Dust and gas coupling explosion risk assessment method and terminal

Abstract

The invention relates to the technical field of risk assessment, in particular to a dust and gas coupling explosion risk assessment method and a terminal, and the method comprises the following steps: mapping dust and gas into comprehensive stoichiometric ratio distribution, clustering active grids in an explosion limit, analyzing the diameter of an inscribed sphere of a block mass and a body surface ratio, and screening an effective explosion source. According to the method, heterogeneous monitoring data is converted into a unified stoichiometric ratio field by constructing a multi-component medium three-dimensional combustion heat weighted mapping model, independent risk agglomerates are analyzed and identified by utilizing spatial connectivity, and the overall explosion risk level is evaluated. Geometric and thermodynamic dual verification is carried out on the block mass in combination with the maximum internally tangent ball diameter and the body surface ratio parameter, invalid areas incapable of maintaining combustion are removed according to the quenching distance and the heat dissipation effect, effective explosion sources are screened, the global risk level is judged, and the accuracy and objectivity of explosion risk assessment of the complex mixed medium in the limited space are improved.

Description

Technical Field

[0001] This invention relates to the field of risk assessment technology, and in particular to a method and terminal for assessing the risk of dust and gas coupled explosions. Background Technology

[0002] Risk assessment technology involves a comprehensive technical system that utilizes systems engineering and statistical principles to identify, quantify, and evaluate potential hazards. It encompasses qualitative and quantitative analysis of hazardous and harmful factors within a system, employing mathematical models and probabilistic statistical methods to calculate the likelihood of accidents and the severity of their consequences, determine risk levels, and formulate corresponding safety countermeasures. Widely applied in industrial production, chemical engineering, and environmental safety, it aims to achieve early warning and control of disasters through scientific calculation and analysis. Traditional dust and gas coupled explosion risk assessment methods refer to the process of determining the explosion hazard of a mixed system containing both combustible dust and flammable gas in an industrial environment. Existing assessment methods typically use a 20L spherical explosion test device to measure the lower explosive limit and maximum explosion pressure of a single dust or gas, then use Le Chatelier's formula to estimate the explosion limit of the mixed system, or directly apply the LEC evaluation method to manually assign values ​​based on expert experience to the probability of an accident, the frequency of human exposure to hazardous environments, and the consequences of an accident, and then determine the risk score by combining the results of these three factors.

[0003] Existing technologies typically estimate explosion limits using empirical formulas based on the assumption of uniform mixing, or rely on subjective assignment of risk factors based on human experience. These technologies ignore the non-uniformity of dust and gas distribution in three-dimensional space at industrial sites, making it impossible to accurately locate local high-concentration accumulation areas. Furthermore, they lack in-depth analysis of the spatial topology of the explosive medium, making it difficult to determine whether the geometry of the risk area meets the physical conditions for flame propagation and heat self-sustaining. This results in an inability to effectively distinguish between simple concentration exceeding the limit and effective explosion sources with actual propagation capabilities, causing deviations between risk assessment results and actual physical conditions. Consequently, it is difficult to achieve refined control over the explosion risks of complex mixed media. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a method for assessing the risk of dust-gas coupled explosions, comprising the following steps: To achieve the above objectives, the present invention adopts the following technical solution: a method for assessing the risk of dust-gas coupled explosion, comprising the following steps: S1: Collect dust concentration monitoring data and gas concentration monitoring data and map them to a spatial three-dimensional mesh model. Perform weighted normalized combustion heat mapping calculation on dust concentration monitoring data and gas concentration monitoring data based on combustion heat parameters to generate comprehensive stoichiometric ratio distribution data. S2: For the comprehensive stoichiometric ratio distribution data, active grid cells with values ​​within the preset explosion limit range parameters are selected, and connectivity analysis is performed on the active grid cells to connect and merge them into independent objects, generating a candidate risk connected domain set. S3: Analyze the connected domain volume parameters and connected domain surface area parameters of each three-dimensional clique in the candidate risk connected domain set, extract the internal skeleton and calculate the depth distance field for independent three-dimensional cliques, and output the maximum inscribed sphere diameter parameter of the minimum core thickness of the corresponding clique. S4: Compare the maximum inscribed sphere diameter parameter with the preset current mixed medium flame quenching distance parameter, and simultaneously calculate the volume-to-surface ratio of the connected domain volume parameter and the connected domain surface area parameter and match and verify them with the thermal self-sustaining critical parameter. Select independent three-dimensional clumps that meet the propagation and accumulation conditions, and generate a list of effective explosion source manifolds. S5: Accumulate the connected domain volume parameters of each independent three-dimensional block in the list of effective explosion source manifolds, compare them with the total volume parameters of industrial confined space, calculate the risk volume ratio parameter, match and determine it with the multi-level risk classification alarm interval parameter, and output the explosion risk assessment level.

[0005] As a further aspect of the present invention, the comprehensive stoichiometric ratio distribution data includes spatial grid location index, combustion potential energy value of mixed components, and oxygen combustion coefficient mapping value; the candidate risk connected domain set includes a potential active unit aggregation list, a three-dimensional spatial adjacency matrix, and the geometric centroid coordinates of the clump; the maximum inscribed sphere diameter parameter includes the spatial positioning vector of the inscribed sphere center, the extreme value of the distance transformation depth, and the fitted geometric radius metric; the effective explosion source manifold list includes a unique sequence number of the explosion source manifold, a thermodynamic propagation judgment flag, and a geometrically selected reserved state position; and the explosion risk assessment level includes a global risk quantification index, a safety control classification code, and a warning response trigger signal.

[0006] As a further aspect of the present invention, the step of obtaining the comprehensive stoichiometric ratio distribution data specifically includes: S101: By deploying sensor arrays at key nodes in industrial confined spaces, dust concentration monitoring data and gas concentration monitoring data characterizing the current environmental state are acquired. Combined with the three-dimensional position coordinate information of the sensor probe in the global coordinate system, the monitoring data and the three-dimensional position coordinate information are correlated to generate a discrete point monitoring data set containing discrete coordinate points and real-time concentration values. S102: Construct a spatial three-dimensional mesh model that adapts to the geometric boundary of the industrial confined space, traverse and analyze the geometric center coordinates of all mesh cells inside the model, perform Euclidean distance calculation for each sampling point in the discrete point monitoring data set, perform inverse weighted interpolation operation on the concentration data of each sampling point, map and fill the discretely distributed concentration values ​​into the spatial mesh cells, and establish a meshed concentration field matrix. S103: Extract the dust concentration and gas concentration values ​​recorded in each grid cell of the gridded concentration field matrix, perform weighted normalized combustion heat mapping calculation on the dust concentration monitoring data and gas concentration monitoring data, and generate comprehensive stoichiometric distribution data of the three-dimensional grid model covering the space and the corresponding mixed medium energy distribution state.

