Chemical safety emergency dispatching command method and device

Abstract

The invention provides a chemical safety emergency dispatching command method and device, and belongs to the technical field of chemical safety emergencies, and the method comprises the steps: obtaining the operation state information of chemical production equipment and the real-time information of an emergency resource point; determining hidden danger factors of different position nodes in the chemical production network according to the operation state information, and further determining corresponding emergency resource types; modeling the chemical production network into a weighted graph; the hidden danger nodes are used as starting points, corresponding emergency resource types are used as constraints, layer-by-layer outward expansion is carried out according to network levels, bidirectional search is carried out from the hidden danger nodes and resource nodes, and edge weights are dynamically updated; determining response time according to the edge weight, optimizing the resource matching degree, the response time and the resource quantity as a multi-objective function, and generating an optimal path set; and performing scheduling command based on the optimal path set. Therefore, emergency resources can be ensured to arrive at an accident site at the fastest speed, and reasonable distribution and efficient utilization of the emergency resources are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of chemical safety emergency response, and in particular relates to a chemical safety emergency dispatch command method and device. Background Art

[0002] With the rapid development of the energy and chemical industries, the scale of chemical production continues to expand, increasing the complexity and risk of production processes. Chemical production involves flammable, explosive, toxic, and hazardous chemicals. Accidents pose serious risks to life, property, and the environment. Traditional chemical safety management relies primarily on manual inspections and empirical judgment, resulting in inefficiency, delayed response, and poor information sharing. This makes it difficult to meet the stringent safety and emergency response requirements of modern chemical production.

[0003] While existing chemical safety emergency management systems have achieved a certain degree of success in monitoring production processes and responding to emergencies, they still have numerous shortcomings. For example, some systems are inadequate in emergency resource management, making it difficult to rapidly deploy resources and optimize routes. This leads to cumbersome emergency response processes and difficulties in coordination, hindering the efficiency and effectiveness of emergency response. Summary of the Invention

[0004] In order to solve the problem of low resource allocation efficiency in chemical safety emergency management, the present invention provides a chemical safety emergency dispatch command method and system.

[0005] A chemical safety emergency dispatch command method, the method comprising: Acquire operating status information of chemical production equipment and real-time information of emergency resource points; construct a chemical production network based on the operating status information and real-time information, wherein the chemical production network is a spatial network formed by connecting the locations of chemical production equipment and emergency resource points, and each node of the spatial network is the location of chemical production equipment or emergency resource points, including hidden danger nodes and resource nodes; the hidden danger nodes are nodes where chemical production equipment with hidden danger factors in operating status information is located, and the resource nodes are nodes where emergency resource points are located; A weighted graph is constructed based on the chemical production network. The nodes of the weighted graph include potential danger nodes and resource nodes, and the edge weights represent resource availability. Taking any potential danger node as the initial starting point, the required resource type is determined based on the potential danger factor of the potential danger node. The resource type is used as a constraint to preferentially search for resource nodes among adjacent nodes. If the resources are matched and available, a scheduling path is directly generated and the edge weights are updated. Otherwise, the graph expands outward layer by layer according to the node hierarchy, while simultaneously searching from both potential danger nodes and resource nodes. Optimize response time and resource quantity as a multi-objective function to generate the optimal path set; Perform dispatching and command based on the optimal path set.

[0006] Optionally, the hidden danger factor is determined through the operating status information, including: Obtaining historical operating data of the chemical production equipment and its corresponding hidden danger factors, and training a pre-built algorithm model using the historical operating data and its corresponding hidden danger factors to obtain a hidden danger factor prediction model; the pre-built algorithm model includes a convolutional neural network; The operating status information is input into a hidden danger factor prediction model to obtain the hidden danger factors and corresponding weights of nodes at different locations; the hidden danger factors include equipment aging, parameter abnormalities and environmental risks.

[0007] Optionally, after constructing the weighted graph, the method further includes: According to the hidden danger type and resource requirements, the matching emergency strategy is selected from the preset strategy library, and the core resource types that the emergency strategy depends on are marked; Resource nodes are searched based on the core resource type.

[0008] Optionally, the performing scheduling and command based on the optimal path set includes: The optimal path set is verified through real-time simulation, and the real-time status and resource consumption of the equipment are monitored during the emergency response process. The real-time simulation software includes MATLAB simulation software driven by the Dijkstra algorithm. The input includes the node location of each node, the type of hidden danger factor, the type of resource required to resolve the hidden danger factor, and the real-time information of each resource node. The output includes a quantitative index of path length. Dynamically adjust emergency strategies based on the real-time status and resource consumption; After the emergency response is completed, the emergency strategy is optimized based on the accident assessment results.

