Train emergency decision information generation method, device, equipment and medium

Abstract

The invention discloses a train emergency decision information generation method and device, equipment and a medium. The method comprises the following steps: acquiring event state data associated with an emergency of a train running in real time, wherein the event state data comprises at least one parameter item and a parameter value of each parameter item; according to each parameter item in the event state data and the parameter value of each parameter item, monitoring whether the train has an emergency; under the condition that it is determined that the train has the emergency event, the event type of the emergency event is obtained, and a target item corresponding to the emergency event is obtained from the parameter items; obtaining an influence type of the target item; and determining train emergency decision information of the train according to the event type and the influence type of the target item. According to the technical scheme of the embodiment of the invention, the accuracy and efficiency of train emergency decision information generation under emergencies can be improved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, equipment and medium for generating emergency decision-making information for trains. Background Technology

[0002] With the development of technology, the types and numbers of rail vehicles are increasing, and their operation greatly meets people's daily travel needs. However, due to the special nature of rail vehicle operation, in the event of an emergency, it is necessary to obtain emergency decision-making information in a timely manner and handle the train according to that information.

[0003] Currently, after obtaining train operation information corresponding to a train emergency, the system manually analyzes the train emergency according to the order in which the train operation information is received, formulates emergency decision information for each train emergency, and processes the emergency decision information in the order in which it is formulated.

[0004] However, simply formulating and maintaining emergency decision-making information for trains based on the order in which train operation information is received makes it difficult to prioritize and handle highly urgent emergencies, and thus makes it difficult to ensure the safe operation of trains. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and medium for generating train emergency decision-making information. The technical solutions of this invention can improve the accuracy and efficiency of generating train emergency decision-making information.

[0006] In a first aspect, embodiments of the present invention provide a method for generating train emergency decision information, the method comprising:

[0007] Acquire real-time event status data associated with emergencies of running trains. The event status data includes at least one parameter item and the parameter value of each parameter item.

[0008] Based on the parameters and their values ​​in the event status data, monitor whether a sudden event has occurred on the train.

[0009] If a train emergency is determined to have occurred, obtain the type of the emergency and the corresponding target item from each parameter item;

[0010] Obtain the type of impact of the target item;

[0011] Based on the event type and the impact type of the target item, determine the train's emergency decision-making information.

[0012] Secondly, embodiments of the present invention also provide a train emergency decision information generation device, the device comprising:

[0013] The data acquisition module is used to acquire event status data associated with sudden events of trains in real time. The event status data includes at least one parameter item and the parameter value of each parameter item.

[0014] The fault detection module is used to monitor whether a sudden event has occurred on the train based on the parameters and their values ​​in the event status data.

[0015] The target item determination module is used to obtain the event type of the emergency and the target item corresponding to the emergency from each parameter item when it is determined that an emergency has occurred on the train.

[0016] The type acquisition module is used to obtain the impact type of the target item;

[0017] The information determination module is used to determine the train's emergency decision-making information based on the event type and the impact type of the target item.

[0018] Thirdly, embodiments of the present invention also provide a train emergency decision-making information generation device, the device comprising:

[0019] At least one processor; and

[0020] A memory that is communicatively connected to at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the train emergency decision information generation method according to any embodiment of the present invention.

[0022] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the train emergency decision information generation method of any embodiment of the present invention.

[0023] The technical solution of this invention acquires event status data associated with real-time train emergencies. This event status data includes at least one parameter item and its value. Based on the parameter items and their values, the system monitors whether an emergency has occurred. If an emergency has occurred, the system acquires the event type and the corresponding target item from each parameter item. It also acquires the impact type of the target item. Based on the event type and the impact type of the target item, the system determines the train's emergency decision-making information. This information, based on multiple dimensions such as the emergency, the influencing factors, and the degree of influence of each factor, enriches the content and accuracy of the emergency decision-making information. The influencing factors and their degree of influence can describe the urgency of the emergency, allowing for handling of emergencies according to their urgency. This solves the problem that humans can only formulate emergency decisions based on the order of receiving train emergency information, making it difficult to prioritize high-urgency emergencies and ensure train operation safety. By handling emergencies according to their urgency, the system improves train operation safety.

[0024] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0025] 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.