[0007] As a further aspect of the present invention, the step of obtaining the candidate risk connected component set specifically includes: S201: Perform a numerical scan of each grid cell on the comprehensive stoichiometric distribution data to obtain the pre-set lower explosion limit critical value and upper explosion limit critical value of the mixed medium, and compare them with each grid cell in intervals. Filter the target grid cells whose values ​​are within the interval range and record the geometric index position to establish an active grid cell state matrix. S202: Call the active grid cell state matrix and set the three-dimensional spatial adjacency determination rules. Perform neighborhood search starting from any active grid cell, detect the active state of adjacent grid cells, merge spatially continuous and active grid cells into the same cluster, and generate a spatial adjacency connected component index. S203: Based on the spatial adjacency connected component index, extract the coordinate data of the grid cells contained in each cluster, reconstruct the grid cells belonging to the same cluster into independent three-dimensional entities, count the number of grid cells in each independent three-dimensional entity and calculate the geometric centroid position, and generate a set of candidate risk connected components.

[0008] As a further aspect of the present invention, the process of obtaining the pre-set lower and upper critical values ​​for the explosion of the mixed medium, comparing them with each grid cell within a range, selecting target grid cells whose values ​​fall within the range, and recording their geometric index positions specifically includes: Obtain the standard pure phase lower explosive limit concentration and standard pure phase upper explosive limit concentration for the dust medium category corresponding to the current monitoring environment, and the standard pure phase lower explosive limit concentration and standard pure phase upper explosive limit concentration for the gas medium category; The mixed medium explosion limit coupling calculation logic is invoked. Based on the unit mass combustion heat parameter corresponding to the dust medium category and the unit volume combustion heat parameter corresponding to the gas medium category, the combustion heat contribution weight is calculated. According to the combustion heat contribution weight, a weighted coupling operation is performed on the standard pure phase lower explosion limit concentration value of the dust medium category and the standard pure phase lower explosion limit concentration value of the gas medium category to obtain the coupled lower explosion limit concentration and convert it into a dimensionless stoichiometric ratio value to generate the critical value of the lower explosion limit of the mixed medium. Using the aforementioned mixed-medium explosion limit coupling calculation logic, a weighted coupling operation and dimension conversion are performed on the standard pure-phase explosion limit concentration values ​​of the dust medium category and the standard pure-phase explosion limit concentration values ​​of the gas medium category to generate the critical value of the mixed-medium explosion limit. The comprehensive stoichiometry value of each grid cell in the comprehensive stoichiometry distribution data is read through it to construct an effective explosion threshold closed interval composed of the lower explosion limit critical value of the mixed medium and the upper explosion limit critical value of the mixed medium. The inclusion of the comprehensive stoichiometric ratio value and the effective explosion threshold closed interval is verified to determine whether the comprehensive stoichiometric ratio value is within the effective explosion threshold closed interval. Extract the mesh cells that pass the inclusion verification, mark them as the target mesh cells, and parse the three-dimensional axial position numbers of the target mesh cells in the coordinate system of the spatial three-dimensional mesh model, and combine them to generate the geometric index position.

[0009] As a further aspect of the present invention, the step of obtaining the maximum inscribed sphere diameter parameter specifically includes: S301: Based on the set of candidate risk connected components, analyze the internal mesh topology of each independent three-dimensional clique, count the total number of mesh units constituting the clique and convert it into a solid space volume value in combination with the physical size of the mesh, identify the surface mesh units that are in direct contact with the external inactive area at the boundary of the clique and calculate the surface area value, and generate spatial morphological geometric attribute data. S302: Call the spatial morphology geometric attribute data and extract the internal grid coordinate information of the independent three-dimensional clumps. Perform Euclidean distance transformation operation relative to the closed geometric boundary of the clump for each internal grid cell. Calculate the shortest straight-line spatial distance from the geometric center of each grid to the nearest boundary surface. Store the shortest straight-line spatial distance as a depth value in the corresponding coordinate node and establish the internal space depth distance field matrix. S303: Perform global numerical retrieval and extreme value filtering operations on the internal space depth distance field matrix, locate the grid node with the largest stored distance value in the matrix, extract the largest distance value as the maximum inscribed radius of the geometric center of the cluster, perform diameter conversion based on geometric multiple on the maximum inscribed radius, determine the limit physical span of the core area, and generate the maximum inscribed sphere diameter parameter corresponding to the minimum core thickness of the cluster.

[0010] As a further aspect of the present invention, the step of obtaining the list of effective explosion source manifolds specifically includes: S401: Based on the maximum inscribed sphere diameter parameter, a numerical comparison analysis is performed with the preset current mixed medium flame quenching distance parameter to determine whether the geometric scale of the core region of the agglomerate exceeds the minimum physical space limit required for free flame propagation. An allowed propagation index record is established for the agglomerates that have passed the determination, and a flame propagation geometric determination index is generated. S402: Call the connected domain volume parameter and the connected domain surface area parameter to calculate the body surface ratio value, obtain the preset thermal self-sustaining critical parameter, perform a numerical range comparison between the body surface ratio value and the thermal self-sustaining critical parameter, filter out the clumping objects whose body surface ratio value exceeds the critical requirement, and generate a heat accumulation judgment index. S403: Call the flame propagation geometric determination index and the heat accumulation determination index to perform dual condition verification on each independent three-dimensional mass, filter the mass index that simultaneously satisfies the geometric scale propagation condition and the thermodynamic energy accumulation condition, extract the corresponding spatial topology information and physical property data from the original dataset based on the retained index, and generate a list of valid explosion source manifolds.

[0011] As a further aspect of the present invention, the process of comparing and analyzing the numerical values ​​with the preset current mixed medium flame quenching distance parameters to determine whether the geometric scale of the core region of the agglomeration exceeds the minimum physical space limit required for free flame propagation, and establishing a propagation-allowed index record for the agglomerations that pass the determination, specifically involves: Obtain the standard dust cloud quenching distance for the dust medium category and the standard flame quenching distance for the gas medium category corresponding to the current monitoring environment. Execute conservative safety threshold selection logic and set the smaller of the standard dust cloud quenching distance and the standard flame quenching distance as the current mixed medium flame quenching distance parameter. A one-way numerical filtering rule is constructed, and the maximum inscribed sphere diameter parameter is compared with the current mixed medium flame quenching distance parameter. If the maximum inscribed sphere diameter parameter is greater than the current mixed medium flame quenching distance parameter, it is determined that the corresponding independent three-dimensional block has the geometric scale conditions to overcome the wall heat loss effect and maintain the flame front propagation. The identification code of the target independent three-dimensional block is extracted and written into the flame propagation geometric determination index. The process of calculating the body surface area ratio, obtaining a preset thermal self-sustaining critical parameter, comparing the body surface area ratio with the thermal self-sustaining critical parameter within a numerical range, and filtering out clumps whose body surface area ratio exceeds the critical requirement is specifically as follows: Perform spatial geometric property calculations, divide the volume parameter of the connected domain by the surface area parameter of the connected domain, and obtain the characteristic length value that characterizes the competitive relationship between the internal heat generation rate and the boundary heat dissipation rate of the independent three-dimensional mass, which is used as the volume-to-surface ratio value. Obtain the combustion reaction activation energy parameter and thermal conductivity parameter of the current mixed medium, and calculate the minimum characteristic length required to maintain the chain combustion reaction based on the thermal equilibrium critical equation, which is used as the thermal self-sustaining critical parameter; The body surface area ratio is compared with the thermal self-sustaining critical parameter. If the body surface area ratio is greater than the thermal self-sustaining critical parameter, the corresponding independent three-dimensional mass is determined to meet the positive heat accumulation condition, and is marked as the mass object and entered into the heat accumulation determination index.