[0009] Optionally, updating edge weights includes: After determining the path, immediately mark the resource as "occupied" to avoid multi-tasking conflicts; When multiple hidden danger factors compete for the same resource, the priority is determined based on the hidden danger risk level and path time, and the edge weight is updated based on the priority.

[0010] A chemical safety emergency dispatch command device, comprising: An acquisition module is configured to acquire operating status information of chemical production equipment and real-time information of emergency resource points; construct a chemical production network based on the operating status information and real-time information, wherein the chemical production network is a spatial network formed by connecting the locations of chemical production equipment and emergency resource points, wherein each node of the spatial network is a location of chemical production equipment or emergency resource points, including a hidden danger node and a resource node; the hidden danger node is a node where chemical production equipment having a hidden danger factor in its operating status information is located, and the resource node is a node where an emergency resource point is located; A construction module is used to construct a weighted graph based on the chemical production network. The nodes of the weighted graph include potential danger nodes and resource nodes, and the edge weights represent resource availability. Taking any potential danger node as the initial starting point, the required resource type is determined based on the potential danger factor of the potential danger node. The resource type is used as a constraint to preferentially search for resource nodes among adjacent nodes. If the resources are matched and available, a scheduling path is directly generated and the edge weights are updated. Otherwise, the graph expands outward layer by layer according to the node hierarchy, and a bidirectional search is simultaneously conducted from potential danger nodes and resource nodes. The optimization module is used to optimize the response time and resource quantity as a multi-objective function to generate the optimal path set; The execution module is used to perform scheduling and command based on the optimal path set.

[0011] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned chemical safety emergency dispatch and command method.

[0012] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned chemical safety emergency dispatch and command method is implemented.

[0013] The chemical safety emergency dispatch command method provided by the present invention has the following beneficial effects: First, determine the location of the hidden danger factors and the corresponding emergency resource types. Accurately locating the hidden danger factors and required resources will help reduce blind searches and ineffective responses, thereby improving the pertinence and efficiency of resource allocation. Secondly, the chemical production network is modeled as a weighted graph, which provides a basis for calculating the shortest path. By expanding outward layer by layer through the network hierarchy and searching bidirectionally from hidden danger nodes and resource nodes, the system can dynamically update the resource path to determine the optimal emergency resource allocation path. This optimized resource allocation method can ensure that emergency resources arrive at the accident site at the fastest speed and shortest path, thereby improving resource utilization efficiency. Moreover, it optimizes with resource matching, response time and resource quantity as the goals, taking into account not only the quantity of resources, but also factors such as resource type, location, response time, etc. This comprehensive consideration can ensure the rational allocation and efficient utilization of emergency resources, thereby improving the emergency efficiency of the entire chemical production network. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] To more clearly illustrate the embodiments of the present invention and its design, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0015] Figure 1 The present invention provides a flow chart of a chemical safety emergency dispatch and command method according to an exemplary embodiment.

[0016] Figure 2 The present invention provides a block diagram of a chemical safety emergency dispatch command device according to an exemplary embodiment. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solution of the present invention and to be able to implement it, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention.

[0018] The present invention discloses a chemical safety emergency dispatch command system and a dispatch method, which relate to the field of chemical safety emergency technology. The system constructs an energy chemical emergency command and dispatch system, and divides it into several submodules, including emergency plans, emergency resource management, emergency duty management, emergency response management, information release, and emergency drills. Based on the sensor data of the production equipment, the production status of the equipment is displayed in real time on the map. Based on the status of the sensor monitoring point, the hidden danger factors of the nodes at different positions in the chemical production network are determined, and the dispatch command strategy called in the reference dispatch command strategy set is determined. According to the available resources, the dispatch command strategy is arranged and commanded through the dispatch algorithm. Through the above technical solution, the present invention realizes the timely determination of efficient and accurate dispatch command strategies, improves the efficiency of solving abnormal hidden danger problems in chemical production, and ensures the safety and stability of chemical production.

[0019] The technical solutions provided by various embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0020] First, the present invention provides a chemical safety emergency dispatch command method, specifically as follows Figure 1 As shown, the following steps are included: S101. Obtain operating status information of chemical production equipment and real-time information of emergency resource points.

