust emission amount (already determined) of the bulk cargo particles during dynamic operation, the bulk cargo dust loading and unloading coefficient (determined in step five) during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under a single disturbance (determined in step three), through comprehensive calculation, determine the dynamic dust generation amount of each hexahedral grid. This step combines the static wind erosion dust amount with the dust amount generated by dynamic operation, and more comprehensively evaluates the dust pollution situation in the port environment.

[0052] For example: Suppose during the bulk cargo loading and unloading operation in area A, the dust loading and unloading coefficient of the bulk cargo is determined according to step five. At the same time, the static wind erosion dust amount of each hexahedral grid under a single disturbance is determined according to step three. Combining the dust emission amount of the bulk cargo during dynamic operation, the dynamic dust generation amount of each hexahedral grid during the loading and unloading operation in area A can be calculated. This helps to identify which areas have the most serious dust pollution.

[0053] In step S15, according to the static wind erosion dust amount, the dynamic dust generation amount, and the continuous duration of the bulk cargo during a single loading and unloading process, determine the estimated result of the bulk cargo loading and unloading dust emission amount.

[0054] Among them, the estimated result of the bulk cargo loading and unloading dust emission amount is the overall assessment of the dust pollution of the port environment caused by the bulk cargo loading and unloading activities after comprehensively considering the static wind erosion dust amount, the dynamic dust generation amount, and the continuous duration of the bulk cargo during a single loading and unloading process.

[0055] In the embodiment of the present disclosure, according to the static wind erosion dust amount, the dynamic dust generation amount, and the continuous duration of the bulk cargo during a single loading and unloading process (such as the time length of the loading and unloading operation), through methods such as integration or accumulation, determine the estimated result of the bulk cargo loading and unloading dust emission amount. Introducing the time factor into the assessment of the dust emission amount makes the estimated result closer to the actual situation.

[0056] For example: Suppose a bulk cargo loading and unloading operation lasting for T hours is carried out in Area A. According to Steps 3 and 6, the static wind erosion dust amount and dynamic dust generation amount of each hexahedron grid are determined respectively. Combining the operation duration T, the overall estimated result of the bulk cargo loading and unloading dust release amount in Area A can be obtained by accumulating the dust release amounts (including static and dynamic parts) of each grid within T hours. This is used to evaluate the impact degree of the bulk cargo loading and unloading activities in Area A on the port environmental dust pollution and provide data support for subsequent environmental protection measures.

[0057] The above technical solution divides the port environment using hexahedron grids with non-uniform volumes, and the grid volume is positively correlated with the distance to the bulk cargo loading and unloading area. This division method can more accurately reflect the non-uniformity of dust distribution in the port environment. Especially in the areas close to the loading and unloading area, the dust concentration is often higher. Therefore, the grid division in these areas is more detailed, which helps to improve the estimation accuracy.

[0058] Furthermore, by combining the historical wind force information in the port environment and estimating the dynamic wind erosion release factor, the wind erosion information of each hexahedron grid under a single disturbance is determined. Further, based on the bulk cargo particle value and the wind erosion information, the static wind erosion dust amount is calculated. This step takes into account the direct impact of wind force on dust release, making the evaluation of dust amount more dynamic and accurate.

[0059] Furthermore, using the attention mechanism, according to the dust release amount and loading and unloading method of bulk cargo during dynamic operation, the dust loading and unloading coefficient of bulk cargo during dynamic operation is intelligently determined. This step takes into account the comprehensive influence of the physical properties of bulk cargo and loading and unloading operations on dust release, and improves the intelligent level of determining the dust coefficient.

[0060] Furthermore, by combining the static wind erosion dust amount, the dynamic operation dust coefficient, and the static wind erosion dust amount of each hexahedron grid under a single disturbance, the dynamic dust generation amount of each grid is comprehensively estimated. This step combines static and dynamic factors, more comprehensively reflecting the impact of bulk cargo loading and unloading activities on port environmental dust pollution.

[0061] Furthermore, according to the static wind erosion dust amount, the dynamic dust generation amount, and the continuous duration of bulk cargo during a single loading and unloading process, the estimated result of the bulk cargo loading and unloading dust release amount is finally determined. This result not only considers the instantaneous situation of dust release but also takes into account the time factor, providing comprehensive and accurate data support for the prevention and control of port environmental dust pollution.

[0062] In summary, through refined environmental division, dynamic assessment of wind erosion dust volume, intelligent determination of dust coefficients, comprehensive estimation of dust generation amount, and comprehensive estimation of dust release amount, a high-precision estimation of the dust release amount generated by bulk cargo handling activities in the port environment is achieved, providing strong technical support for the prevention and control of dust pollution in the port environment.

[0063] In a possible implementation manner, in step S11, according to the first distance between the bulk cargo handling areas in the port environment and the bulk cargo particle values of the bulk cargo handled in each bulk cargo handling area, the port environment is divided using a hexahedral grid with non-uniform volume, including:

[0064] In step S111, according to the first distance between the bulk cargo handling areas in the port environment, the space where the port environment is located is evenly divided into hexahedral grids to obtain initial hexahedral grids;

[0065] Among them, uniform division is to divide the entire area into grid units with the same size and shape in the space where the port environment is located. The initial hexahedral grid is the basic grid unit obtained after uniform division and is used for subsequent adjustment.

[0066] In the embodiments of the present disclosure, according to the distribution of the bulk cargo handling areas in the port environment and the first distance between them, the three-dimensional space where the entire port environment is located is evenly divided into a series of hexahedral grids. These grids have the same size and shape and serve as the basis for subsequent adjustment according to the influence of bulk cargo handling activities. For example: Suppose the port environment is a rectangular area with two bulk cargo handling areas A and B. First, according to the relative positions of areas A and B, the port environment is evenly divided into several hexahedral grids with equal side lengths.

[0067] In step S112, according to the bulk cargo particle values of the bulk cargo handled in each bulk cargo handling area and the third distance from each initial hexahedral grid to the bulk cargo handling area, the influence value of each initial hexahedral grid affected by the bulk cargo handling in multiple bulk cargo handling areas is determined;

[0068] Among them, the influence value is the degree to which the initial hexahedral grid is affected by the bulk cargo handling activities in the bulk cargo handling area and is used to determine whether the grid needs to be adjusted.

[0069] In the embodiments of the present disclosure, considering the particle values of the bulk cargo handled in the bulk cargo handling area and the third distance from each initial hexahedral grid to these handling areas, the influence value of each grid affected by the bulk cargo handling activity is calculated. The magnitude of the influence value reflects the strength of the grid area affected by the bulk cargo handling activity.