[0012] As a further aspect of the present invention, the step of obtaining the explosion risk assessment level specifically includes: S501: For the list of effective explosion source manifolds, extract the connected component volume parameters associated with each independent three-dimensional mass in the list, construct a sequence of risk source volume values ​​to be processed, and perform mathematical accumulation operation on each volume value in the sequence to generate a global cumulative explosion source volume value. S502: Call the global cumulative explosion source volume value, obtain the total volume parameter of the industrial confined space that has been pre-mapped and stored in the database, compare the obtained cumulative volume value with the total volume parameter of the industrial confined space, obtain the numerical ratio of the effective risk source volume to the total volume, and generate the risk volume ratio parameter. S503: Based on the risk volume ratio parameter, obtain the preset multi-level risk classification alarm interval parameter, match and determine the risk volume ratio parameter with the multi-level risk classification alarm interval parameter, filter the target interval containing the current ratio parameter, perform state mapping according to the preset safety level definition associated with the target interval, and generate the explosion risk assessment level.

[0013] A dust-gas coupled explosion risk assessment terminal includes: The coupled data mapping module collects dust concentration monitoring data and gas concentration monitoring data and maps them to a three-dimensional spatial grid model. Based on the combustion heat parameters, it performs a weighted normalized combustion heat mapping operation on the dust concentration monitoring data and gas concentration monitoring data to generate comprehensive stoichiometric ratio distribution data. The regional connectivity clustering module, for the comprehensive stoichiometric ratio distribution data, filters active grid cells whose values ​​are within the preset explosion limit range parameters, performs connectivity analysis on the active grid cells, connects and merges them into independent objects, and generates a set of candidate risk connected domains. The morphological feature analysis module analyzes the connected domain volume parameters and connected domain surface area parameters of each three-dimensional clumping in the candidate risk connected domain set, extracts the internal skeleton and calculates the depth distance field for independent three-dimensional clumping, and outputs the maximum inscribed sphere diameter parameter of the minimum core thickness of the corresponding clumping. The source term validity filtering module compares the maximum inscribed sphere diameter parameter with the preset current mixed medium flame quenching distance parameter, and simultaneously calculates the volume-to-surface ratio of the connected domain volume parameter and the connected domain surface area parameter and verifies it with the thermal self-sustaining critical parameter. It then filters out independent three-dimensional clumps that meet the propagation and accumulation conditions and generates a list of effective explosion source manifolds. The global risk assessment module accumulates the connected domain volume parameters of each independent three-dimensional block in the list of effective explosion source manifolds, compares them with the total volume parameters of industrial confined spaces, calculates the risk volume ratio parameter, matches and determines it with the multi-level risk classification alarm interval parameters, and outputs the explosion risk assessment level.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, a three-dimensional combustion heat weighted mapping model of multi-component media is constructed to transform heterogeneous monitoring data into a unified stoichiometric field. Spatial connectivity analysis is used to identify independent risk clumps. The clumps are then verified geometrically and thermodynamically by combining the maximum inscribed sphere diameter and the volume surface ratio parameter. Invalid regions that cannot maintain combustion due to limitations in quenching distance and heat dissipation effects are eliminated, effective explosion sources are screened, and the global risk level is determined. This significantly improves the accuracy and objectivity of risk assessment for explosions in complex mixed media within confined spaces. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a diagram of the terminal module of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] Please see Figure 1 This invention provides a method for assessing the risk of dust and gas coupled explosions, comprising the following steps: S1: Collect dust concentration monitoring data and gas concentration monitoring data and map them to a spatial three-dimensional mesh model. Perform weighted normalized combustion heat mapping calculation on dust concentration monitoring data and gas concentration monitoring data based on combustion heat parameters to generate comprehensive stoichiometric ratio distribution data. S2: For the comprehensive stoichiometric ratio distribution data, active grid cells with values ​​within the preset explosion limit range parameters are selected, and connectivity analysis is performed on the active grid cells to connect and merge them into independent objects, generating a set of candidate risk connected domains. S3: Analyze the connected component volume parameters and connected component surface area parameters of each 3D clique in the candidate risk connected component set, extract the internal skeleton and calculate the depth distance field for independent 3D cliques, and output the maximum inscribed sphere diameter parameter of the minimum core thickness of the corresponding clique. S4: Compare the maximum inscribed sphere diameter parameter with the preset current mixed medium flame quenching distance parameter, and simultaneously calculate the volume-to-surface ratio of the connected domain volume parameter and the connected domain surface area parameter and match and verify them with the thermal self-sustaining critical parameter. Select independent three-dimensional clumps that meet the propagation and accumulation conditions, and generate a list of effective explosion source manifolds. S5: Accumulate the connected domain volume parameters of each independent three-dimensional block in the list of effective explosion source manifolds, compare them with the total volume parameters of industrial confined space, calculate the risk volume ratio parameter, match and determine it with the multi-level risk classification alarm interval parameters, and output the explosion risk assessment level.

[0023] The comprehensive stoichiometric distribution data includes spatial grid location index, combustion potential energy value of mixed components, and oxygen combustion coefficient mapping value. The candidate risk connected domain set includes a list of potential active units, a three-dimensional spatial adjacency matrix, and the geometric centroid coordinates of the clumps. The maximum inscribed sphere diameter parameter includes the spatial positioning vector of the inscribed sphere center, the extreme value of the distance transformation depth, and the fitted geometric radius measure. The effective explosion source manifold list includes the unique sequence number of the explosion source manifold, the thermodynamic propagation judgment mark, and the geometrically selected and retained state position. The explosion risk assessment level includes the global risk quantification index, the safety control classification code, and the early warning response trigger signal.

[0024] Please see Figure 2 The specific steps for obtaining the comprehensive stoichiometric ratio distribution data are as follows: S101: By deploying sensor arrays at key nodes in industrial confined spaces, dust concentration monitoring data and gas concentration monitoring data characterizing the current environmental state are acquired. Combined with the three-dimensional position coordinate information of the sensor probe in the global coordinate system, the monitoring data and the three-dimensional position coordinate information are correlated to generate a discrete point monitoring data set containing discrete coordinate points and real-time concentration values. Firstly, the spatial geometric dimension is length. ,Width ,high A sensor array is deployed within the factory building. The sensor array consists of 30 multi-parameter composite detection nodes, which are installed at key locations such as crane beams, waste pit sidewalls, and top ventilation openings, forming a three-dimensional monitoring network. Each detection node integrates a laser backscattered dust concentration sensor (model LDS-500, range...). The system includes electrochemical gas sensor modules (specifically for ammonia, hydrogen sulfide, and methane). During system operation, the main control unit transmits signals via the industrial Ethernet protocol every [time period missing]. A data acquisition command is triggered synchronously. For example, the coordinates located above the center of the factory building. The 12th sensor node (unit: meters) is located in... The data collected at all times is: the concentration value of suspended ash and dust. ammonia concentration value Hydrogen sulfide concentration value methane concentration value (Volume fraction). Simultaneously, the system database stores the fixed three-dimensional position coordinates of this node in the global coordinate system. After receiving the raw signal, the data processing server converts the analog signal into a digital signal and binds the concentration value with the corresponding three-dimensional location coordinate information to form a structured record containing "coordinates-dust concentration-concentration of each component gas". After traversing the data of all 30 nodes, a set of discrete point monitoring values ​​for that time slice is generated, as shown in Table 1.