[0021] In this step, sensor data of chemical production equipment and real-time information (location, resource type, available quantity) such as resource storage status of various emergency resource points (such as fire stations and material warehouses) can be collected in real time. The operating parameters and status information of chemical production equipment, such as temperature, pressure, flow, vibration and other data, can be obtained to provide the system with accurate equipment production status information.

[0022] S102: Construct a chemical production network based on the operation status information and real-time information.

[0023] Among them, the chemical production network is a spatial network formed by connecting the locations of chemical production equipment and emergency resource points. Each node of the spatial network is the location of chemical production equipment or emergency resource points, including equipment nodes and resource nodes. The equipment nodes include normal nodes and hidden danger nodes. The normal node is the node where the chemical production equipment whose operating status information does not contain hidden danger factors is located. The hidden danger node is the node where the chemical production equipment whose operating status information contains hidden danger factors is located. The resource node is the node where the emergency resource point is located. In addition, the network in the chemical production network is not a network model and does not have input and output. It is only connected based on the location of each equipment or material in chemical production to form a spatial network. On this spatial network, each connection node is the location of the equipment or material, and the status information of the equipment operation or the real-time information or status information of the material is marked on each node.

[0024] As for the hidden danger factors, they need to be determined in this step based on the operating status information of the chemical production equipment.

[0025] Specifically, the hidden danger factors of each location node can be predicted through machine learning, and the hidden danger factors of different location nodes in the chemical production network can be analyzed and determined based on the operating status information and historical data of chemical production equipment at each location node monitored by sensors.

[0026] For example, historical operating data and corresponding hidden danger factors of the chemical production equipment are obtained. A pre-built algorithm model is trained using this historical operating data and its corresponding hidden danger factors to generate a hidden danger factor prediction model. The operating status information is then input into the hidden danger factor prediction model to output hidden danger factors and corresponding weights for different nodes at different locations. The hidden danger factors represent possible failures or accidents, including different hidden danger types such as equipment aging, gas leaks, parameter anomalies, and environmental risks. Required emergency resources, such as fire extinguishing agents or leak-proofing equipment, are then determined based on the hidden danger factors. The hidden danger factors corresponding to the historical operating data are historical hidden danger factors. The present invention uses these historical hidden danger factors for algorithm model training and can be directly obtained from historical records. For example, if the equipment has experienced a fire, historical operating data from before the fire is obtained, and the hidden danger factor corresponding to this historical operating data is fire. Alternatively, if part 1 of the equipment has experienced damage, historical operating data from before the damage is obtained, and the hidden danger factor corresponding to this historical operating data is damage to part 1.

[0027] In addition, the pre-built algorithm model can be any machine learning algorithm model that can be used for device operation feature recognition, such as random forest RF, convolutional neural network CNN, support vector machine SVM, long short-term memory network LSTM, and gradient boosting decision tree, etc. Any conventional model can be used, and the present invention does not limit this.

[0028] Furthermore, to enable timely response to risks, a pre-configured dispatch and command strategy library can be used. Based on the potential risk factors and emergency response requirements, a matching emergency strategy is called from the pre-configured strategy library, which integrates emergency response plans for various accident types, production stages, and resource conditions.

[0029] S103. Construct a weighted graph based on the chemical production network, and perform resource search with any potential danger node as the initial starting point.

[0030] Specifically, a weighted graph is constructed based on the chemical production network. The nodes of the weighted graph include hidden danger nodes and resource nodes, and the edge weights represent the resource availability. Taking any hidden danger node as the initial starting point, the required resource type is determined according to the hidden danger factor of the hidden danger node. The resource type is used as a constraint, and resource nodes in adjacent nodes are searched first. When the resources are matched and available, the scheduling path is directly generated and the edge weights are updated. In other cases, the graph expands outward layer by layer according to the node hierarchy, and searches in both directions from the hidden danger nodes and resource nodes.

[0031] In this step, graph theory methods and resource optimization techniques are used to find the shortest path and optimize resource allocation.

[0032] For example, the first step is to construct a weighted graph. Starting with the node where the potential risk factor is located as the starting vertex, a node graph is constructed by combining the remaining nodes in the chemical production network (such as equipment, warehouses, and emergency exits). This node graph is an abstract representation, where each node represents a location in the network, and the connections (edges) between nodes represent relationships between these locations (such as physical connections, communication connections, or functional associations). Each edge is weighted, and the edge weight represents resource availability.