[0026] Figure 1 This is a flowchart of a train emergency decision information generation method according to Embodiment 1 of the present invention;

[0027] Figure 2 This is a flowchart of a train emergency decision information generation method according to Embodiment 2 of the present invention;

[0028] Figure 3 This is a structural diagram of a train emergency decision information generation device according to an embodiment of the present invention;

[0029] Figure 4 This is a schematic diagram of the structure of a train emergency decision information generation device provided in an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] In the technical solutions of the embodiments of the present invention, the acquisition, storage and application of event status data, etc., all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0033] Example 1

[0034] Figure 1 This is a flowchart illustrating a train emergency decision information generation method according to Embodiment 1 of the present invention. This embodiment of the invention is applicable to situations involving train emergency decision information generation. The method can be executed by a train emergency decision information generation device, which can be implemented in hardware and / or software and can be configured within a train emergency decision information generation equipment.

[0035] See Figure 1 The train emergency decision-making information generation method shown includes:

[0036] S101. Obtain event status data associated with sudden events of trains in real time. The event status data includes at least one parameter item and the parameter value of each parameter item.

[0037] An emergency can refer to an abnormal event that occurs suddenly or exceeds normal operational expectations during train operation, stopping, or dispatching, which may pose a direct or indirect threat to train safety, operational order, passenger life and property, or public interests, requiring immediate emergency response measures. Event status data can be used to describe a collection of data on various aspects such as the real-time operating status of the train, its own performance, and its environment.

[0038] Specifically, emergencies can be: Mechanical train malfunctions: such as brake system failure, power system failure (e.g., engine stall or traction motor failure), or bogie abnormalities, which may lead to train stoppage, rear-end collision risk, or derailment. Track and line malfunctions: such as track deformation, switch failure, overhead contact line breakage (for electrified trains), or foreign objects on the track (e.g., falling rocks or construction debris), which may cause trains to be unable to pass or to collide. Communication and signaling malfunctions: signaling system paralysis or dispatch communication interruption may cause operational chaos such as rear-end collisions or trains traveling in the wrong direction. Event status data includes at least one parameter item and the parameter values ​​for each parameter item. A parameter item can refer to a variable representing the train status to be collected. The parameter values ​​of a parameter item are used to describe the data collected based on the parameter item. Example: Event status data includes parameter item 1: train speed, parameter item 1 value 500 km / h; parameter item 2: wheel angle, parameter item 2 value 130°; parameter item 3: wind force, parameter item 3 value level 3 gale.

[0039] S102. Based on the parameters and their values ​​in the event status data, monitor whether a sudden event has occurred on the train.

[0040] Specifically, in rail transit, monitoring parameters determines whether a train incident has occurred by checking if the values ​​of monitored parameters exceed normal ranges or show abnormal values. Different event status data include different parameter items. Different event status data can trigger different types of train incidents. For example, when the train speed value in the event status data exceeds the maximum permissible speed stipulated by the railway, it can lead to a train derailment; when the engine temperature value in the event status data exceeds the normal operating range stipulated by the railway, it can lead to an engine malfunction; when the wind force value in the event status data exceeds the maximum safe wind force stipulated by the railway, it can lead to a window malfunction, etc. Preset information is obtained, including at least one event type and at least one parameter item corresponding to each event type that triggers the incident, as well as the parameter conditions corresponding to each parameter item. The parameter value corresponding to the parameter item is compared with its corresponding parameter conditions. If the parameter value of the parameter item meets the parameter conditions, it indicates that the parameter item is abnormal and the train exhibits the event type corresponding to that parameter item; if the parameter value of the parameter item does not meet the parameter conditions, it indicates that the parameter item is not abnormal and the train does not exhibit the event type corresponding to that parameter item.

[0041] S103. If it is determined that a train emergency has occurred, obtain the event type of the emergency and the target item corresponding to the emergency in each parameter item.

[0042] The event type can be used to describe the type of sudden event that occurs on the train. The target item can refer to the parameter item that causes the sudden event to occur on the train.