[0070] For example: Assume that the bulk cargo particles loaded and unloaded in Area A have a relatively large value, while those in Area B are relatively small. For the grids close to Area A and with a large value of bulk cargo particles in Area A, the influence value of these grids by the loading and unloading activities in Area A will be relatively large; on the contrary, for the grids far from both Area A and Area B or close to Area B but with a small value of bulk cargo particles in Area B, the influence value will be relatively small.

[0071] In step S113, according to the influence value of each initial hexahedron grid by the bulk cargo loaded and unloaded in multiple bulk cargo loading and unloading areas and a plurality of preset influence value thresholds, determine the adjustment strategy for the initial hexahedron grid. The adjustment strategy includes merging with adjacent initial hexahedron grids, or splitting the initial hexahedron grid itself again.

[0072] Among them, the adjustment strategy is an operation method for deciding whether to merge, make no adjustment, or split according to the size of the influence value of the initial hexahedron grid. The influence value threshold is a standard value used to judge the size of the grid influence value and thus determine the adjustment strategy.

[0073] In the embodiments of the present disclosure, according to the size of the influence value of each initial hexahedron grid and a plurality of preset influence value thresholds, determine the adjustment strategy for each grid. If the influence value of the grid exceeds a certain threshold, it indicates that the area is significantly affected by the bulk cargo loading and unloading activities and may require a finer division (splitting); if the influence value is lower than a certain threshold and the influence of the surrounding grids is also similar, merging can be considered to reduce the computational amount.

[0074] For example: Set five influence value thresholds T1 to T5 (T1 > T2 > T3 > T4 > T5). For the initial hexahedron grid with an influence value greater than T1, perform three splitting operations. For example, split longitudinally three times, or split horizontally three times, or split longitudinally twice and horizontally once, or split longitudinally once and horizontally twice, to subdivide it into smaller initial hexahedron grids; for the initial hexahedron grid with an influence value between T1 and T2, perform two splitting operations. For example, split longitudinally twice, or split horizontally twice, or split once longitudinally and once horizontally, to subdivide it into smaller initial hexahedron grids; for the initial hexahedron grid with an influence value between T2 and T3, perform one splitting operation. For example, split longitudinally once, or split horizontally once, to subdivide it into smaller initial hexahedron grids; for the initial hexahedron grid with an influence value between T3 and T4, do not perform splitting or merging and keep the status quo unchanged.

[0075] For the initial hexahedral mesh with the influence value between T4 and T5, if there is no adjacent initial hexahedral mesh with an influence value less than T5 and no initial hexahedral mesh with an influence value between T4 and T5, then the initial hexahedral mesh is not divided or merged and remains unchanged. If there is no adjacent initial hexahedral mesh with an influence value less than T5 and there is one initial hexahedral mesh with an influence value between T4 and T5, then the two initial hexahedral meshes are merged. If there is no adjacent initial hexahedral mesh with an influence value less than T5 and there are multiple initial hexahedral meshes with an influence value between T4 and T5, then any initial hexahedral mesh with an influence value between T4 and T5 is merged with this initial hexahedral mesh; If there are less than two adjacent initial hexahedral meshes with an influence value less than T5, then the two initial hexahedral meshes are merged. If there are multiple initial hexahedral meshes with an influence value between T4 and T5 among the adjacent initial hexahedral meshes, then any two adjacent initial hexahedral meshes are merged with this initial hexahedral mesh.

[0076] For the initial hexahedral mesh with an influence value less than T5, if the influence values of the adjacent initial hexahedral meshes are all greater than T4, then the initial hexahedral mesh is not divided or merged and remains unchanged. If there are more than three adjacent initial hexahedral meshes with an influence value less than T5, then any three adjacent initial hexahedral meshes are merged with this initial hexahedral mesh; If there are two adjacent initial hexahedral meshes with an influence value less than T5 and there is at least one initial hexahedral mesh with an influence value between T4 and T5, then the two initial hexahedral meshes with an influence value less than T5 are merged with this initial hexahedral mesh; If there is one adjacent initial hexahedral mesh with an influence value less than T5 and there is at least one initial hexahedral mesh with an influence value between T4 and T5, then the initial hexahedral mesh with an influence value less than T5 and any initial hexahedral mesh with an influence value between T4 and T5 are merged with this initial hexahedral mesh; If there is no adjacent initial hexahedral mesh with an influence value less than T5 and there is at least one initial hexahedral mesh with an influence value between T4 and T5, then any initial hexahedral mesh with an influence value between T4 and T5 is merged with this initial hexahedral mesh.

[0077] In step S114, according to the adjustment strategy, each initial hexahedral mesh is adjusted to complete the step of dividing the port environment with hexahedral meshes of non-uniform volume.

[0078] Among them, the volume of the meshes in the hexahedral meshes of non-uniform volume is not uniform in space, but is adjusted according to the distribution of the bulk cargo handling area and the bulk cargo particle value to meet the accuracy requirements of simulation or analysis.

[0079] In the embodiments of the present disclosure, each initial hexahedral mesh is adjusted. For the meshes that need to be divided, they are subdivided into smaller hexahedral meshes; for the meshes that need to be merged, they are merged with adjacent meshes into a larger mesh. The adjusted meshes exhibit the characteristic of non-uniform volume in space, better adapting to the influence of bulk cargo handling activities. For example, the meshes with influence values greater than T1 are divided, and they are successively subdivided into smaller mesh units. Finally, the port environment is divided into a series of hexahedral meshes with non-uniform volume, which not only reflect the influence of bulk cargo handling activities but also optimize the calculation efficiency.

[0080] In a possible implementation manner, in step S111, according to the first distance between the bulk cargo handling areas in the port environment, the space where the port environment is located is evenly divided into hexahedral meshes to obtain the initial hexahedral meshes, including:

[0081] In step S1111, determine the first distance between the bulk cargo handling areas in the port environment, and take the minimum first distance between the bulk cargo handling areas as the target distance. According to the first quantity of the bulk cargo handling areas, the target distance is evenly divided into multiple segments with the same numerical value as the first quantity to obtain the value of each segment;

[0082] Among them, the target distance is the minimum first distance between the bulk cargo handling areas, serving as the benchmark for mesh division. The segment is to evenly divide the target distance into parts with the same quantity as the first quantity of the bulk cargo handling areas, used to determine the fineness of mesh division. The segment value is the specific length value of each segment.

[0083] In the embodiments of the present disclosure, measure the first distance between all the bulk cargo handling areas in the port environment, and find the minimum value among them as the target distance. Then, according to the quantity of the bulk cargo handling areas, the target distance is evenly divided into corresponding segments, and each segment represents a basic unit length for mesh division.