[0025] Table 1. Real-time data sampling table for monitoring points at time T: Sensor number X-coordinate (m) Y coordinate (m) Z-coordinate (m) <![CDATA[Dust concentration (g / m 3 )]]> Ammonia concentration (ppm) Hydrogen sulfide concentration (ppm) methane concentration (%) Node_01 5.0 5.0 2.0 12.5 45.0 5.2 0.2 Node_12 25.0 15.0 10.0 35.0 150.0 20.0 0.8 Node_30 45.0 25.0 18.0 8.2 30.0 2.5 0.1 As shown in Table 1, this dataset not only records discrete spatial point information, but also provides basic data support for the original physical field for subsequent interpolation calculations.

[0026] S102: Construct a spatial three-dimensional mesh model that adapts to the geometric boundary of the industrial confined space, traverse and analyze the geometric center coordinates of all mesh cells inside the model, perform Euclidean distance calculation for each sampling point in the discrete point monitoring data set, perform inverse weighted interpolation operation on the concentration data of each sampling point, map and fill the discretely distributed concentration values ​​into the spatial mesh cells, and establish a meshed concentration field matrix. First, based on the aforementioned physical boundaries of the factory building ( A spatial 3D mesh model adapted to the geometric boundaries of the industrial restricted space is constructed in computational memory. The mesh generation precision is set to [value missing]. Discretize the entire space into Each independent cubic mesh cell contains This indicates the total number of mesh cells after partitioning. The program iterates through and analyzes the geometric center coordinates of all mesh cells within the model, for example, for the index... Grid cell center point Then, the inverse distance weighted interpolation (IDW) algorithm is executed. The algorithm first calculates the center point. The data from the discrete monitoring points in Table 1 are 30 sampling points. Euclidean distance The calculation formula is: In the formula The coordinates of the grid center point, For the first The coordinates of each sampling point. For example, calculate the coordinates of the grid center and Node_12 (coordinates). The distance is close to 0 (in actual calculations, a smoothing factor is set). To prevent division by zero), and Node_01 (coordinates) The distance is The system sets the distance attenuation power exponent to be... Calculate the weight of each sampling point Subsequently, an inverse weighted interpolation operation was performed on the concentration data at each sampling point, i.e. In the formula These are the interpolated grid concentration values. For the first The actual monitored concentration value at each sampling point The corresponding weights are used. After calculating each of the 30,000 grid cells, the originally discrete concentration values ​​are mapped and filled into the entire spatial grid cell, establishing a gridded concentration field matrix. In this matrix, the coordinates... The dust concentration of the neighboring grid cells is calculated by interpolation and then assigned a value. The methane concentration was assigned a value This enables continuous reconstruction from point data to field data.

[0027] S103: Extract the dust concentration and gas concentration values ​​recorded in each grid cell of the gridded concentration field matrix, perform weighted normalized combustion heat mapping calculation on the dust concentration monitoring data and gas concentration monitoring data, and generate comprehensive stoichiometric distribution data of the three-dimensional grid model covering the space and the corresponding mixed medium energy distribution state. Extract the dust concentration and gas concentration values ​​recorded in each grid cell from the gridded concentration field matrix. For example, extract its dust concentration. The concentration of the mixed gas needs to be converted into an energy contribution value. The unit mass combustion heat parameters of municipal solid waste incineration ash should be set. for For the gas mixture, set its weighted average heat of combustion per unit volume. for (Mainly methane). Perform a weighted normalized combustion heat mapping operation, first calculating the total energy density within the grid. The calculation formula is: Here This represents the volume fraction of the gas (0.8%, which is 0.008). Substitute the values ​​into the calculation: Obtain the standard reference measurement specific energy density. (Set as the energy density of pure methane at a stoichiometric concentration of 9.5%, i.e.) To simplify the calculation, the values ​​are selected. Next, calculate the overall stoichiometry. This value equals Divide by In this example, The system repeats this process for all 30,000 grids to generate comprehensive stoichiometric distribution data covering the three-dimensional grid model of the space and the corresponding energy distribution state of the mixed medium. This data intuitively reflects the energy saturation of the mixed medium at various points in space relative to the theoretical state of complete combustion.

[0028] Please see Figure 3 The specific steps for obtaining the candidate risk connected component set are as follows: S201: Perform numerical scanning of each grid cell for the comprehensive stoichiometric distribution data, obtain the pre-set lower explosion limit critical value and upper explosion limit critical value of the mixed medium, compare them with each grid cell in interval, filter the target grid cells whose values ​​are within the interval range and record the geometric index position, and establish the active grid cell state matrix. The process of obtaining the pre-set lower and upper critical values ​​for the explosion of the mixed medium, comparing them with each grid cell within a range, selecting target grid cells whose values ​​fall within the range, and recording their geometric index positions specifically includes: Obtain the standard pure phase lower explosive limit concentration and standard pure phase upper explosive limit concentration for the dust medium category corresponding to the current monitoring environment, and the standard pure phase lower explosive limit concentration and standard pure phase upper explosive limit concentration for the gas medium category; The mixed medium explosion limit coupling calculation logic is invoked. Based on the unit mass combustion heat parameter corresponding to the dust medium category and the unit volume combustion heat parameter corresponding to the gas medium category, the combustion heat contribution weight is calculated. According to the combustion heat contribution weight, a weighted coupling operation is performed on the standard pure phase lower explosion limit concentration value of the dust medium category and the standard pure phase lower explosion limit concentration value of the gas medium category to obtain the coupled lower explosion limit concentration and convert it into a dimensionless stoichiometric ratio value to generate the critical value of the lower explosion limit of the mixed medium. Using the aforementioned mixed-medium explosion limit coupling calculation logic, a weighted coupling operation and dimension conversion are performed on the standard pure-phase explosion limit concentration values ​​of the dust medium category and the standard pure-phase explosion limit concentration values ​​of the gas medium category to generate the critical value of the mixed-medium explosion limit. The comprehensive stoichiometry value of each grid cell in the comprehensive stoichiometry distribution data is read through it to construct an effective explosion threshold closed interval composed of the lower explosion limit critical value of the mixed medium and the upper explosion limit critical value of the mixed medium. The inclusion of the comprehensive stoichiometric ratio value and the effective explosion threshold closed interval is verified to determine whether the comprehensive stoichiometric ratio value is within the effective explosion threshold closed interval. Extract the mesh cells that pass the inclusion verification, mark them as the target mesh cells, and parse the three-dimensional axial position numbers of the target mesh cells in the coordinate system of the spatial three-dimensional mesh model, and combine them to generate the geometric index position; A numerical scan of each grid cell is performed on the generated integrated stoichiometric distribution data. First, the pre-defined lower explosion limit value of the mixture is obtained. Critical value of the upper limit of explosion This embodiment calls the mixed-medium explosion limit coupling calculation logic to obtain the standard pure-phase lower explosion limit concentration of ash dust. (corresponding energy density) The standard pure-phase lower explosive limit of gaseous media (corresponding energy density) Based on the energy form of Le Chatelier's law, the normalized lower limit of explosion in the energy dimension of the mixed medium is calculated. Considering that the lean-burn limit of typical hydrocarbon gases is approximately 0.5, and that the addition of dust reduces the critical energy requirement, a dimensionless lower explosive limit value for the mixed medium was set after experimental calibration. Explosion upper limit critical value The system calculates the comprehensive stoichiometry for each grid cell. With this interval Perform a comparison. For example, for a grid... ,That Value less than Therefore, this grid is marked as inactive (0). As for the grid near the feed inlet... Due to the localized accumulation of high concentrations of biogas and dust, its calculated... Value ,lie in If the value is within the specified range, the system determines that the value is within the range, marks the target mesh cell as "active" (1), and records its geometric index position. After traversing the entire field, an active grid cell state matrix is ​​established. This matrix is ​​a 30,000-dimensional binary array in which only the grid positions that satisfy the explosion limit condition are set to 1, and the rest are 0.