[0033] Using any vulnerable node as the starting vertex, we construct an adjacency matrix based on the node graph. An adjacency matrix is a mathematical representation that describes the connections between nodes in a graph. In this matrix, rows and columns correspond to nodes in the graph, and the elements represent the availability of resources between nodes (e.g., 1 for available, 0 for unavailable).

[0034] With the starting vertex as the center, it expands outwards layer by layer to the surrounding nodes, and updates the edge weights based on the connected nodes, and continues to expand to the peripheral nodes with the connected nodes as the center. The following steps can be used to update the edge weights: immediately mark the resource as "occupied" after determining the path to avoid multi-task conflicts; when multiple hidden danger factors compete for the same resource, determine the priority based on the hidden danger risk level and path time, and update the edge weights based on the priority. For example, the edge weights can be weighted according to priority. When multiple hidden danger factors compete for the same resource, resources can be allocated according to the weight ratio, or when the weight difference is greater than a preset difference, the low-weight factor will transfer resources to the high-weight factor.

[0035] After constructing the weighted graph in this step, matching emergency strategies are selected from the preset strategy library based on the hidden danger type and resource requirements, and the core resource types that the emergency strategies depend on are marked. Then, the second step is executed to search for resource nodes based on the core resource types and calculate the shortest path.

[0036] The second step is to calculate the shortest path. Using the graph theory shortest path algorithm, we iteratively calculate the shortest paths from the starting vertex to all other nodes in the graph based on the adjacency matrix. This process dynamically updates the shortest path length (i.e., the minimum cost / distance to reach that vertex) and the number of predecessor neighbors (i.e., the number of nodes preceding that vertex on the shortest path) for each adjacent vertex.

[0037] In this step, the improved Dijkstra scheduling algorithm combined with available emergency resources can be used to optimize and arrange the scheduling and command strategy to generate a specific emergency scheduling and command plan.

[0038] The steps of the Dijkstra scheduling algorithm are as follows: 1. When calculating the shortest path in graph G, using the Dijkstra algorithm, you must first set a starting vertex A, that is, start the path calculation from vertex A.

[0039] 2. Introduce two auxiliary arrays, S and U. Array S is used to store the vertices for which the shortest path has been determined and their corresponding shortest path lengths; array U records the vertices for which the shortest path has not yet been determined and their distances from the starting vertex A.

[0040] 3. Initialize array S to contain only the starting vertex A. Array U contains all vertices except A and records the distance from each vertex to A. If a vertex is not adjacent to A, the distance is set to infinity. Number all vertices and construct an adjacency matrix. Assign a fixed number (n) to the starting point A, leaving the remaining vertices unnumbered. Compute the shortest path from starting point A to its adjacent vertices, recording the number of adjacent vertices.

[0041] 4. Find the next fixed-number vertex (n): Use the adjacency matrix to find the vertex v that has not yet been fixed-numbered and has the shortest path length. If the shortest path length to vertex v is infinite, the algorithm terminates; otherwise, vertex v is set to the fixed-number (n).

[0042] 5. Using vertex v and the adjacency matrix, calculate the shortest path length from vertex v to adjacent point x and the number of its predecessors. If the path length from starting point A through vertex v to adjacent point x is less than the currently recorded shortest path length for x, update the shortest path length for vertex x to the path length from A through v to x.

[0043] 6. Continue to search for the next vertex with a fixed label (n label). If all vertices have obtained fixed labels, the algorithm ends; otherwise, return to step 4.

[0044] 7. Repeat the above steps until all vertices in graph G are traversed and the shortest path calculation is completed.

[0045] The third step involves optimizing resource allocation. By introducing the types of available emergency resources as constraints, the path calculation logic from the second step is optimized, prioritizing dispatch paths with the shortest response times and highest resource utilization. Combining the available emergency resources in the chemical production network (such as rescue teams, firefighting equipment, and emergency supplies), the emergency dispatch and command strategy is optimized based on the calculated shortest paths and node priorities (which may be determined by the severity of the potential risk). This involves determining which resources should be allocated to which locations to ensure a swift and effective response and mitigate the impact of potential risks in emergencies.

[0046] S104: Optimize the response time and the number of resources as a multi-objective function to generate an optimal path set.

[0047] For example, a decision-making system consisting of three core indicators was first established: Resource compatibility: This quantifies the degree of resource type matching. A perfect match is assigned a score of 1, an alternative (e.g., replacing foam with dry powder) is assigned a score of 0.5, and no match is assigned a score of 0. Response time: This is calculated as vehicle travel time using the formula (distance of the road section / average speed of 60 km / h) × real-time congestion coefficient. Resource adequacy: This is the resource reserve divided by the demand at the potential risk point. A value exceeding 100% indicates excess supply.