[0084] For example: Suppose there are 3 bulk cargo handling areas in the port, and the minimum distance is 100 meters. Then, the target distance is 100 meters. Divide this distance into 3 segments, and the value of each segment is approximately 33.33 meters.

[0085] In step S1112, determine the difference between the first distance between the bulk cargo handling areas and the target distance to obtain multiple first differences, and calculate the differences between the first differences in sequence according to the magnitudes of the first differences to obtain multiple second differences;

[0086] Among them, the first difference is the difference between the actual first distance between the bulk cargo handling areas and the target distance. The second difference is the difference between adjacent first differences, used to evaluate the uniformity of distance distribution.

[0087] In the embodiments of the present disclosure, the difference between the actual distance and the target distance between each bulk cargo handling area is calculated to obtain a plurality of first differences. Then, the difference between these first differences, that is, the second difference, is calculated to evaluate the uniformity of the distances between the bulk cargo handling areas.

[0088] For example: If the distance between bulk cargo handling areas A and B is 105 meters, the difference from the target distance of 100 meters is 5 meters; the distance between B and C is 108 meters, and the difference from the target distance is 8 meters; the distance between A and C is 113 meters, and the difference from the target distance is 13 meters; the distance between bulk cargo handling areas A and D is the target distance of 100 meters; the distance between B and D is 118 meters, and the difference from the target distance is 18 meters; the distance between D and C is 114 meters, and the difference from the target distance is 14 meters. Therefore, the first differences are: 5, 8, 13, 14, and 18 in sequence, and the second differences are: 8 - 5 = 3, 13 - 8 = 5, 14 - 13 = 1, 18 - 14 = 4.

[0089] In step S1113, the first absolute value of the difference between the first average value of the first differences and the second average value of the second differences is calculated, as well as the second absolute value of the difference between the value of each segment and the third average value, where the third average value is the average of the first average value and the second average value;

[0090] In the embodiments of the present disclosure, the average value of all the first differences (the first average value) and the average value of all the second differences (the second average value) are calculated. Then, the absolute value of the difference between these two average values (the first absolute value) and the absolute value of the difference between the value of each segment and the third average value obtained by averaging these two average values (the second absolute value) are calculated. These values are used to evaluate the accuracy and uniformity of the grid division. For example, the first average value is 11.6 and the second average value is 3.25. Then, the absolute value of the difference between these two average values (the first absolute value) is 8.35, and the absolute value of the difference between the value of each segment 25 and the third average value obtained by averaging these two average values (the second absolute value) is 16.65.

[0091] In step S1114, the ratio of the first average value to the second absolute value is determined as the side length of the hexahedron grid for uniformly dividing the space where the port environment is located;

[0092] In the embodiments of the present disclosure, the ratio of the first average value to the second absolute value is used as an index for the fineness of the grid division. The larger this ratio is, the more uniform the distance distribution between the bulk cargo handling areas is, and the finer the grid can be divided. According to this ratio and the preset grid division accuracy requirement, the final side length of the hexahedron grid is determined.

[0093] Continuing with the example from the previous step, the ratio of the first average value of 11.6 to the second absolute value of 16.65 is 0.7. Therefore, the edge length of the hexahedron mesh for the uniform hexahedron mesh division is 0.7 m.

[0094] In step S1115, based on the edge length of the hexahedron mesh, starting from the central position of each bulk cargo loading and unloading area respectively, with the edge length of the hexahedron mesh as the target edge length, the space where the port environment is located is evenly divided into hexahedron meshes in the same way as the start of the step to obtain the initial hexahedron meshes;

[0095] Among them, when the adjacent bulk cargo loading and unloading areas meet during the uniform hexahedron mesh division starting from their respective central positions, if the fourth distance of the remaining undivided space is less than the edge length of the hexahedron mesh, the undivided space will no longer be divided. If the fourth distance of the remaining undivided space is greater than the edge length of the hexahedron mesh and less than 2 times the edge length of the hexahedron mesh, the fourth distance will be bisected to obtain two hexahedron meshes.

[0096] In the embodiments of the present disclosure, starting from the central position of each bulk cargo loading and unloading area, based on the determined edge length of the hexahedron mesh (target edge length), the space where the port environment is located is evenly divided into hexahedron meshes. When the mesh divisions of adjacent bulk cargo loading and unloading areas meet, according to the relationship between the distance of the remaining undivided space (the fourth distance) and the edge length of the mesh, it is determined whether to continue the division or how to divide.

[0097] For example: If two bulk cargo loading and unloading areas A and B meet during the mesh division starting from their respective central positions, and the distance of the remaining undivided space is 0.6 meters (less than the mesh edge length of 0.7 meters), then this space will no longer be divided. If the remaining distance is 0.8 meters (greater than the mesh edge length and less than 2 times the mesh edge length), then this distance will be bisected to obtain two hexahedron meshes with an edge length of 0.4 meters.

[0098] In a possible implementation manner, in step S12, according to the historical wind force information of the port environment and the dynamic wind erosion release factor, the wind erosion information of each hexahedron mesh under a single disturbance is determined, and according to the bulk cargo particle values of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and the wind erosion information, the static wind erosion dust amount of each hexahedron mesh under a single disturbance is determined, including:

[0099] In step S121, according to the wind direction information in the historical wind force information of the port environment and the position information of each bulk cargo loading and unloading area, the distribution of the friction velocity of the port environment is determined;

[0100] Among them, the friction velocity refers to the wind speed above the bulk cargo loading and unloading area, which reflects the interaction intensity between the air flow and the objects in the bulk cargo loading and unloading area (such as buildings, traveling cranes, containers, etc.). The wind direction information of the wind force is the wind force and the wind direction, and the wind force is represented by the wind speed; the wind direction refers to the direction from which the wind blows.

[0101] In the embodiments of the present disclosure, by collecting historical wind force information of the port environment, especially the wind force magnitude and direction, and combining with the geographical location information of the bulk cargo loading and unloading area, and using the wind speed distribution model in meteorology (such as the logarithmic wind speed profile model), the friction velocity at different positions within the port area can be calculated. The friction velocity is an important parameter for evaluating the wind erosion effect, which determines the ability of surface particles to be transported by the wind.

[0102] For example: Suppose the port historical data shows that the average wind speed in a certain area is 10 m / s and the dominant wind direction is north. Combining with the specific coordinates of the bulk cargo loading and unloading area, using the logarithmic wind speed profile model, the friction velocity values at different distances extending from the loading and unloading area to the surrounding can be calculated, forming a friction velocity distribution map.