[0029] S202: Call the active grid cell state matrix and set the three-dimensional spatial adjacency determination rules. Perform neighborhood search starting from any active grid cell, detect the active state of adjacent grid cells, merge spatially continuous and active grid cells into the same cluster, and generate a spatial adjacency connected component index. The generated active mesh cell state matrix is ​​called, and the 3D spatial adjacency determination rule is set to "26-neighborhood connectivity", that is, a mesh cell and its directly adjacent face contact cells, edge contact cells, and vertex contact cells in the X, Y, and Z axes are all considered neighbors. The algorithm takes the first mesh cell in the matrix with a state of "active" (1) (e.g., coordinate...) as its neighbor. Starting from a given point, a breadth-first search (BFS) is performed. The program checks the activation state of the 26 neighboring grid cells around this starting point. If the coordinates are found... If a cell is also "active," it is added to the current queue and the search continues outwards. This process continues until there are no more connected active cells on the current search path. All spatially contiguous and state-activated cells accessed through this search are merged into the same cluster (e.g., labeled Cluster_ID_01). The algorithm then continues scanning the matrix for other unvisited active nodes, repeating the above process. Ultimately, the thousands of active cells originally scattered in space are structurally divided into several independent connected regions, generating spatial adjacency connectivity component indices. For example, the index table records that Cluster_01 contains... Cluster_02 contains [number] grids. Each grid.

[0030] S203: Based on the spatial adjacency connected component index, extract the coordinate data of the grid cells contained in each cluster, reconstruct the grid cells belonging to the same cluster into independent three-dimensional entities, count the number of grid cells in each independent three-dimensional entity and calculate the geometric centroid position, and generate a set of candidate risk connected components. Based on the generated spatial adjacency connected component index, the coordinate data of all grid cells contained within each cluster are extracted. For Cluster_01, the system reads the coordinate list of its 500 grid cells and reconstructs grid cells belonging to the same cluster into independent 3D entities (i.e., an irregular "cloud"). The number of grid cells in each independent 3D entity is counted, for example, the number in Cluster_01. The number of Cluster_02 Simultaneously calculate the position of the geometric centroid, using the following formula: For Cluster_01, the centroid coordinates are obtained as follows: For Cluster_02, the calculated centroid coordinates are as follows: The system encapsulates these objects, which contain volume (number of grids), centroid coordinates, and a detailed list of constituent elements, to generate a set of candidate risk connected components.

[0031] Please see Figure 4 The specific steps for obtaining the maximum inscribed sphere diameter parameter are as follows: S301: Based on the candidate risk connected component set, analyze the internal mesh topology of each independent 3D clique, count the total number of mesh units constituting the clique and convert it into a solid space volume value by combining the mesh physical size, identify the surface mesh units that are in direct contact with the external inactive area at the boundary of the clique and calculate the surface area value, and generate spatial morphological geometric attribute data. Based on the set of candidate risk connected components, an independent 3D clique named Obj_A (derived from Cluster_01) is analyzed. First, its internal mesh topology is analyzed, and the total number of mesh cells constituting the clique is counted. Since the volume of a single mesh is... If Obj_A has 500 meshes, then it can be directly converted into a solid space volume value. Next, the algorithm identifies the clutter boundaries. It iterates through each grid cell of Obj_A, checking if any of its six faces are in contact with inactive grids (value 0) or boundaries. If a grid has... If a face is exposed to an inactive region, then the mesh contributes... The surface area of ​​Obj_A is calculated by summing the number of exposed surfaces. The total external physical interface (connected region surface area parameter) of Obj_A is then calculated. for Similarly, for the smaller Obj_B (originating from Cluster_02, volume...) ) is calculated to obtain its surface area as These data generated spatial morphological geometric attribute data, including volume and surface area.

[0032] S302: Call the spatial morphology geometric attribute data and extract the internal mesh coordinate information of the independent three-dimensional clumps. Perform Euclidean distance transformation operation relative to the closed geometric boundary of the clump for each internal mesh unit, calculate the shortest straight-line spatial distance from the geometric center of each mesh to the nearest boundary surface, store the shortest straight-line spatial distance as the depth value in the corresponding coordinate node, and establish the internal space depth distance field matrix. The spatial morphological geometric attribute data is retrieved, with a focus on processing the internal mesh coordinate information of Obj_A. This is done for each mesh cell within Obj_A (e.g., the mesh itself). The algorithm performs a DistanceTransform operation relative to the closed geometric boundary of the cluster. The nearest boundary mesh surface, and calculation The shortest straight-line spatial distance from the geometric center to the boundary surface In the formula, Indicates the first The depth distance value of each internal grid. Indicates the first The geometric center coordinate vector of each internal grid cell. This represents the coordinate vector of any grid surface that constitutes the boundary of the cluster. This represents the function that takes the minimum value. This indicates the calculation of the Euclidean distance (i.e., modulus) between two vectors. For example, for a mesh located at the edge of a cloud, this distance might be only... For grids deeply embedded in the center of cloud clusters, this distance could reach... The program calculates the shortest straight-line spatial distance from the geometric center of each grid to the nearest boundary surface, and stores this distance value as a depth value in the corresponding coordinate node. After calculating the entire clutter, an internal spatial depth-distance field matrix is ​​established.

[0033] S303: Perform global numerical search and extreme value filtering operations on the internal space depth distance field matrix, locate the grid node with the largest stored distance value in the matrix, extract the largest distance value as the maximum inscribed radius of the geometric center of the clique, perform diameter conversion based on geometric multiple on the maximum inscribed radius, determine the limit physical span of the core area, and generate the maximum inscribed sphere diameter parameter corresponding to the minimum core thickness of the clique. A global numerical search is performed on the internal spatial depth-distance field matrix of Obj_A. The system compares the depth values ​​recorded in all grids in the matrix and locates the grid node with the largest stored distance value (assuming it is a coordinate). (points), extract the maximum distance value (e.g.) Let be the maximum inscribed radius of the geometric center of the cluster. This means that a space with a radius of can be placed inside the cloud. The largest sphere is obtained without touching the boundary. Then, a diameter conversion based on a geometric multiple is performed on the largest inscribed radius, i.e. In this example, the calculated limit physical span of the core area is... The system outputs the maximum inscribed sphere diameter parameter corresponding to the minimum core thickness of the cluster. For the smaller Obj_B, the same calculation shows that its maximum inscribed radius is only... The corresponding maximum inscribed sphere diameter parameter .