[0048] Secondly, rigid constraints are set: the path must be connected by actual road sections; the amount of resource calls for a single dispatch must not exceed the node inventory; and the total response time must not exceed the 30-minute threshold.

[0049] The improved NSGA-II algorithm was then used for multi-objective optimization. Population initialization randomly generated 200 feasible paths, ensuring that each path connected the potential risk point and the resource point. Genetic evolution operations included crossover: randomly selecting two parent paths and exchanging intermediate nodes to generate a new path. Mutation: randomly replacing a node in a path with a 10% probability. Selection: retaining 100 elite individuals and generating 200 offspring individuals. Iterative optimization: performing 50 generations of evolution, evaluating the three objective function values of individuals in each generation. Optimal solution screening: outputting a Pareto optimal solution set, including: Option A: fully matching resources, arriving in 18 minutes, and a resource sufficiency rate of 160%; Option B: fully matching resources, arriving in 22 minutes, and a resource sufficiency rate of 60%; Option C: using alternative resources, arriving in 16 minutes, and a resource sufficiency rate of 200%.

[0050] For example, when multiple potential hazards compete for the same resources, priority decisions are made. Risk scoring: The risk level (1-5) is calculated based on the hazard type (leakage / fire / explosion), population density within the impact radius, and environmental sensitivity. Resource allocation prioritizes high-risk hazards and initiates alternative solutions for medium- and low-risk sites, including but not limited to: directing the use of alternative resource types, coordinating resource adjustments in surrounding areas, and triggering emergency procurement processes. Finally, real-time updates: Resource inventory status is refreshed every 5 minutes, dynamically adjusting deployed solutions.

[0051] S105: Perform dispatching and command based on the optimal path set.

[0052] Implement emergency dispatch and command plans, including launching emergency plans, deploying emergency resources, issuing early warning information, and organizing emergency responses.

[0053] For example, to prevent unexpected events during an actual emergency response, it's necessary to verify the optimal path set through real-time simulation. During the emergency response, the real-time status and resource consumption of the equipment are monitored. Based on this real-time status and resource consumption, the emergency strategy is dynamically adjusted. For example, if a resource node is depleted, a new resource node with the required resources is immediately searched for. After the emergency is over, the emergency strategy is optimized based on the accident assessment results. For example, after determining the path, the resource is immediately marked as "occupied" to avoid multi-task conflicts. When multiple hidden danger factors compete for the same resource, priority scheduling is performed based on the hidden danger risk level and path duration, triggering a dynamic resource reallocation mechanism. This allows for real-time monitoring and dynamic adjustment of the simulation process to ensure the efficiency and effectiveness of emergency response. This process is then evaluated and improved upon, providing experience for actual emergency dispatch and command.

[0054] Among them, the simulation software used for simulation can be any existing path or traffic flow simulation software, for example, TESS NG intelligent highway simulation platform, Paramics microscopic traffic flow simulation software, Pathfinder intelligent body evacuation simulation and Dijkstra algorithm driven MATLAB simulation, etc.; the input includes the node position of each node (including the position of the hidden danger node), the type of hidden danger factor and the type of resources required to solve the hidden danger factor and the real-time information of each resource node (resource availability); the output includes one or more results such as emergency time, efficiency evaluation, congestion point analysis and multiple path comparison analysis. The input and output can be adjusted according to the specific circumstances of different simulation software, and the present invention does not limit this.

[0055] In addition, during the emergency response process, execution and coordinated command can be as follows: Multi-terminal command distribution: push navigation paths and operation instructions to emergency vehicles and personnel terminals, and simultaneously notify surrounding nodes to initiate linkage plans (such as evacuation alerts).

[0056] Process monitoring and backtracking: Track resource transportation status through IoT devices, automatically trigger alternative plans when abnormal situations occur, and record data for iterative optimization of the strategy library.