[0103] In step S122, according to the dynamic wind erosion release factor, the friction velocity distribution, and the central coordinates of each hexahedral grid, determine the wind erosion information of each hexahedral grid under a single perturbation;

[0104] Among them, the dynamic wind erosion release factor is a parameter that quantifies the degree of bulk cargo release by wind erosion at different positions within the port area, which comprehensively considers factors such as soil moisture, particle size, and surface roughness. Combining the friction velocity distribution obtained in step S121 and the known dynamic wind erosion release factor, use the wind erosion model (such as the WEPS model) to calculate the wind erosion degree of each hexahedral grid unit under a single perturbation. This includes determining which grid units are in the active state of wind erosion and their wind erosion potential.

[0105] In step S123, according to the wind erosion information of each hexahedral grid under a single perturbation, divide each hexahedral grid into different perturbation types, where the perturbation type is used to represent the amount of dust corresponding to the hexahedral grid affected by the quantity and influence value of the bulk cargo loaded and unloaded in the bulk cargo loading and unloading area;

[0106] Among them, the perturbation type is to divide the grid into different categories according to the influence degree of the bulk cargo loading and unloading activities on each hexahedral grid, so as to reflect its contribution to the amount of dust.

[0107] In the embodiments of the present disclosure, based on the obtained wind erosion information of each hexahedral grid, combined with the intensity of the bulk cargo loading and unloading activities (such as the quantity and frequency of the bulk cargo loaded and unloaded), divide the grid into different types such as mild perturbation, moderate perturbation, and severe perturbation. This helps to more accurately evaluate the dust generation amount of each grid subsequently.

[0108] For example: Grids close to a large number of bulk cargo handling activities, if they have high wind erosion information and are affected by the bulk cargo handling in multiple bulk cargo handling areas at the same time, may be classified as the heavily disturbed type, which means that these areas may generate a large amount of dust under a single disturbance. Grids far from bulk cargo handling activities, if they do not have high wind erosion information and are affected by the bulk cargo handling in a single bulk cargo handling area, may be classified as the lightly disturbed type, which means that these areas may generate a small amount of dust under a single disturbance.

[0109] In step S124, according to the bulk cargo particle values of the bulk cargo handled in each bulk cargo handling area and the disturbance types corresponding to each hexahedral grid, determine the static wind erosion dust amount of each hexahedral grid under a single disturbance.

[0110] In the embodiments of the present disclosure, in combination with the divided disturbance types and known bulk cargo particle values (representing the proportion or mass of particles in the bulk cargo that can be eroded by the wind), use an empirical formula or model (such as a mass balance model) to calculate the static wind erosion dust amount of each hexahedral grid under a single disturbance. This takes into account the differences in dust generation under different disturbance types. For example: For grids of the heavily disturbed type, if the bulk cargo particle values are high (such as bulk cargo with a lot of fine sand and dust content), the static wind erosion dust amount calculated according to the empirical formula will also be relatively high, indicating that these areas will generate a large amount of suspended dust during a single handling activity.

[0111] In a possible implementation manner, according to the dynamic wind erosion release factor, the distribution of friction velocity, and the central coordinates of each hexahedral grid, determine the wind erosion information of each hexahedral grid under a single disturbance, including:

[0112] E i，j，k =a·μ * (x i，j，k ,y i，j，k ,z i，j，k ) b ;

[0113]

[0114] Wherein, E i，j，k represents the wind erosion information of the (i, j, k) - th hexahedral grid under a single disturbance, μ * represents the friction velocity distribution function, a and b respectively represent the grid release factors in the dynamic wind erosion release factor set according to empirical values, U represents the observed wind speed of the port environment, ρ represents the air density, Z 0 represents the surface roughness length, C D represents the drag function, n represents the number of bulk cargo handling areas in the port environment, k m is the influence coefficient of the bulk cargo handling dust release amount corresponding to the m - th bulk cargo handling area on the (i, j, k) - th hexahedral grid, Hm represents the maximum influence height of the m-th bulk handling area, H ref represents the reference maximum influence height, α m and β m respectively represent the windward release factor of the bulk handling area in the kinetic wind erosion release factor set by empirical values, θ m represents the angle between the wind direction and the m-th bulk handling area, x i，j，k , y i，j，k , z i，j，k are the central coordinates of the (i, j, k)-th hexahedral grid.

[0115] In a possible implementation manner, in step S14, according to the dust release amount of the bulk cargo during dynamic operation, the bulk cargo dust handling coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under a single disturbance, determine the dynamic dust generation amount of each hexahedral grid, including:

[0116] In step S141, calculate the product of the dust release amount of the bulk cargo during dynamic operation, the bulk cargo dust handling coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under a single disturbance, and determine the initial dust generation amount of each hexahedral grid;

[0117] Among them, the dust release amount during dynamic operation refers to the amount of dust generated during the bulk cargo handling operation due to material movement (such as dumping, shoveling, conveying, etc.). The bulk cargo dust handling coefficient during dynamic operation is a coefficient reflecting the dust release characteristics of the bulk cargo during handling, and is related to factors such as the type of bulk cargo, handling method, and operating conditions. The initial dust generation amount is the preliminary estimated dust generation amount of each hexahedral grid after considering the bulk cargo particle value, the dust release amount during dynamic operation, and the static wind erosion dust amount.

[0118] In the embodiments of the present disclosure, by multiplying the dust release amount of the bulk cargo during dynamic operation, the bulk cargo dust handling coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under a single disturbance, the initial dust generation amount of each hexahedral grid can be calculated. This step comprehensively considers the physical characteristics of the bulk cargo, the handling operation method, and the influence of environmental wind erosion on dust generation.

[0119] In step S142, according to the initial dust generation amount of each hexahedral grid and the relative position relationship of each hexahedral grid, determine the self-settling dust amount of adjacent hexahedral grids in the vertical direction;

[0120] Among them, the self-settling dust amount refers to the amount of dust particles that settle from a higher position to a lower position (such as the adjacent lower-layer grid) under the action of gravity. According to the initial dust generation amount of each hexahedron grid and the relative position relationship of each hexahedron grid (especially the adjacent relationship in the vertical direction), the self-settling dust amount of adjacent hexahedron grids in the vertical direction is calculated using a settlement model or an empirical formula. This step takes into account the suspension time of dust particles in the air and the gravity settlement effect.

[0121] In step S143, according to the initial dust generation amount of each hexahedron grid, the self-settling dust amount of the adjacent upper hexahedron grid, and the self-settling dust amount of this hexahedron grid, the dynamic dust generation amount of each hexahedron grid is determined.