[0043] Specifically, when a train incident is determined to have occurred, meaning at least one parameter value exceeds the normal range or exhibits an abnormal value, at least one event type and at least one parameter item corresponding to each event type are determined based on preset information. Each parameter item corresponding to an event type is the target item for that event type. For example, preset type 1: [Preset parameter item 1: Train speed, parameter condition for preset parameter item 1: greater than 400 km / h or preset parameter item 2: Wheel angle, parameter condition for preset parameter item 2: greater than 120° or preset parameter item 3: Train signal, parameter condition for preset parameter item 3: log data contains 404]. When the parameter item is train speed, the parameter value is 500 km / h. Comparing 500 km / h with the parameter condition for preset type 1 (greater than 400 km / h), if the comparison result meets the condition, then preset type 1 corresponding to train speed is determined as the train's event type. Train speed is the target item corresponding to the train's event type.

[0044] S104. Obtain the impact type of the target item.

[0045] Among them, the impact type can be used to describe the type of cause of a train emergency due to a parameter item.

[0046] Specifically, the impact of a target item on train emergencies can be categorized into direct and indirect impact types. If an anomaly in a target item directly causes a component or system of the train to malfunction, thus triggering an emergency, then the impact type of that target item is a direct impact. If an anomaly in a target item itself does not immediately cause a malfunction, but gradually weakens the performance of train components or systems, increases the likelihood of malfunctions, or affects other key parameters, thus indirectly leading to an emergency, then the impact type of that target item is an indirect impact. For example, a motor generates heat during operation and normally has a certain operating temperature range. When the motor temperature remains excessively high, such as exceeding the temperature limit that the insulation material can withstand, it directly leads to accelerated aging or even damage of the insulation material. This reduces the insulation performance between the motor windings, causing a short circuit fault, resulting in the motor malfunctioning and the train losing power; the impact type of the motor temperature is a direct impact. Similarly, excessively high external humidity can cause a water film to form on the track surface, reducing the friction between the wheels and the track. While this does not directly cause train malfunctions, it affects the train's braking and traction performance. Trains require a longer braking distance to stop and may slip during starting and acceleration, increasing the instability of train operation and indirectly increasing the risk of emergencies. Therefore, the influence of external humidity is classified as an indirect influence.

[0047] S105. Determine the train emergency decision-making information based on the event type and the impact type of the target item.

[0048] Among them, train emergency decision-making information can be a collection of data on maintenance time and maintenance methods for train emergencies, determined according to the event type and the impact type of the target item.

[0049] Specifically, different types of emergencies require different emergency decision-making methods. Different impact types of target items correspond to different levels of urgency for handling. Based on the impact type of the target item, the urgency level corresponding to the event type of the emergency is determined. Based on the event type of the emergency, the corresponding emergency decision-making method can be determined. The urgency levels of each event type are ranked to determine the order of emergencies to be handled. The event types and their corresponding emergency decision-making methods are then ranked according to the order of the emergencies to be handled, thus determining the train's emergency decision-making information. The train's emergency decision-making information can be identified, at least one person to receive the information and their contact information can be determined, and the train's emergency decision-making information can be sent to the respective recipients according to their contact information.

[0050] The technical solution of this invention acquires event status data associated with real-time train emergencies. This event status data includes at least one parameter item and its value. Based on the parameter items and their values, the system monitors whether an emergency has occurred. If an emergency has occurred, the system acquires the event type and the corresponding target item from each parameter item. It also acquires the impact type of the target item. Based on the event type and the impact type of the target item, the system determines the train's emergency decision-making information. This information, based on multiple dimensions such as the emergency, the influencing factors, and the degree of influence of each factor, enriches the content and accuracy of the emergency decision-making information. The influencing factors and their degree of influence can describe the urgency of the emergency, allowing for handling of emergencies according to their urgency. This solves the problem that humans can only formulate emergency decisions based on the order of receiving train emergency information, making it difficult to prioritize high-urgency emergencies and ensure train operation safety. By handling emergencies according to their urgency, the system improves train operation safety.

[0051] Example 2

[0052] Figure 2 This is a flowchart illustrating a train emergency decision-making information generation method according to Embodiment 2 of the present invention. Based on the above embodiments, the present invention optimizes and improves the train emergency decision-making information generation method.

[0053] Furthermore, the "obtaining the impact type of the target item" is refined into "obtaining the connection relationship between the nodes of the event type and the nodes of the target item in the emergency event knowledge graph; the emergency event knowledge graph includes nodes of each event type, nodes of at least one parameter item, and the connection relationship between each event type and the parameter item that causes each event type; based on the connection relationship, the impact type of the target item is determined", in order to improve the train emergency decision-making information generation method.