[0034] Please see Figure 5 The specific steps for obtaining the list of effective explosion source manifolds are as follows: S401: Based on the maximum inscribed sphere diameter parameter, a numerical comparison analysis is performed with the preset current mixed medium flame quenching distance parameter to determine whether the geometric scale of the core region of the agglomeration exceeds the minimum physical space limit required for free flame propagation. An allowed propagation index record is established for the agglomerations that pass the determination, and a flame propagation geometric determination index is generated. Regarding the calculated maximum inscribed sphere diameter parameters The parameters are compared with preset parameters. First, the specific process of "obtaining preset current mixed medium flame quenching distance parameters" is executed: the system queries the database to obtain the standard dust cloud quenching distance for the dust medium (ash and slag) corresponding to the current monitoring environment. (Set as) (This value is a setpoint for the macroscopic quenching scale, taking into account the turbulence and non-uniformity at the industrial scale) and the standard flame quenching distance for gaseous media (methane / ammonia). (Set as) A conservative safety threshold selection logic is implemented. Considering the complexity of the coupled environment and the need for macro-risk assessment, the larger of the two values ​​is selected, and an industrial safety factor is introduced. Set the current flame quenching distance parameter for the mixed medium. Construct a one-way numerical filtering rule to filter Obj_A. ( )and ( ) for comparison, because The system determines that Obj_A possesses the geometrical conditions to overcome wall heat loss and maintain flame front propagation, and extracts Obj_A's identification code, writing it into the flame propagation geometry determination index. Obj_B's... ( (less than) If it is determined to be a non-dangerous area that is easily quenched, it will not be written into the index.

[0035] S402: Call the connected domain volume parameter and the connected domain surface area parameter to calculate the body surface ratio value, obtain the preset thermal self-sustaining critical parameter, perform a numerical range comparison between the body surface ratio value and the thermal self-sustaining critical parameter, filter out the clumping objects whose body surface ratio value exceeds the critical requirement, and generate a heat accumulation judgment index. Continue thermodynamic verification of Obj_A. Use the connected component volume parameters calculated in S301. ( ) and surface area parameters of connected regions ( Perform spatial geometric property operations to calculate the feature length. Substitute the values: This value characterizes the characteristic length of the relationship between the internal heat generation rate and the boundary heat dissipation rate of an independent three-dimensional mass, i.e., the volume surface area ratio. Simultaneously, a preset thermal self-sustaining critical parameter is obtained. The process for obtaining this parameter is as follows: Obtain the activation energy parameter of the combustion reaction in the current mixed medium. ( ) and thermal conductivity parameter ( Based on the Frank-Kamenetskii thermal autoignition theory model, the minimum characteristic length required to sustain a chain combustion reaction was calculated. Assume that the critical thermal self-sustaining parameters under this environment are calculated. The calculated body surface area ratio ( ) and thermal self-sustaining critical parameter ( Perform numerical comparison. Because... If the corresponding independent three-dimensional clumping is determined to meet the positive heat accumulation condition (i.e., heat generation is faster than heat dissipation), it is marked as a clumping object and entered into the heat accumulation determination index.

[0036] S403: Call the flame propagation geometric determination index and the heat accumulation determination index, perform dual condition verification on each independent three-dimensional clutter, filter the clutter index that simultaneously satisfies the geometric scale propagation condition and the thermodynamic energy accumulation condition, extract the corresponding spatial topology information and physical property data from the original dataset based on the retained index, and generate a list of valid explosion source manifolds. The flame propagation geometry determination index (containing Obj_A) and the heat accumulation determination index (containing Obj_A) are invoked. Dual condition verification is performed on each independent 3D blob; only blobs appearing in both indices are retained. Obj_A simultaneously satisfies the geometric scale propagation condition (…). ) and thermodynamic energy accumulation conditions ( Therefore, it passes the screening. Suppose there is another mass, Obj_C, which is large in volume but flat in shape, resulting in a body surface area ratio smaller than [value missing]. If the index is not valid, it will be removed. Based on the retained index (Obj_A), the system extracts the corresponding spatial topology information and physical attribute data from the original dataset to generate a list of valid explosion source manifolds. At this point, the list only contains connected components that have been filtered for physical validity and are truly at risk of explosion.

[0037] Please see Figure 6 The specific steps for obtaining the explosion risk assessment level are as follows: S501: For the list of effective explosion source manifolds, extract the connected component volume parameters associated with each independent three-dimensional mass in the list, construct a sequence of risk source volume values ​​to be processed, perform mathematical accumulation on each volume value in the sequence, and generate a global cumulative explosion source volume value. For a list of valid explosion source manifolds, the connected component volume parameters associated with each independent 3D clique in the list are extracted item by item. Assume the list contains two valid cliques: Obj_A ( ) and Obj_D ( (Another newly detected cluster). Construct a numerical sequence of the volumes of the risk sources to be processed. Perform a mathematical summation operation on each volume value contained in the sequence, i.e. Generates the global cumulative explosion source volume value. This value represents the total volume of all areas within the entire plant that could potentially explode and cause damage.

[0038] S502: Call the global cumulative explosion source volume value, obtain the total volume parameter of the industrial confined space that has been pre-mapped and stored in the database, compare the obtained cumulative volume value with the total volume parameter of the industrial confined space, obtain the numerical ratio of the effective risk source volume to the total volume, and generate the risk volume ratio parameter. Call the global cumulative explosion source volume value ( Obtain the total volume parameters of the pre-mapped and stored industrial confined space in the database. In this example, the factory building dimensions are... Total volume The accumulated volume values ​​are compared with the total volume parameters of the industrial confined space. The calculation formula is as follows: Substitute the values: The numerical proportion of the effective risk source volume to the total volume is obtained as follows: Generate the risk volume ratio parameter.

[0039] S503: Based on the risk volume ratio parameter, obtain the preset multi-level risk classification alarm interval parameter, match and determine the risk volume ratio parameter with the multi-level risk classification alarm interval parameter, filter the target interval containing the current ratio parameter, perform state mapping according to the preset safety level definition associated with the target interval, and generate the explosion risk assessment level. Based on the calculated risk volume ratio parameter ( The system retrieves preset multi-level risk classification alarm range parameters. This parameter table, shown in Table 2, is formulated based on the "Hygienic Standards for Industrial Enterprise Design" and related explosion risk assessment specifications.

[0040] Table 2 Definition of Explosion Risk Classification Alarm Intervals: Risk level Lower limit of the percentage range (%) Upper limit of the percentage range (%) Safety control definition Level I 0.00 1.00 Blue - Low risk, maintain routine inspections. Level II 1.00 5.00 Yellow-medium risk, activate local ventilation. Level III 5.00 10.00 Orange - High risk, entry restricted. Level IV 10.00 100.00 Red - Extremely high risk, emergency shutdown and evacuation required. Refer to Table 2, the system will use the risk volume ratio parameter ( It is matched and determined with the multi-level risk classification alarm interval parameters. lie in Within the specified range, the target range containing the current proportion parameter is selected as Level II. A state mapping is performed based on the preset safety level definition associated with the target range, generating an explosion risk assessment level of "Level II (Yellow - Medium Risk)". This result indicates that although a valid explosion source exists within the current plant, its total volume proportion has not yet reached the level to cause global catastrophic damage. Based on this, the system will output control commands to automatically activate local explosion-proof fans for intervention.