[0122] In the embodiments of the present disclosure, by calculating the initial dust generation amount of each hexahedron grid, the self-settling dust amount of the adjacent upper hexahedron grid, and the self-settling dust amount of this hexahedron grid itself (if any, because the bottommost grid has no lower-layer grid to receive the settled dust), the dynamic dust generation amount of each hexahedron grid can be determined. This step is an integration and correction of the previous steps to obtain a more accurate dust generation amount.

[0123] In a possible implementation manner, in step S13, through an attention mechanism, according to the dust release amount of the bulk cargo particles during dynamic operation and the loading and unloading method for the bulk cargo, the dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading is determined, including:

[0124] In step S131, based on the multi-head attention mechanism, using the dust loading and unloading coefficient as the query, the dust release amount of the bulk cargo particles during dynamic operation as the query, the first coefficient is determined, and using the dust loading and unloading coefficient as the query, the loading and unloading method for the bulk cargo as the query, the second coefficient is determined;

[0125] In the embodiments of the present disclosure, using the multi-head attention mechanism, the dust loading and unloading coefficient is used as the query (Query), and the dust release amount of the bulk cargo particles during dynamic operation and the loading and unloading method for the bulk cargo are used as two different keys (Key) and values (Value) respectively. For each group, we calculate the similarity between the query and each key (usually using the dot product), then normalize it through the softmax function to obtain the attention weights, and finally perform a weighted sum of the values according to these weights to obtain two coefficients: the first coefficient (based on the dust release amount) and the second coefficient (based on the loading and unloading method).

[0126] In step S132, according to the attention weights, a weighted sum of the first coefficient and the second coefficient is performed to determine the dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading.

[0127] In the embodiments of the present disclosure, a weighted sum of the first coefficient and the second coefficient is performed. The weights here can be preset or obtained through learning. The purpose of the weighted sum is to comprehensively consider the dust release amount of the bulk cargo and the influence of the loading and unloading method on the dust loading and unloading coefficient, so as to obtain a more accurate dust loading and unloading coefficient.

[0128] In a possible implementation manner, in step S15, according to the static wind erosion dust amount, dynamic dust generation amount of each hexahedral grid, and the duration of the bulk cargo during a single loading and unloading process, an estimation result of the dust release amount during the bulk cargo loading and unloading is determined, including:

[0129] In step S151, the product of the static wind erosion dust amount and the corresponding dynamic dust generation amount of each hexahedral grid is calculated to obtain the dust amount at each moment of each hexahedral grid;

[0130] In the embodiments of the present disclosure, by calculating the product of the static wind erosion dust amount and the corresponding dynamic dust generation amount of each hexahedral grid, the total dust amount of the grid at a certain moment is obtained. This step considers two dust sources, static wind erosion (such as dust release caused by natural wind) and dynamic dust generation (such as dust release caused by loading and unloading operations), and combines them to reflect the total dust amount of the grid at that moment.

[0131] In step S152, according to the duration of the bulk cargo during a single loading and unloading process, the dust diffusion coefficient is determined;

[0132] In the embodiments of the present disclosure, the dust diffusion coefficient is determined according to the duration of the bulk cargo during a single loading and unloading process. The longer the duration, the greater the chance of dust diffusion in space, so the diffusion coefficient will increase accordingly. This step considers the influence of time factors on dust diffusion.

[0133] In step S153, according to the dust diffusion coefficient and the dust amount at each moment of each hexahedral grid, a dust amount integration operation is performed to determine the single-grid dust amount of each hexahedral grid;

[0134] In the embodiments of the present disclosure, an integration operation is performed using the dust diffusion coefficient determined in step S152 and the dust amount at each moment of each hexahedral grid calculated in step S151. Here, the integration can be understood as the cumulative summation of the dust amount in the time domain (which can be summation in the discrete case) to obtain the total dust amount (i.e., the single-grid dust amount) in the grid during the entire loading and unloading process. The integration operation considers the cumulative effect of dust over time.

[0135] In step S154, the single-grid dust amounts of each hexahedral grid are summed to determine the estimation result of the dust release amount during the bulk cargo loading and unloading.

[0136] In the embodiments of the present disclosure, the dust amount of each single cell of the hexahedron grid is summed to obtain the total dust release amount in the entire loading and unloading operation area. This step is the integration and summary of the dust amounts of each grid calculated in the previous steps.

[0137] The embodiments of the present disclosure further provide an estimation device for the dust release amount during the bulk cargo loading and unloading in the port environment. Refer to Figure 2 as shown, the device includes:

[0138] A division module 210, configured to divide the port environment by using hexahedron grids with non-uniform volumes according to the first distance between the bulk cargo loading and unloading areas in the port environment and the bulk cargo particle values of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area, wherein the volume of the hexahedron grid is positively correlated with the second distance to the bulk cargo loading and unloading area;

[0139] A first determination module 220, configured to determine the wind erosion information of each hexahedron grid under a single disturbance according to the historical wind force information of the port environment and the dynamic wind erosion release factor, and determine the static wind erosion dust amount of each hexahedron grid under a single disturbance according to the bulk cargo particle values of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and the wind erosion information;

[0140] A second determination module 230, configured to determine the dust loading and unloading coefficient of the bulk cargo during dynamic operation and loading and unloading through an attention mechanism according to the dust release amount of the bulk cargo during dynamic operation and the loading and unloading method for the bulk cargo;

[0141] A third determination module 240, configured to determine the dynamic dust generation amount of each hexahedron grid according to the dust release amount of the bulk cargo during dynamic operation, the dust loading and unloading coefficient of the bulk cargo during dynamic operation, and the static wind erosion dust amount of each hexahedron grid under a single disturbance;

[0142] A fourth determination module 250, configured to determine the estimation result of the dust release amount during the bulk cargo loading and unloading according to the static wind erosion dust amount, the dynamic dust generation amount of each hexahedron grid, and the duration of the bulk cargo during a single loading and unloading process.

[0143] In a possible implementation manner, the partitioning module 210 is configured to: evenly divide the space where the port environment is located into hexahedron meshes according to a first distance between bulk cargo loading and unloading areas in the port environment, so as to obtain initial hexahedron meshes; determine the magnitude of the influence value of each initial hexahedron mesh affected by the loading and unloading of bulk cargo in multiple bulk cargo loading and unloading areas according to the bulk cargo particle values of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and a third distance from each initial hexahedron mesh to the bulk cargo loading and unloading area; determine an adjustment strategy for the initial hexahedron meshes according to the magnitude of the influence value of each initial hexahedron mesh affected by the loading and unloading of bulk cargo in multiple bulk cargo loading and unloading areas and a plurality of preset influence value thresholds, where the adjustment strategy includes merging with adjacent initial hexahedron meshes, or further dividing the initial hexahedron meshes themselves; and adjust each initial hexahedron mesh according to the adjustment strategy to complete the step of partitioning the port environment using hexahedron meshes with non-uniform volumes.