[0057] Using the above method, we first determine the location of the hidden danger factor and the corresponding emergency resource type. This precise positioning of the hidden danger factor and the required resources helps reduce blind searches and ineffective responses, thereby improving the pertinence and efficiency of resource allocation. Secondly, the chemical production network is modeled as a weighted graph, which provides a basis for calculating the shortest path. By expanding outward layer by layer through the network hierarchy and searching bidirectionally from hidden danger nodes and resource nodes, the system can dynamically update the resource path to determine the optimal emergency resource allocation path. This optimized resource allocation method can ensure that emergency resources arrive at the accident site at the fastest speed and shortest path, thereby improving resource utilization efficiency. Moreover, it optimizes with resource matching, response time and resource quantity as the goals, taking into account not only the quantity of resources, but also factors such as resource type, location, and response time. This comprehensive consideration can ensure the rational allocation and efficient utilization of emergency resources, thereby improving the emergency efficiency of the entire chemical production network.

[0058] Secondly, the present invention also provides a chemical safety emergency dispatch command device, such as Figure 2 Shown, including: Acquisition module 201 is used to obtain the operating status information of chemical production equipment and the real-time information of emergency resource points; a chemical production network is constructed based on the operating status information and real-time information. The chemical production network is a spatial network formed by connecting the locations of chemical production equipment and emergency resource points. Each node of the spatial network is the location of chemical production equipment or emergency resource points, including hidden danger nodes and resource nodes; the hidden danger node is the node where the chemical production equipment with hidden danger factors in the operating status information is located, and the resource node is the node where the emergency resource point is located.

[0059] Construction module 202 is used to construct a weighted graph based on the chemical production network. The nodes of the weighted graph include hidden danger nodes and resource nodes, and the edge weights represent the resource availability; taking any hidden danger node as the initial starting point, the required resource type is determined according to the hidden danger factor of the hidden danger node, and the resource type is used as a constraint to preferentially search for resource nodes in adjacent nodes. When the resources are matched and available, the scheduling path is directly generated and the edge weights are updated; in other cases, it is expanded outward layer by layer according to the node hierarchy, and a two-way search is simultaneously performed from the hidden danger node and the resource node.

[0060] The optimization module 203 is configured to optimize the response time and the number of resources as a multi-objective function to generate an optimal path set.

[0061] The execution module 204 is used to perform scheduling and command based on the optimal path set.

[0062] Using the above-mentioned device, the location of the hidden danger factor and the corresponding emergency resource type are first determined. This precise positioning of the hidden danger factor and the required resources helps to reduce blind searches and invalid responses, thereby improving the pertinence and efficiency of resource allocation; secondly, the chemical production network is modeled as a weighted graph, which provides a basis for calculating the shortest path. By expanding outward layer by layer through the network hierarchy and searching in both directions from the hidden danger node and the resource node, the system can dynamically update the resource path to determine the optimal emergency resource allocation path. This optimized resource allocation method can ensure that emergency resources arrive at the accident site at the fastest speed and shortest path, thereby improving resource utilization efficiency. Moreover, it optimizes with resource matching, response time and resource quantity as the goals, taking into account not only the quantity of resources, but also factors such as the type, location, and response time of resources. This comprehensive consideration can ensure the rational allocation and efficient utilization of emergency resources, thereby improving the emergency efficiency of the entire chemical production network.

[0063] In a specific embodiment, based on the above device, the present invention also provides an implementation system.

[0064] This invention aims to provide an efficient and reliable chemical safety emergency dispatch and command system and method to ensure comprehensive implementation of enterprise emergency management systems and efficient response to emergencies. By collecting, analyzing, and processing various types of information related to emergencies in real time, the system accurately grasps the development trends of events, thereby providing enterprises with scientific and effective emergency response plans and supporting decision-making information. The system deeply integrates production management with emergency management, enabling data visualization and the integration of multimedia voice dispatch and emergency command, creating a highly reliable production emergency command platform.

[0065] The present invention follows the design concept of combining peacetime and wartime, and centered around the production emergency command system, carefully builds a chemical safety emergency dispatch and command system that includes core functional modules such as emergency dispatch, visual command, and collaborative consultation, ensuring that efficient command can be achieved in an emergency state with "connectivity, visibility, and responsiveness." The system can proactively push key information such as emergency resources, hazardous sources, and environmentally sensitive points, and monitor on-site dynamics in real time and accurately with the help of video surveillance and various detection equipment at the emergency site. At the same time, the system also has the ability to automatically associate similar accident case processing procedures in the accident case library, providing emergency command personnel with a scientific and reliable reference basis, thereby ensuring the scientific nature and effectiveness of emergency response measures, minimizing the losses caused by emergencies to enterprise production, and ensuring the safe production and stable operation of the enterprise. The system specifically includes:

[0066] Production equipment sensor data acquisition module: used to collect real-time operating parameters and status information of chemical production equipment, such as temperature, pressure, flow, vibration and other data, to provide the system with accurate equipment production status information.