[0054] It should be noted that for parts not described in detail in the embodiments of the present invention, please refer to the descriptions in other embodiments.

[0055] See Figure 2 The train emergency decision-making information generation method shown includes:

[0056] S201. Obtain event status data associated with emergencies of trains in real time. The event status data includes at least one parameter item and the parameter value of each parameter item.

[0057] S202. Based on the parameters and their values ​​in the event status data, monitor whether a sudden event has occurred on the train.

[0058] S203. If it is determined that a train emergency has occurred, obtain the event type of the emergency and the target item corresponding to the emergency in each parameter item.

[0059] S204. Obtain the connection relationship between the nodes of event types and the nodes of target items in the emergency event knowledge graph; the emergency event knowledge graph includes nodes of each event type, nodes of at least one parameter item, and the connection relationship between each event type and the parameter item that causes each event type.

[0060] Among them, the emergency knowledge graph can be used to describe a graph-based knowledge representation method. It organizes and presents various entities (such as event types or parameter items) and their relationships in a graphical way in the field of train emergencies, providing comprehensive and accurate knowledge support for the diagnosis and management of train emergencies. Connection relationships can be used to describe the connection information between event types and the parameter items that cause event types.

[0061] Specifically, train emergency reports can be obtained, and these reports can be segmented to obtain at least one entity word. Relationships are then extracted from the train emergency reports and each entity word to determine the associations between them. The extracted associations and the entity words themselves are imported into a graph database to obtain a train emergency knowledge graph. This knowledge graph contains connections between nodes of target items and nodes of emergency event types, as well as between nodes of target items and nodes of emergency event types. There are direct connections between nodes of emergency event types and nodes of target items, and there are also indirect connections between emergency event types and target items through multiple parameter items.

[0062] S205. Determine the type of influence of the target item based on the connection relationship.

[0063] Among them, the impact type can be used to describe the type of cause that leads to a sudden incident on the train.

[0064] Specifically, the train emergency event knowledge graph contains nodes for target items and nodes for event types, as well as connections between these nodes. Queries are performed within the train emergency event knowledge graph using methods including, but not limited to, sequential search algorithms, tree search algorithms, binary search algorithms, or hash search algorithms; this embodiment of the invention does not impose any limitations on these methods. Based on the connections between nodes for target items and nodes for event types, it is determined whether the connection between the target item and the event type is direct or indirect. Direct and indirect connections correspond to different impact types, thereby determining the impact type of the target item.

[0065] S206. Determine the train emergency decision-making information based on the event type and the impact type of the target item.

[0066] In this embodiment of the invention, the connection relationship between nodes of event types and nodes of target items in the emergency event knowledge graph is obtained. The emergency event knowledge graph includes nodes of each event type, nodes of at least one parameter item, and connection relationships between each event type and the parameter item that causes each event type. Based on the connection relationship, the influence type of the target item is determined. The influence type between the target item and the event type can be determined through the emergency event knowledge graph of the train, and the target item can be classified. This refines the processing operation of the target item and improves the accuracy of the target item analysis.

[0067] Optionally, the type of influence of the target item can be determined based on the connection relationship, including: if the connection relationship is a direct connection, the type of influence of the target item is determined to be a direct influence type; if the connection relationship is an indirect connection, the type of influence of the target item is determined to be an indirect influence type.

[0068] In this configuration, direct connections describe nodes that are directly connected to the target item and the event type of the emergency, with no nodes between them. Indirect connections describe nodes that are connected to the target item and the event type of the emergency by at least one node.

[0069] Specifically, the train emergency knowledge graph contains nodes representing target items and nodes representing event types, as well as connections between these nodes. Nodes representing event types are directly connected to nodes representing target items. When the parameter value corresponding to a target item malfunctions or falls outside the normal train operating range, the target item can directly cause an emergency; this is a direct impact type. Nodes representing event types are indirectly connected to target items through multiple parameter items. When the parameter value corresponding to a target item malfunctions or falls outside the normal train operating range, the target item only indirectly causes an emergency by gradually weakening the performance of train components or systems, increasing the likelihood of an emergency, or by affecting other key parameter items. The target item cannot directly cause an emergency; this is an indirect impact type.