[0144] In a possible implementation manner, the partitioning module 210 is configured to: determine a first distance between bulk cargo loading and unloading areas in the port environment, and use the smallest first distance between the bulk cargo loading and unloading areas as the target distance, evenly divide the target distance into a plurality of segments with the same numerical value as the first quantity according to the first quantity of the bulk cargo loading and unloading areas, so as to obtain the value of each segment; determine the difference between the first distance between the bulk cargo loading and unloading areas and the target distance to obtain a plurality of first differences, and calculate the differences between the first differences in sequence according to the magnitudes of the first differences to obtain a plurality of second differences; calculate a first absolute value of the difference between a first average value of the first differences and a second average value of the second differences, and a second absolute value of the difference between the value of each segment and a third average value, where the third average value is the average value of the first average value and the second average value; determine the ratio of the first average value to the second absolute value as the side length of the hexahedron mesh for evenly partitioning the space where the port environment is located into hexahedron meshes; and according to the side length of the hexahedron mesh, starting from the central position of each bulk cargo loading and unloading area respectively, with the side length of the hexahedron mesh as the target side length, evenly divide the space where the port environment is located into hexahedron meshes in the same way as the beginning to obtain initial hexahedron meshes; where when adjacent bulk cargo loading and unloading areas meet during the uniform hexahedron mesh partitioning starting from their respective central positions, if a fourth distance of the remaining unpartitioned space is less than the side length of the hexahedron mesh, the unpartitioned space will no longer be partitioned, and if the fourth distance of the remaining unpartitioned space is greater than the side length of the hexahedron mesh and less than 2 times the side length of the hexahedron mesh, the fourth distance will be bisected to obtain two hexahedron meshes.

[0145] In a possible implementation manner, the first determination module 220 is configured to: determine the friction wind speed distribution of the port environment according to the wind direction information in the historical wind force information of the port environment and the position information of each bulk cargo loading and unloading area; determine the wind erosion information of each hexahedral grid under a single disturbance according to the dynamic wind erosion release factor, the friction wind speed distribution, and the central coordinates of each hexahedral grid; divide each hexahedral grid into different disturbance types according to the wind erosion information of each hexahedral grid under a single disturbance, where the disturbance type is used to represent the amount of dust corresponding to the hexahedral grid affected by the quantity of bulk cargo loaded and unloaded in the bulk cargo loading and unloading area and the magnitude of the influence value; determine the static wind erosion dust amount of each hexahedral grid under a single disturbance according to the bulk cargo particle value of the bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and the disturbance type corresponding to each hexahedral grid.

[0146] In a possible implementation manner, the first determination module 220 is configured to determine the wind erosion information of each hexahedral grid under a single disturbance in the following manner, including:

[0147] E i，j，k = a·μ * (x i，j，k , y i，j，k , z i，j，k ) b ;

[0148]

[0149] where E i，j，k represents the wind erosion information of the (i, j, k)-th hexahedral grid under a single disturbance, μ * represents the friction wind speed distribution function, a and b respectively represent the grid release factors in the dynamic wind erosion release factor set according to empirical values, U represents the observed wind speed of the port environment, ρ represents the air density, Z 0 represents the surface roughness length, C D represents the drag function, n represents the number of bulk cargo loading and unloading areas in the port environment, k m is the influence coefficient of the bulk cargo loading and unloading dust release amount corresponding to the m-th bulk cargo loading and unloading area on the (i, j, k)-th hexahedral grid, H m represents the maximum influence height of the m-th bulk cargo loading and unloading area, H ref represents the reference maximum influence height, α m and β m respectively represent the bulk cargo loading and unloading area wind direction release factors in the dynamic wind erosion release factor set according to empirical values, θ m represents the angle between the wind direction and the m-th bulk cargo loading and unloading area, x i，j，k , y i，j，k , z i，j，k are the central coordinates of the (i, j, k)-th hexahedral grid.

[0150] In a possible implementation manner, the third determination module 240 is configured to: calculate the product of the dust release amount of the bulk cargo particles during dynamic operation, the bulk cargo dust handling coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedron grid under a single disturbance to determine the initial dust generation amount of each hexahedron grid; determine the self-settling dust amount of adjacent hexahedron grids in the vertical direction according to the initial dust generation amount of each hexahedron grid and the relative position relationship of each hexahedron grid; determine the dynamic dust generation amount of each hexahedron grid according to the initial dust generation amount of each hexahedron grid, the self-settling dust amount of the adjacent upper hexahedron grid, and the self-settling dust amount of this hexahedron grid.

[0151] In a possible implementation manner, the second determination module 230 is configured to: based on the multi-head attention mechanism, use the dust handling coefficient as a query and the dust release amount of the bulk cargo particles during dynamic operation as a query to determine the first coefficient, and use the dust handling coefficient as a query and the handling method of the bulk cargo as a query to determine the second coefficient; perform weighted summation on the first coefficient and the second coefficient according to the attention weights to determine the dust handling coefficient of the bulk cargo during dynamic operation handling.

[0152] In a possible implementation manner, the fourth determination module 250 is configured to: calculate the product of the static wind erosion dust amount of each hexahedron grid and the corresponding dynamic dust generation amount to obtain the dust amount of each hexahedron grid at a moment; determine the dust diffusion coefficient according to the duration of the bulk cargo during a single handling process; perform dust amount integration operation according to the dust diffusion coefficient and the dust amount of each hexahedron grid at a moment to determine the single-grid dust amount of each hexahedron grid; sum up the single-grid dust amounts of each hexahedron grid to determine the estimated result of the dust release amount during bulk cargo handling.

[0153] The embodiments of the present disclosure further provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any one of the foregoing embodiments are implemented.

[0154] The embodiments of the present disclosure further provide an electronic device, including:

[0155] A memory, on which a computer program is stored;

[0156] A processor, configured to execute the computer program in the memory to implement the steps of the method described in any one of the foregoing embodiments.