[0067] Hidden danger factor analysis module: Based on the status of sensor monitoring points and historical data, using data analysis and machine learning algorithms, it determines the hidden danger factors of nodes at different locations in the chemical production network, such as equipment aging, parameter abnormalities, environmental risks, etc., providing a basis for emergency dispatch and command.

[0068] Dispatch and command strategy library: Integrates multiple emergency dispatch and command strategies, covering emergency response plans for different accident types, different production stages, and different resource conditions, for system call and execution.

[0069] Scheduling algorithm module: Based on available resources and emergency response requirements, it uses optimization algorithms to intelligently optimize and arrange scheduling and command strategies to achieve rational allocation of resources and efficient execution of emergency response.

[0070] Emergency plan management module: realizes digital and structured management of emergency plans, including functions such as plan preparation, review, release, update and drill, to ensure the scientific nature and practicality of emergency plans.

[0071] Emergency resource management module: unified management of emergency materials, emergency teams, emergency equipment and other resources, including registration, classification, storage, allocation and maintenance of resources, to achieve visual display and dynamic update of resources.

[0072] Emergency duty management module: responsible for the scheduling, handover, duty log recording and other tasks of emergency duty personnel to ensure the orderly implementation of emergency duty work.

[0073] Emergency response management module: includes functions such as accident analysis, rescue deployment generation, visual communication dispatch command, and dynamic tracking of rescue execution, to achieve management and control of the entire emergency response process.

[0074] Information release module: responsible for the release of enterprise comprehensive information, early warning information, and dispatch command information, and delivers information to relevant personnel and departments in a timely and accurate manner through multiple channels such as emergency broadcasts, text messages, and electronic display screens.

[0075] Emergency drill management module: supports the formulation, execution, recording and summary of emergency drill plans, and improves emergency response capabilities and the operability of plans through simulation drills.

[0076] In this way, based on the above system, the present invention can complete efficient, intelligent and integrated chemical safety emergency dispatch, can monitor various risk factors in the chemical production process in real time, quickly and accurately formulate and implement emergency dispatch command strategies, improve the safety and stability of chemical production, and reduce the probability and losses of accidents.

[0077] The above-mentioned system monitors the production process and provides emergency dispatch and command. The specific process involves: The system first uses the production equipment sensor data acquisition module to collect real-time operating parameters from various production equipment within the enterprise, such as reactor temperature and pressure, and tank liquid level and flow rate. The hazard factor analysis module, based on this collected data and historical data, applies a data analysis algorithm to detect an abnormal increase in reactor temperature, indicating an overheating risk, and identifies the reactor's hazard factor. The system then calls an emergency dispatch and command strategy from the dispatch and command strategy library for overheating incidents, including measures such as lowering reactor temperature, stopping feed, and activating the cooling system. The dispatch algorithm module optimizes the dispatch and command strategy based on available emergency resources, such as cooling water supply, backup cooling equipment, and emergency supplies, generating a specific emergency dispatch and command plan. The system executes this plan and, through the emergency response management module, activates the emergency plan, notifies relevant personnel and departments, deploys emergency resources, issues warnings, and organizes the emergency response. During the emergency response process, the system monitors reactor temperature changes and the implementation of emergency measures in real time, dynamically adjusting the emergency dispatch and command plan to ensure efficient and effective emergency response. After the emergency is over, the system will evaluate and summarize the accident, record the cause of the accident, the emergency response process, resource consumption and other information, improve the emergency plan and dispatch command strategy library, and provide experience reference for future emergency dispatch command.

[0078] Enterprises formulate emergency drill plans based on actual production conditions and emergency plan requirements, including drill time, location, participating departments, drill theme and other information. The drill plan management module creates, edits, deletes, queries and views drill plans, and manages historical plans. During the execution of the drill, the drill process recording module records drill time, location, commander-in-chief, participating departments, drill name, effect evaluation, reviewers and other information. After the drill, the drill summary management module logs, edits, deletes, queries, and views the drill evaluation summary results, achieving unified management of the drill evaluation summary results. Through simulation drills, enterprises have improved their emergency response capabilities and the operability of their plans, and accumulated valuable experience for actual emergency response.

[0079] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 Provides steps for chemical safety emergency dispatch command method.

[0080] The present invention also provides a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 Provides steps for chemical safety emergency dispatch command method.