[0070] By classifying target items based on their connection relationships—if the connection is direct, the impact type is determined to be direct; if the connection is indirect, the impact type is determined to be indirect—and performing different operations on different categories, the accuracy of target item processing is improved.

[0071] Optionally, train emergency decision-making information is determined based on the event type and the impact type of the target item, including: determining the target weight coefficient of the target item from at least one weight coefficient corresponding to the target item based on the impact type of the target item; determining the target weight value of the target item based on the target weight coefficient and the parameter value of the target item; and determining the train emergency decision-making information based on the event type and the target weight value.

[0072] The weighting coefficient can be used to describe the importance of a target item requiring emergency handling. The target weighting coefficient can be used to describe the weighting coefficient of the target item at the current time.

[0073] Specifically, the value and number of weight coefficients corresponding to different impact types of target items vary. Based on the impact type of the target item, the target weight coefficient is determined from at least one of the weight coefficients corresponding to the target item. The target weight value of the target item is determined by multiplying its target weight coefficient by its parameter value. Based on the event type of the emergency and the target weight value, the event type of the train and the urgency level of the emergency response corresponding to that event type can be determined. The target weight values ​​corresponding to each event type are sorted, and the emergency response methods corresponding to the event types are obtained sequentially according to the order of the target weight values ​​to determine the train's emergency decision information.

[0074] By determining the target weight coefficient of the target item from at least one weight coefficient corresponding to the target item based on the impact type of the target item; determining the target weight value of the target item based on the target weight coefficient and the parameter value of the target item; and determining the train emergency decision information based on the event type and the target weight value, the urgency of the emergency events to be handled can be ranked so that the emergency events with higher urgency can be handled first, thereby improving the safety of train operation.

[0075] Optionally, when the impact type is indirect, the target weight coefficient of the target item is determined from at least one weight coefficient corresponding to the target item based on the impact type of the target item. This includes: finding the connection distance between the node of the target item and the node of the event type in the knowledge graph of the emergency event, and using it as the first weight coefficient; obtaining at least one distance threshold of the target item and the distance weight corresponding to each distance threshold; comparing the connection distance with each distance threshold to determine the second weight coefficient; and multiplying the first weight coefficient and the second weight coefficient to determine the target weight coefficient of the target item.

[0076] The connection distance describes the distance between the target item and the node representing the event type of the emergency in the emergency knowledge graph. The distance threshold describes the threshold corresponding to the preset connection distance. The distance weight describes the urgency of the emergency requiring emergency handling corresponding to the distance threshold.

[0077] Specifically, when the impact type is indirect, there must be at least one node between the target item's node and the event type's node. The connection distance between nodes is preset to 1. The number of nodes between the target item's node and the event type's node is found in the emergency event knowledge graph to determine the connection distance, which is used as the first weight coefficient. Different connection distances correspond to different weight coefficients; the longer the connection distance, the smaller the weight coefficient, indicating a smaller impact of the target item on the emergency event; the shorter the connection distance, the larger the weight coefficient, indicating a greater impact of the target item on the emergency event. At least one distance threshold for the target item and the distance weight corresponding to each distance threshold are obtained. The connection distance is compared with each distance threshold, and the weight coefficient corresponding to the distance threshold to which the connection distance belongs is determined as the second weight coefficient. The first weight coefficient and the second weight coefficient are multiplied to determine the target weight coefficient of the target item.

[0078] When the impact type is indirect, the connection distance between the node of the target item and the node of the event type is found in the knowledge graph of the emergency, and used as the first weight coefficient; at least one distance threshold of the target item and the distance weight corresponding to each distance threshold are obtained; the connection distance is compared with each distance threshold to determine the second weight coefficient; the first weight coefficient and the second weight coefficient are multiplied to determine the target weight coefficient of the target item. The connection distance is determined according to the connection method between each node in the indirect connection. The degree of impact of the target item on the emergency of the train is determined by multidimensional data, which improves the accuracy of the determination of the target weight coefficient.

[0079] Optionally, when the impact type is direct impact, the target weight coefficient of the target item is determined from at least one weight coefficient corresponding to the target item according to the impact type of the target item, including: obtaining the parameter weight corresponding to the target item; and determining the parameter weight as the target weight coefficient of the target item.