[0041] Please see Figure 7 A dust and gas coupled explosion risk assessment terminal, comprising: The coupled data mapping module collects dust concentration monitoring data and gas concentration monitoring data and maps them to a three-dimensional spatial grid model. Based on the combustion heat parameters, it performs a weighted normalized combustion heat mapping operation on the dust concentration monitoring data and gas concentration monitoring data to generate comprehensive stoichiometric ratio distribution data. The regional connectivity clustering module, for the comprehensive stoichiometric ratio distribution data, filters active grid cells whose values ​​are within the preset explosion limit range parameters, performs connectivity analysis on the active grid cells, connects and merges them into independent objects, and generates a set of candidate risk connectivity domains. The morphological feature analysis module analyzes the connected domain volume parameters and connected domain surface area parameters of each 3D clique in the candidate risk connected domain set, extracts the internal skeleton and calculates the depth distance field for independent 3D cliques, and outputs the maximum inscribed sphere diameter parameter of the minimum core thickness of the corresponding clique. The source term validity filtering module compares the maximum inscribed sphere diameter parameter with the preset current mixed medium flame quenching distance parameter, and simultaneously calculates the volume-to-surface ratio of the connected domain volume parameter and the connected domain surface area parameter and matches and verifies them with the thermal self-sustaining critical parameter. It then filters out independent three-dimensional clumps that meet the propagation and accumulation conditions and generates a list of effective explosion source manifolds. The global risk assessment module accumulates the connected domain volume parameters of each independent three-dimensional block in the list of effective explosion source manifolds, compares them with the total volume parameters of industrial confined spaces, calculates the risk volume ratio parameter, matches and determines it with the multi-level risk classification alarm interval parameters, and outputs the explosion risk assessment level.

[0042] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for assessing the risk of dust-gas coupled explosion, characterized in that, Includes the following steps: S1: Collect dust concentration monitoring data and gas concentration monitoring data and map them to a spatial three-dimensional mesh model. Perform weighted normalized combustion heat mapping calculation on dust concentration monitoring data and gas concentration monitoring data based on combustion heat parameters to generate comprehensive stoichiometric ratio distribution data. S2: For the comprehensive stoichiometric ratio distribution data, active grid cells with values ​​within the preset explosion limit range parameters are selected, and connectivity analysis is performed on the active grid cells to connect and merge them into independent objects, generating a candidate risk connected domain set. S3: Analyze the connected domain volume parameters and connected domain surface area parameters of each three-dimensional clique in the candidate risk connected domain set, extract the internal skeleton and calculate the depth distance field for independent three-dimensional cliques, and output the maximum inscribed sphere diameter parameter of the minimum core thickness of the corresponding clique. S4: Compare the maximum inscribed sphere diameter parameter with the preset current mixed medium flame quenching distance parameter, and simultaneously calculate the volume-to-surface ratio of the connected domain volume parameter and the connected domain surface area parameter and match and verify them with the thermal self-sustaining critical parameter. Select independent three-dimensional clumps that meet the propagation and accumulation conditions, and generate a list of effective explosion source manifolds. S5: Accumulate the connected domain volume parameters of each independent three-dimensional block in the list of effective explosion source manifolds, compare them with the total volume parameters of industrial confined space, calculate the risk volume ratio parameter, match and determine it with the multi-level risk classification alarm interval parameter, and output the explosion risk assessment level.

2. The dust and gas coupled explosion risk assessment method according to claim 1, characterized in that, The comprehensive stoichiometric distribution data includes spatial grid location index, combustion potential energy value of mixed components, and oxygen combustion coefficient mapping value. The candidate risk connected domain set includes a list of potential active units, a three-dimensional spatial adjacency matrix, and the geometric centroid coordinates of the clumps. The maximum inscribed sphere diameter parameter includes the spatial positioning vector of the inscribed sphere center, the extreme value of the distance transformation depth, and the fitted geometric radius measure. The effective explosion source manifold list includes the unique sequence number of the explosion source manifold, the thermodynamic propagation judgment mark, and the geometrically selected and retained state position. The explosion risk assessment level includes the global risk quantification index, the safety control classification code, and the early warning response trigger signal.

3. The dust and gas coupled explosion risk assessment method according to claim 1, characterized in that, The specific steps for obtaining the comprehensive stoichiometric ratio distribution data are as follows: S101: By deploying sensor arrays at key nodes in industrial confined spaces, dust concentration monitoring data and gas concentration monitoring data characterizing the current environmental state are acquired. Combined with the three-dimensional position coordinate information of the sensor probe in the global coordinate system, the monitoring data and the three-dimensional position coordinate information are correlated to generate a discrete point monitoring data set containing discrete coordinate points and real-time concentration values. S102: Construct a spatial three-dimensional mesh model that adapts to the geometric boundary of the industrial confined space, traverse and analyze the geometric center coordinates of all mesh cells inside the model, perform Euclidean distance calculation for each sampling point in the discrete point monitoring data set, perform inverse weighted interpolation operation on the concentration data of each sampling point, map and fill the discretely distributed concentration values ​​into the spatial mesh cells, and establish a meshed concentration field matrix. S103: Extract the dust concentration and gas concentration values ​​recorded in each grid cell of the gridded concentration field matrix, perform weighted normalized combustion heat mapping calculation on the dust concentration monitoring data and gas concentration monitoring data, and generate comprehensive stoichiometric distribution data of the three-dimensional grid model covering the space and the corresponding mixed medium energy distribution state.

4. The dust and gas coupled explosion risk assessment method according to claim 3, characterized in that, The specific steps for obtaining the candidate risk connected component set are as follows: S201: Perform a numerical scan of each grid cell on the comprehensive stoichiometric distribution data to obtain the pre-set lower explosion limit critical value and upper explosion limit critical value of the mixed medium, and compare them with each grid cell in intervals. Filter the target grid cells whose values ​​are within the interval range and record the geometric index position to establish an active grid cell state matrix. S202: Call the active grid cell state matrix and set the three-dimensional spatial adjacency determination rules. Perform neighborhood search starting from any active grid cell, detect the active state of adjacent grid cells, merge spatially continuous and active grid cells into the same cluster, and generate a spatial adjacency connected component index. S203: Based on the spatial adjacency connected component index, extract the coordinate data of the grid cells contained in each cluster, reconstruct the grid cells belonging to the same cluster into independent three-dimensional entities, count the number of grid cells in each independent three-dimensional entity and calculate the geometric centroid position, and generate a set of candidate risk connected components.