[0157] Figure 3The estimating device 100 for the dust emission amount of bulk cargo handling in the port environment shown includes: a processor 1001 and a memory 1003. Among them, the processor 1001 and the memory 1003 are connected, such as being connected through a bus 1002. Optionally, the estimating device 100 for the dust emission amount of bulk cargo handling in the port environment may further include a communication component 1004, and the communication component 1004 can be used for data interaction between the device 100 and other devices, such as data sending and / or data receiving, etc. It should be noted that in actual scheduling, the communication component 1004 is not limited to one, and the structure of the estimating device 100 for the dust emission amount of bulk cargo handling in the port environment does not constitute a limitation on the embodiments of the present application.

[0158] The processor 1001 can be a CPU (Central Processing Unit, central processor), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), an ASIC (Application Specific Integrated Circuit, application-specific integrated circuit), an FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in combination with the disclosure of the present application. The processor 1001 can also be a combination that realizes computing functions, such as a combination including one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0159] The bus 1002 may include a path for transmitting information between the above components. The bus 1002 can be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture, extended industry standard architecture) bus, etc. The bus 1002 can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 3 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0160] The memory 1003 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), magnetic disk storage medium, other magnetic storage devices, or any other medium that can be used to carry or store program code and can be read by a computer, without limitation herein.

[0161] The memory 1003 is used to store program codes for executing the embodiments of the present disclosure, and the execution is controlled by the processor 1001. The processor 1001 is used to execute the program codes stored in the memory 1003 to implement the steps shown in the embodiment of the method for estimating dust release amount of bulk cargo loading and unloading in the port environment.

[0162] The embodiment of the present disclosure also provides a computer-readable storage medium having program code stored thereon. When the program code is executed by a processor, the steps and corresponding contents of the embodiment of the method for estimating dust release amount in bulk cargo loading and unloading in the aforementioned port environment can be implemented.

[0163] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, various changes, modifications, substitutions and variants can be made to these embodiments, and these changes, modifications, substitutions and variants all belong to the protection scope of the present disclosure. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner if there is no contradiction, and they should also be regarded as the contents disclosed by the present disclosure. In order to avoid unnecessary repetition, the present disclosure will not further explain various possible combinations. The technical scope of this application is not limited to the contents in the specification.

Claims

1. A method for estimating dust release from bulk cargo loading and unloading in a port environment, characterized in that: The method comprises: According to a first distance between bulk cargo loading and unloading areas in the port environment and a bulk cargo particle value of bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas, the port environment is divided using a volume-nonuniform hexahedral grid, wherein the volume of the hexahedral grid is positively correlated with a second distance to the bulk cargo loading and unloading area; Determine the wind erosion information of each of the hexahedral grids under a single disturbance based on the historical wind information and the dynamic wind erosion release factor of the port environment, and determine the static wind erosion dust amount of each of the hexahedral grids under a single disturbance based on the bulk cargo particle value of bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas and the wind erosion information; Determining the dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading according to the dust release amount of the bulk cargo particle value during dynamic operation and the loading and unloading method of the bulk cargo through an attention mechanism; Determine the dynamic dust emission of each hexahedral grid according to the dust release amount of the bulk cargo particle value during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under the single disturbance; The estimation result of the dust release amount during bulk cargo loading and unloading is determined based on the static wind erosion dust amount, the dynamic dust generation amount and the duration of the bulk cargo during a single loading and unloading process of each of the hexahedral grids.

2. The method for estimating dust release in bulk cargo loading and unloading in a port environment according to claim 1, characterized in that: The method of dividing the port environment by using a volumetrically non-uniform hexahedral grid according to the first distance between the bulk cargo loading and unloading areas in the port environment and the bulk cargo particle value of the bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas comprises: According to the first distance between the bulk cargo loading and unloading areas in the port environment, the space where the port environment is located is evenly divided into hexahedral grids to obtain an initial hexahedral grid; Determine the influence value of each of the initial hexahedral grids on the loading and unloading of bulk cargo in the bulk cargo loading and unloading areas according to the bulk cargo particle value of the bulk cargo in each of the bulk cargo loading and unloading areas and the third distance from each of the initial hexahedral grids to the bulk cargo loading and unloading area; Determine an adjustment strategy for the initial hexahedral mesh according to the influence value of each initial hexahedral mesh on the bulk cargo loading and unloading of the plurality of bulk cargo loading and unloading areas and a plurality of preset influence value thresholds, wherein the adjustment strategy includes merging the initial hexahedral mesh with the adjacent initial hexahedral meshes, or re-segmenting the initial hexahedral mesh itself; According to the adjustment strategy, each of the initial hexahedral grids is adjusted to complete the step of dividing the port environment using volumetrically non-uniform hexahedral grids.

3. The method for estimating dust release during bulk cargo loading and unloading in a port environment according to claim 2, characterized in that: The step of uniformly dividing the space where the port environment is located into hexahedral grids according to the first distance between the bulk cargo loading and unloading areas in the port environment to obtain an initial hexahedral grid includes: Determine a first distance between bulk cargo loading and unloading areas in the port environment, and take the minimum first distance between the bulk cargo loading and unloading areas as a target distance, and divide the target distance into a plurality of segments having the same value as the first number according to a first number of the bulk cargo loading and unloading areas, to obtain a value of each of the segments; Determine the difference between the first distance between the bulk cargo loading and unloading areas and the target distance to obtain a plurality of first differences, and calculate the differences between the first differences in sequence according to the magnitude of the first differences to obtain a plurality of second differences; Calculate a first absolute value of a difference between a first average value of the first difference and a second average value of the second difference, and a second absolute value of a difference between a value of each segment and a third average value, wherein the third average value is an average value of the first average value and the second average value; Determine the ratio of the first average value to the second absolute value as the side length of a hexahedral mesh for uniformly dividing the space where the port environment is located into hexahedral meshes; According to the side length of the hexahedral grid, taking the center position of each bulk cargo loading and unloading area as the starting point, the side length of the hexahedral grid is used as the target side length, and starting from the same step, the space where the port environment is located is evenly divided into hexahedral grids to obtain an initial hexahedral grid; Among them, when adjacent bulk cargo loading and unloading areas meet each other after being divided into uniform hexahedral grids starting from their respective center positions, if the fourth distance of the remaining undivided space is less than the side length of the hexahedral grid, the undivided space will no longer be divided; if the fourth distance of the remaining undivided space is greater than the side length of the hexahedral grid and less than 2 times the side length of the hexahedral grid, the fourth distance will be equally divided to obtain two hexahedral grids.