[0080] Among them, the parameter weights can be used to describe the urgency of the preset target items to be handled in an emergency.

[0081] Specifically, at least one parameter item and its corresponding weight are obtained. The methods for obtaining these parameters include, but are not limited to, voice input, mouse selection, or keyboard input; this embodiment of the invention does not impose any restrictions on these methods. The target item is searched among the parameter items to obtain its corresponding weight. If the influence type is "direct influence," it indicates that the target item can directly cause a sudden event on the train. Other nodes do not affect the degree of influence of the target item on the sudden event. The weight of the parameter item is then determined as the target weight coefficient of the target item.

[0082] When the impact type is direct impact, obtain the weight of the parameter item corresponding to the target item; determine the weight of the parameter item as the target weight coefficient of the target item, which can reduce the amount of data to be analyzed and improve the efficiency of determining the target weight coefficient.

[0083] Optionally, based on the event type and target weight value, train emergency decision information is determined, including: inputting the event prediction model based on the event type and target weight value to obtain the emergency handling prediction time and emergency handling method corresponding to the event type; calculating the train delay time based on the emergency handling prediction time corresponding to the event type and the obtained current train departure time; and determining the train emergency decision information based on the train delay time and the emergency handling method corresponding to the event type.

[0084] Among them, the event prediction model can be used to describe the model that generates emergency decision-making information for emergencies. The emergency response prediction time can be used to describe the time required for emergency response based on the predicted emergency. The emergency response method can be used to describe the methods used to respond to emergencies. The current train departure time can be used to describe the current time the train is waiting to depart. The train delay time can be used to describe the time when the train will re-depart after the emergency response to the train has been completed.

[0085] Specifically, the event prediction model can be pre-trained using at least one event type, its corresponding weight, emergency response time, and emergency response method. Based on the event type and its weight, the predicted emergency response time and method for a sudden event can be obtained. The event prediction model is then input with the event type and target weight values ​​to obtain the predicted emergency response time and method for that event type. The train delay time is calculated by adding the predicted emergency response time to the current train departure time. Based on the train delay time and the emergency response method for the sudden event, the train's emergency decision information is determined. At least one piece of train equipment and its corresponding operating commands can be identified based on the train's emergency decision information. These operating commands are then sent to each piece of train equipment to enable it to perform the corresponding operations.

[0086] By inputting event prediction models based on event type and target weight values, the predicted emergency response time and method corresponding to each event type are obtained. Based on the predicted emergency response time and the current train departure time, train delay time is calculated. Based on the train delay time and the corresponding emergency response method, train emergency decision information is determined. This multi-dimensional information constructs emergency decision information for sudden events, enabling train maintenance to proceed according to this information. This eliminates the need for manual emergency response based on the order in which emergency information is received, thus improving the efficiency and accuracy of train emergency response.

[0087] Example 3

[0088] Figure 3 This is a schematic diagram of a train emergency decision information generation device according to Embodiment 3 of the present invention. This embodiment of the invention is applicable to the generation of train emergency decision information. The device can use a train emergency decision information generation method, and can be implemented in hardware and / or software. The device can be configured within a train emergency decision information generation device.

[0089] See Figure 3The train emergency decision-making information generation device shown includes: a data acquisition module 301, a fault detection module 302, a target item determination module 303, a type acquisition module 304, and an information determination module 305, wherein...

[0090] The data acquisition module 301 is used to acquire event status data associated with sudden events of a train in real time. The event status data includes at least one parameter item and the parameter value of each parameter item.

[0091] The fault detection module 302 is used to monitor whether a sudden event has occurred on the train based on the parameter items and parameter values ​​in the event status data.

[0092] The target item determination module 303 is used to obtain the event type of the sudden event and the target item corresponding to the sudden event from each parameter item when it is determined that a sudden event has occurred on the train.

[0093] Type acquisition module 304 is used to obtain the impact type of the target item;

[0094] The information determination module 305 is used to determine the train emergency decision information based on the event type and the impact type of the target item.