5. The dust and gas coupled explosion risk assessment method according to claim 4, characterized in that, The process of obtaining the pre-set lower and upper critical values ​​for the explosion of the mixed medium, comparing them with each grid cell within a range, selecting target grid cells whose values ​​fall within the range, and recording their geometric index positions specifically includes: Obtain the standard pure phase lower explosive limit concentration and standard pure phase upper explosive limit concentration for the dust medium category corresponding to the current monitoring environment, and the standard pure phase lower explosive limit concentration and standard pure phase upper explosive limit concentration for the gas medium category; The mixed medium explosion limit coupling calculation logic is invoked. Based on the unit mass combustion heat parameter corresponding to the dust medium category and the unit volume combustion heat parameter corresponding to the gas medium category, the combustion heat contribution weight is calculated. According to the combustion heat contribution weight, a weighted coupling operation is performed on the standard pure phase lower explosion limit concentration value of the dust medium category and the standard pure phase lower explosion limit concentration value of the gas medium category to obtain the coupled lower explosion limit concentration and convert it into a dimensionless stoichiometric ratio value to generate the critical value of the lower explosion limit of the mixed medium. Using the aforementioned mixed-medium explosion limit coupling calculation logic, a weighted coupling operation and dimension conversion are performed on the standard pure-phase explosion limit concentration values ​​of the dust medium category and the standard pure-phase explosion limit concentration values ​​of the gas medium category to generate the critical value of the mixed-medium explosion limit. The comprehensive stoichiometry value of each grid cell in the comprehensive stoichiometry distribution data is read through it to construct an effective explosion threshold closed interval composed of the lower explosion limit critical value of the mixed medium and the upper explosion limit critical value of the mixed medium. The inclusion verification is performed between the comprehensive stoichiometric ratio value and the effective explosion threshold closed interval to determine whether the comprehensive stoichiometric ratio value is within the effective explosion threshold closed interval. Extract the mesh cells that pass the inclusion verification, mark them as the target mesh cells, and parse the three-dimensional axial position numbers of the target mesh cells in the coordinate system of the spatial three-dimensional mesh model, and combine them to generate the geometric index position.

6. The dust and gas coupled explosion risk assessment method according to claim 5, characterized in that, The specific steps for obtaining the maximum inscribed sphere diameter parameter are as follows: S301: Based on the set of candidate risk connected components, analyze the internal mesh topology of each independent three-dimensional clique, count the total number of mesh units constituting the clique and convert it into a solid space volume value in combination with the physical size of the mesh, identify the surface mesh units that are in direct contact with the external inactive area at the boundary of the clique and calculate the surface area value, and generate spatial morphological geometric attribute data. S302: Call the spatial morphology geometric attribute data and extract the internal grid coordinate information of the independent three-dimensional clumps. Perform Euclidean distance transformation operation relative to the closed geometric boundary of the clump for each internal grid cell. Calculate the shortest straight-line spatial distance from the geometric center of each grid to the nearest boundary surface. Store the shortest straight-line spatial distance as a depth value in the corresponding coordinate node and establish the internal space depth distance field matrix. S303: Perform global numerical retrieval and extreme value filtering operations on the internal space depth distance field matrix, locate the grid node with the largest stored distance value in the matrix, extract the largest distance value as the maximum inscribed radius of the geometric center of the cluster, perform diameter conversion based on geometric multiple on the maximum inscribed radius, determine the limit physical span of the core area, and generate the maximum inscribed sphere diameter parameter corresponding to the minimum core thickness of the cluster.

7. The dust and gas coupled explosion risk assessment method according to claim 6, characterized in that, The specific steps for obtaining the list of effective explosion source manifolds are as follows: S401: Based on the maximum inscribed sphere diameter parameter, a numerical comparison analysis is performed with the preset current mixed medium flame quenching distance parameter to determine whether the geometric scale of the core region of the agglomerate exceeds the minimum physical space limit required for free flame propagation. An allowed propagation index record is established for the agglomerates that have passed the determination, and a flame propagation geometric determination index is generated. S402: Call the connected domain volume parameter and the connected domain surface area parameter to calculate the body surface ratio value, obtain the preset thermal self-sustaining critical parameter, perform a numerical range comparison between the body surface ratio value and the thermal self-sustaining critical parameter, filter out the clumping objects whose body surface ratio value exceeds the critical requirement, and generate a heat accumulation judgment index. S403: Call the flame propagation geometric determination index and the heat accumulation determination index to perform dual condition verification on each independent three-dimensional mass, filter the mass index that simultaneously satisfies the geometric scale propagation condition and the thermodynamic energy accumulation condition, extract the corresponding spatial topology information and physical property data from the original dataset based on the retained index, and generate a list of valid explosion source manifolds.

8. The dust and gas coupled explosion risk assessment method according to claim 7, characterized in that, The specific steps for obtaining the explosion risk assessment level are as follows: S501: For the list of effective explosion source manifolds, extract the connected component volume parameters associated with each independent three-dimensional mass in the list, construct a sequence of risk source volume values ​​to be processed, and perform mathematical accumulation operation on each volume value in the sequence to generate a global cumulative explosion source volume value. S502: Call the global cumulative explosion source volume value, obtain the total volume parameter of the industrial confined space that has been pre-mapped and stored in the database, compare the obtained cumulative volume value with the total volume parameter of the industrial confined space, obtain the numerical ratio of the effective risk source volume to the total volume, and generate the risk volume ratio parameter. S503: Based on the risk volume ratio parameter, obtain the preset multi-level risk classification alarm interval parameter, match and determine the risk volume ratio parameter with the multi-level risk classification alarm interval parameter, filter the target interval containing the current ratio parameter, perform state mapping according to the preset safety level definition associated with the target interval, and generate the explosion risk assessment level.

9. A dust-gas coupled explosion risk assessment terminal, said terminal being used to implement the dust-gas coupled explosion risk assessment method according to any one of claims 1-8, characterized in that, The terminal includes: The coupled data mapping module collects dust concentration monitoring data and gas concentration monitoring data and maps them to a three-dimensional spatial grid model. Based on the combustion heat parameters, it performs a weighted normalized combustion heat mapping operation on the dust concentration monitoring data and gas concentration monitoring data to generate comprehensive stoichiometric ratio distribution data. The regional connectivity clustering module, for the comprehensive stoichiometric ratio distribution data, filters active grid cells whose values ​​are within the preset explosion limit range parameters, performs connectivity analysis on the active grid cells, connects and merges them into independent objects, and generates a set of candidate risk connected domains. The morphological feature analysis module analyzes the connected domain volume parameters and connected domain surface area parameters of each three-dimensional clumping in the candidate risk connected domain set, extracts the internal skeleton and calculates the depth distance field for independent three-dimensional clumping, and outputs the maximum inscribed sphere diameter parameter of the minimum core thickness of the corresponding clumping. The source term validity filtering module compares the maximum inscribed sphere diameter parameter with the preset current mixed medium flame quenching distance parameter, and simultaneously calculates the volume-to-surface ratio of the connected domain volume parameter and the connected domain surface area parameter and verifies it with the thermal self-sustaining critical parameter. It then filters out independent three-dimensional clumps that meet the propagation and accumulation conditions and generates a list of effective explosion source manifolds. The global risk assessment module accumulates the connected domain volume parameters of each independent three-dimensional block in the list of effective explosion source manifolds, compares them with the total volume parameters of industrial confined spaces, calculates the risk volume ratio parameter, matches and determines it with the multi-level risk classification alarm interval parameters, and outputs the explosion risk assessment level.

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