[0081] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0082] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0083] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0085] It should be noted that the above specific embodiments can enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although this specification has described the present invention in detail, those skilled in the art should understand that the present invention can still be modified or replaced with equivalents; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are included in the scope of protection of the patent for the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. A chemical safety emergency dispatch command method, characterized in that: The method comprises: Acquire operating status information of chemical production equipment and real-time information of emergency resource points; construct a chemical production network based on the operating status information and real-time information, wherein the chemical production network is a spatial network formed by connecting the locations of chemical production equipment and emergency resource points, and each node of the spatial network is the location of chemical production equipment or emergency resource points, including hidden danger nodes and resource nodes; the hidden danger nodes are nodes where chemical production equipment with hidden danger factors in operating status information is located, and the resource nodes are nodes where emergency resource points are located; A weighted graph is constructed based on the chemical production network. The nodes of the weighted graph include potential danger nodes and resource nodes, and the edge weights represent resource availability. Taking any potential danger node as the initial starting point, the required resource type is determined based on the potential danger factor of the potential danger node. The resource type is used as a constraint to preferentially search for resource nodes among adjacent nodes. If the resources are matched and available, a scheduling path is directly generated and the edge weights are updated. Otherwise, the graph expands outward layer by layer according to the node hierarchy, while simultaneously searching from both potential danger nodes and resource nodes. Optimize response time and resource quantity as a multi-objective function to generate the optimal path set; Perform dispatching and command based on the optimal path set.

2. The method according to claim 1, characterized in that Determine potential hazards through operational status information, including: Obtaining historical operating data of the chemical production equipment and its corresponding hidden danger factors, and training a pre-built algorithm model using the historical operating data and its corresponding hidden danger factors to obtain a hidden danger factor prediction model; the pre-built algorithm model includes a convolutional neural network; The operating status information is input into a hidden danger factor prediction model to obtain the hidden danger factors and corresponding weights of nodes at different locations; the hidden danger factors include equipment aging, parameter abnormalities and environmental risks.

3. The method according to claim 1, characterized in that After constructing the weighted graph, the method further includes: According to the hidden danger type and resource requirements, the matching emergency strategy is selected from the preset strategy library, and the core resource types that the emergency strategy depends on are marked; Resource nodes are searched based on the core resource type.

4. The method according to claim 3, characterized in that The dispatching and commanding based on the optimal path set includes: The optimal path set is verified through real-time simulation, and the real-time status and resource consumption of the equipment are monitored during the emergency response process. The real-time simulation software includes MATLAB simulation software driven by the Dijkstra algorithm. The input includes the node location of each node, the type of hidden danger factor, the type of resource required to resolve the hidden danger factor, and the real-time information of each resource node. The output includes a quantitative index of path length. Dynamically adjust emergency strategies based on the real-time status and resource consumption; After the emergency response is completed, the emergency strategy is optimized based on the accident assessment results.

5. The method according to claim 1, wherein The updating of edge weights includes: Mark the resource as "occupied" immediately after determining the path; When multiple hidden danger factors compete for the same resource, the priority is determined based on the hidden danger risk level and path time, and the edge weight is updated based on the priority.

6. A chemical safety emergency dispatch command device, characterized in that: The device comprises: An acquisition module is configured to acquire operating status information of chemical production equipment and real-time information of emergency resource points; construct a chemical production network based on the operating status information and real-time information, wherein the chemical production network is a spatial network formed by connecting the locations of chemical production equipment and emergency resource points, wherein each node of the spatial network is a location of chemical production equipment or emergency resource points, including a hidden danger node and a resource node; the hidden danger node is a node where chemical production equipment having a hidden danger factor in its operating status information is located, and the resource node is a node where an emergency resource point is located; A construction module is used to construct a weighted graph based on the chemical production network. The nodes of the weighted graph include potential danger nodes and resource nodes, and the edge weights represent resource availability. Taking any potential danger node as the initial starting point, the required resource type is determined based on the potential danger factor of the potential danger node. The resource type is used as a constraint to preferentially search for resource nodes among adjacent nodes. If the resources are matched and available, a scheduling path is directly generated and the edge weights are updated. Otherwise, the graph expands outward layer by layer according to the node hierarchy, and a bidirectional search is simultaneously conducted from potential danger nodes and resource nodes. The optimization module is used to optimize the response time and resource quantity as a multi-objective function to generate the optimal path set; The execution module is used to perform scheduling and command based on the optimal path set.

7. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

8. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 5 when executing the program.

Images