4. The method for estimating dust release during bulk cargo loading and unloading in a port environment according to claim 1, characterized in that: The method of determining the wind erosion information of each hexahedral grid under a single disturbance according to the historical wind force information and the dynamic wind erosion release factor of the port environment, and determining the static wind erosion dust amount of each hexahedral grid under a single disturbance according to the bulk cargo particle value of bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and the wind erosion information, includes: Determining the friction wind speed distribution of the port environment according to the wind force and direction information in the historical wind force information of the port environment and the location information of each bulk cargo loading and unloading area; Determine the wind erosion information of each hexahedral mesh under a single disturbance according to the dynamic wind erosion release factor, the friction wind speed distribution and the central coordinates of each hexahedral mesh; According to the wind erosion information of each hexahedral grid under a single disturbance, each hexahedral grid is divided into different disturbance types, wherein the disturbance type is used to indicate the influence of the amount of bulk cargo loaded and unloaded in the bulk cargo loading and unloading area on the dust amount corresponding to the hexahedral grid and the magnitude of the influence value; According to the bulk cargo particle value of bulk cargo loaded and unloaded in each bulk cargo loading and unloading area and the disturbance type corresponding to each hexahedral grid, the static wind erosion dust amount of each hexahedral grid under a single disturbance is determined.

5. The method for estimating dust release during bulk cargo loading and unloading in a port environment according to claim 4, characterized in that: Determining the wind erosion information of each hexahedral mesh under a single disturbance according to the dynamic wind erosion release factor, the friction wind speed distribution and the central coordinates of each hexahedral mesh includes: BY i，j，k =a·µ * (x i，j，k y i，j，k ,z i,j，k ) b 4 Among them, E i，j，k represents the wind erosion information of the (i, j, k)th hexahedral grid under a single disturbance, μ * represents the friction wind speed distribution function, a and b represent the grid release factors in the dynamic wind erosion release factor set according to the empirical value, U represents the observed wind speed in the port environment, ρ represents the air density, Z0 represents the surface roughness length, C D represents the drag function, n represents the number of bulk cargo loading and unloading areas in the port environment, k m is the influence coefficient of the dust release from bulk cargo loading and unloading corresponding to the mth bulk cargo loading and unloading area on the (i, j, k)th hexahedral grid, H m represents the maximum impact height of the mth bulk cargo loading and unloading area, H ref represents the reference maximum impact height, α m and β m They represent the wind direction release factor of bulk cargo loading and unloading area in the dynamic wind erosion release factor set by empirical value, θ m represents the angle between the wind direction and the mth bulk cargo loading and unloading area, x i，j，k ,y i，j，k , z i，j，k are the center coordinates of the (i, j, k)th hexahedral mesh.

6. The method for estimating dust release during bulk cargo loading and unloading in a port environment according to claim 1, characterized in that: Determining the dynamic dust generation amount of each hexahedral grid according to the dust release amount of the bulk cargo particle value during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under the single disturbance includes: Calculate the product of the dust release amount of the bulk cargo particle value during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each of the hexahedral grids under the single disturbance to determine the initial dust emission amount of each of the hexahedral grids; Determining the self-settling dust settling amount of the adjacent hexahedral grids in the vertical direction according to the initial dust generation amount of each hexahedral grid and the relative position relationship of each hexahedral grid; The dynamic dust generation amount of each hexahedral grid is determined according to the initial dust generation amount of each hexahedral grid, the self-settling dust generation amount of the adjacent previous hexahedral grid and the self-settling dust generation amount of the hexahedral grid.

7. The method for estimating dust release during bulk cargo loading and unloading in a port environment according to any one of claims 1 to 6, characterized in that: The dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading is determined according to the dust release amount of the bulk cargo particle value during dynamic operation and the loading and unloading method of the bulk cargo through the attention mechanism, including: Based on the multi-head attention mechanism, the dust loading and unloading coefficient is used as a query, and the dust release amount of the bulk cargo particle value during dynamic operation of the bulk cargo is used as a query to determine the first coefficient, and the dust loading and unloading coefficient is used as a query, and the loading and unloading method of the bulk cargo is used as a query to determine the second coefficient; According to the attention weight, the first coefficient and the second coefficient are weightedly summed to determine the dust loading and unloading coefficient of the bulk cargo during dynamic loading and unloading operations.

8. The method for estimating dust release during bulk cargo loading and unloading in a port environment according to any one of claims 1 to 6, characterized in that: Determining the estimated result of the dust release amount during bulk cargo loading and unloading based on the static wind erosion dust amount, the dynamic dust generation amount, and the duration of the bulk cargo during a single loading and unloading process of each of the hexahedral grids includes: Calculate the product of the static wind erosion dust amount and the corresponding dynamic dust emission amount of each hexahedral grid to obtain the dust amount of each hexahedral grid at a moment; Determine the dust diffusion coefficient based on the duration of a single loading and unloading process of the bulk cargo; Perform dust amount integration calculation according to the dust diffusion coefficient and the dust amount of each hexahedral grid at a moment, and determine the dust amount of each single grid of the hexahedral grid; The dust amounts of each single grid of the hexahedral grids are summed to determine an estimated result of the dust release amount during bulk cargo loading and unloading.

9. A device for estimating dust release during bulk cargo loading and unloading in a port environment, characterized in that: The device comprises: a partitioning module configured to partition the port environment using a volume-inhomogeneous hexahedral grid according to a first distance between bulk cargo loading and unloading areas in the port environment and a bulk cargo particle value of bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas, wherein the volume of the hexahedral grid is positively correlated with a second distance to the bulk cargo loading and unloading area; The first determination module is configured to determine the wind erosion information of each of the hexahedral grids under a single disturbance according to the historical wind force information and the dynamic wind erosion release factor of the port environment, and determine the static wind erosion dust amount of each of the hexahedral grids under a single disturbance according to the bulk cargo particle value of bulk cargo loaded and unloaded in each of the bulk cargo loading and unloading areas and the wind erosion information; A second determination module is configured to determine the dust loading and unloading coefficient of the bulk cargo during dynamic operation loading and unloading according to the dust release amount of the bulk cargo particle value of the bulk cargo during dynamic operation and the loading and unloading method of the bulk cargo through an attention mechanism; The third determination module is configured to determine the dynamic dust emission of each hexahedral grid according to the dust release amount of the bulk cargo particle value during dynamic operation, the bulk cargo dust loading and unloading coefficient during dynamic operation, and the static wind erosion dust amount of each hexahedral grid under the single disturbance; The fourth determination module is configured to determine an estimation result of the dust release amount during bulk cargo loading and unloading based on the static wind erosion dust amount, the dynamic dust emission amount and the duration of the bulk cargo during a single loading and unloading process of each of the hexahedral grids.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 8 are implemented.

11. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 8.

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