[0095] The technical solution of this invention acquires event status data associated with real-time train emergencies. This event status data includes at least one parameter item and its value. Based on the parameter items and their values, the system monitors whether an emergency has occurred. If an emergency has occurred, the system acquires the event type and the corresponding target item from each parameter item. It also acquires the impact type of the target item. Based on the event type and the impact type of the target item, the system determines the train's emergency decision-making information. This information, based on multiple dimensions such as the emergency, the influencing factors, and the degree of influence of each factor, enriches the content and accuracy of the emergency decision-making information. The influencing factors and their degree of influence can describe the urgency of the emergency, allowing for handling of emergencies according to their urgency. This solves the problem that humans can only formulate emergency decisions based on the order of receiving train emergency information, making it difficult to prioritize high-urgency emergencies and ensure train operation safety. By handling emergencies according to their urgency, the system improves train operation safety.

[0096] Optional, the type retrieval module 304 includes:

[0097] The relationship acquisition unit is used to acquire the connection relationship between the nodes of event types and the nodes of target items in the emergency event knowledge graph; the emergency event knowledge graph includes nodes of each event type, nodes of at least one parameter item, and the connection relationship between each event type and the parameter item that causes each event type;

[0098] The type determination unit is used to determine the type of influence of the target item based on the connection relationship.

[0099] Optional, type-determining unit, specifically used for:

[0100] The direct type determines the sub-unit, which is used to determine the influence type of the target item as the direct influence type if the connection relationship is a direct connection;

[0101] The indirect type determines the sub-unit, which is used to determine the influence type of the target item as indirect influence type if the association relationship is indirect connection.

[0102] Optionally, the information determination module 305 includes:

[0103] The coefficient determination unit is used to determine the target weight coefficient of the target item from at least one weight coefficient corresponding to the target item based on the type of influence of the target item.

[0104] The numerical calculation unit is used to determine the target weight value of the target item based on the target weight coefficient and the parameter value of the target item.

[0105] The decision-making unit is used to determine the train's emergency decision information based on the event type and target weight value.

[0106] Optional, coefficient determination unit, specifically used for:

[0107] When the impact type is indirect, the connection distance between the node of the target item and the node of the event type is found in the knowledge graph of the emergency event and used as the first weight coefficient;

[0108] Obtain at least one distance threshold for the target item and the distance weight corresponding to each distance threshold;

[0109] The connection distance is compared with various distance thresholds to determine the second weighting coefficient;

[0110] Multiply the first weight coefficient by the second weight coefficient to determine the target weight coefficient of the target item.

[0111] Optional, coefficient determination unit, specifically used for:

[0112] When the impact type is direct impact, obtain the weight of the parameter item corresponding to the target item;

[0113] The weights of the parameter items are determined as the target weight coefficients of the target items.

[0114] Optional, decision-making unit, specifically used for:

[0115] Based on the event type and target weight values, the event prediction model is obtained to get the emergency response prediction time and emergency response method corresponding to the event type.

[0116] Calculate the train delay time based on the predicted emergency response time corresponding to the event type and the current train departure time.

[0117] Based on the train delay time and the corresponding emergency response method for the event type, determine the train's emergency decision-making information.

[0118] The train emergency decision information generation device provided in this embodiment of the invention can execute the train emergency decision information generation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the train emergency decision information generation method.

[0119] Example 4

[0120] Figure 4 A schematic diagram of the structure of a train emergency decision information generation device 400 that can be used to implement an embodiment of the present invention is shown.

[0121] like Figure 4 As shown, the train emergency decision-making information generation device 400 includes at least one processor 401 and a memory, such as a read-only memory (ROM) 402 and a random access memory (RAM) 403, communicatively connected to the at least one processor 401. The memory stores computer programs executable by the at least one processor. The processor 401 can perform various appropriate actions and processes based on the computer program stored in the ROM 402 or loaded from the storage unit 408 into the RAM 403. The RAM 403 can also store various programs and data required for the operation of the train emergency decision-making information generation device 400. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0122] Multiple components in the train emergency decision-making information generation device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard or mouse; an output unit 407, such as various types of displays or speakers; a storage unit 408, such as a hard disk or optical disk; and a communication unit 409, such as a network card, modem, or wireless transceiver. The communication unit 409 allows the train emergency decision-making information generation device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0123] Processor 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 401 performs the various methods and processes described above, such as the train emergency decision information generation method.

[0124] In some embodiments, the train emergency decision information generation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded into and / or installed onto the train emergency decision information generation device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by processor 401, one or more steps of the train emergency decision information generation method described above may be performed. Alternatively, in other embodiments, processor 401 may be configured to perform the train emergency decision information generation method by any other suitable means (e.g., by means of firmware).

[0125] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0127] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] To provide user interaction, the systems and techniques described herein can be implemented on a train emergency decision information generation device, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the train emergency decision information generation device. Other types of devices can also be used to provide user interaction; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0129] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0130] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0131] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0132] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for generating emergency decision-making information for trains, characterized in that, The method includes: Acquire event status data associated with emergencies of a train in real time, wherein the event status data includes at least one parameter item and the parameter value of each parameter item; Based on the parameter items and their values ​​in the event status data, monitor whether the train experiences a sudden event; If it is determined that an emergency has occurred on the train, the event type of the emergency is obtained and the target item corresponding to the emergency is obtained from each of the parameter items; Obtain the impact type of the target item; Based on the event type and the impact type of the target item, determine the train emergency decision information.

2. The method according to claim 1, characterized in that, The acquisition of the impact type of the target item includes: Obtain the connection relationship between the nodes of the event type and the nodes of the target item in the emergency event knowledge graph; the emergency event knowledge graph includes nodes of each event type, nodes of at least one parameter item, and connection relationships between each event type and the parameter item that causes each event type; Based on the connection relationship, determine the influence type of the target item.

3. The method according to claim 2, characterized in that, Determining the influence type of the target item based on the connection relationship includes: If the connection relationship is a direct connection, then the influence type of the target item is determined to be a direct influence type; If the relationship is an indirect connection, then the influence type of the target item is determined to be an indirect influence type.

4. The method according to claim 2, characterized in that, The step of determining the train emergency decision information based on the event type and the impact type of the target item includes: Based on the type of influence of the target item, determine the target weight coefficient of the target item from at least one weight coefficient corresponding to the target item; The target weight value of the target item is determined based on the target weight coefficient of the target item and the parameter value of the target item; Based on the event type and the target weight value, the train emergency decision information is determined.

5. The method according to claim 4, characterized in that, When the influence type is an indirect influence type, determining the target weight coefficient of the target item from at least one weight coefficient corresponding to the target item based on the influence type of the target item includes: The connection distance between the node of the target item and the node of the event type is found in the knowledge graph of the emergency, and used as the first weight coefficient; Obtain at least one distance threshold for the target item and the distance weight corresponding to each distance threshold; The connection distance is compared with each of the distance thresholds to determine the second weighting coefficient; The target weight coefficient of the target item is determined by multiplying the first weight coefficient by the second weight coefficient.

6. The method according to claim 4, characterized in that, When the influence type is a direct influence type, determining the target weight coefficient of the target item from at least one weight coefficient corresponding to the target item based on the influence type of the target item includes: Obtain the weights of the parameter items corresponding to the target item; The weight of the parameter item is determined as the target weight coefficient of the target item.

7. The method according to claim 4, characterized in that, The step of determining the train emergency decision information based on the event type and the target weight value includes: Based on the event type and the target weight value input, the event prediction model is obtained to obtain the emergency response prediction time and emergency response method corresponding to the event type. The train delay time is calculated based on the predicted emergency response time corresponding to the event type and the current train departure time. Based on the train delay time and the emergency response method corresponding to the event type, the train emergency decision information is determined.

8. A train emergency decision-making information generation device, characterized in that, The device includes: The data acquisition module is used to acquire event status data associated with sudden events of a train in real time. The event status data includes at least one parameter item and the parameter value of each parameter item. The fault detection module is used to monitor whether a sudden event has occurred on the train based on each parameter item and the parameter value in the event status data. The target item determination module is used to, when it is determined that a sudden event has occurred on the train, obtain the event type of the sudden event and obtain the target item corresponding to the sudden event from each of the parameter items; The type acquisition module is used to acquire the impact type of the target item; The information determination module is used to determine the train emergency decision information of the train based on the event type and the impact type of the target item.

9. A train emergency decision-making information generation device, characterized in that, The device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the train emergency decision information generation method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the train emergency decision information generation method according to any one of claims 1-7.

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