Rail transit emergency information generation method, device, equipment and medium

Abstract

The invention discloses a rail transit emergency information generation method and device, equipment and a medium. The method comprises the steps of obtaining fault parameter items corresponding to rail transit fault types and fault parameter data corresponding to the fault parameter items; acquiring system monitoring parameter items, system monitoring parameter data corresponding to the system monitoring parameter items, and sensing data; comparing the system monitoring parameter data corresponding to the system monitoring parameter items with the fault parameter data of the fault parameter items corresponding to the system monitoring parameter items to obtain risk parameter items and risk parameter data corresponding to the risk parameter items; calculating to obtain a predicted fault type according to the obtained data; obtaining resource supply information corresponding to the predicted fault type; and generating rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type. According to the technical scheme of the embodiment of the invention, the accuracy and efficiency of rail transit emergency information generation can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a rail transit emergency information generation method, device, equipment and medium. Background Art

[0002] With the development of science and technology, the types and number of rail transit lines are increasing, and the rail transit network has greatly met people's daily travel needs. However, due to the special operation of rail transit facilities and equipment, for example, large passenger flow and bad weather, there are many risks in the operation process. When an emergency occurs, emergency response needs to be carried out more quickly.

[0003] At present, rail transit facilities and equipment are manually maintained on a daily basis, and emergency response or operation and maintenance methods are manually planned for different emergency events.

[0004] However, there are a large number of rail transit facilities and equipment, and the amount of data that needs to be monitored on a daily basis is huge, making it difficult to promptly detect fault information and emergency information on rail transit facilities and equipment and to promptly plan emergency or operation and maintenance measures. Summary of the invention

[0005] The present invention provides a rail transit emergency information generation method, device, equipment and medium. The technical solution of the embodiment of the present invention can improve the accuracy and efficiency of rail transit emergency information generation.

[0006] In a first aspect, an embodiment of the present invention provides a method for generating rail transit emergency information, the method comprising:

[0007] Obtain at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each fault parameter item;

[0008] Acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, and sensor data collected by at least one sensor device;

[0009] For each system monitoring parameter item, compare the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item to obtain the risk parameter item and the risk parameter data corresponding to the risk parameter item;

[0010] Calculate according to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item, and the sensor data collected by each sensor device to obtain the predicted fault type;

[0011] Obtain resource supply information corresponding to the predicted fault type;

[0012] Rail transit emergency information is generated according to the predicted fault type and resource supply information corresponding to the predicted fault type.

[0013] In a second aspect, an embodiment of the present invention further provides a rail transit emergency information generating device, the device comprising:

[0014] A fault data acquisition module, used to obtain at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each fault parameter item;

[0015] A monitoring data acquisition module, used to acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, and sensor data collected by at least one sensor device;

[0016] A risk data acquisition module is used to compare the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item for each system monitoring parameter item, so as to obtain the risk parameter item and the risk parameter data corresponding to the risk parameter item;

[0017] A prediction type acquisition module is used to calculate according to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item, and the sensor data collected by each sensor device to obtain the predicted fault type;

[0018] A supply information acquisition module, used to obtain resource supply information corresponding to the predicted fault type;

[0019] The emergency information generation module is used to generate rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type.

[0020] In a third aspect, an embodiment of the present invention further provides a rail transit emergency information generating device, the device comprising:

[0021] at least one processor; and

[0022] a memory communicatively connected to at least one processor; wherein,

[0023] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the rail transit emergency information generation method of any embodiment of the present invention.

[0024] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for implementing the rail transit emergency information generating method of any embodiment of the present invention when executed by a processor.

[0025] The technical solution of the embodiment of the present invention can improve the accuracy of fault type analysis by performing fault type analysis through multi-dimensional data by obtaining fault parameter items corresponding to multiple fault types and fault parameter data corresponding to the fault parameter items. At least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, as well as sensor data collected by at least one sensor device, are obtained, the system monitoring data and the sensor data are obtained, and the operating status of rail transit facilities and equipment is monitored in real time through multi-dimensional data to obtain the real-time operating status of rail transit facilities and equipment. For each system monitoring parameter item, the system monitoring parameter data corresponding to the system monitoring parameter item is compared with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item, and the risk parameter item and the risk parameter data corresponding to the risk parameter item are obtained, so that the fault condition of rail transit facilities and equipment can be detected in time, and the efficiency of rail transit emergency handling can be improved. According to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item and the sensor data collected by each sensor device, calculation is performed to obtain the predicted fault type, and the resource supply information corresponding to the predicted fault type is obtained in real time; according to the predicted fault type and the resource supply information corresponding to the predicted fault type, rail transit emergency information is generated, the fault of rail transit facilities and equipment can be predicted in time, and the resource supply information of the fault can be obtained in time, thereby improving the efficiency of generating rail transit emergency information.

[0026] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 is a flow chart of a rail transit emergency information generation method provided according to an embodiment of the present invention;

[0029] Figure 2 is a flow chart of a rail transit emergency information generation method provided according to an embodiment of the present invention;

[0030] Figure 3 is a structural diagram of a rail transit emergency information generating device provided according to an embodiment of the present invention;

[0031] Figure 4 It is a structural schematic diagram of a rail transit emergency information generating device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] In the technical solution of the embodiment of the present invention, the acquisition, storage and application of the sensor data collected by the sensor equipment involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0035] Embodiment 1

[0036] Figure 1 A flow chart of a rail transit emergency information generation method provided in Embodiment 1 of the present invention. The embodiment of the present invention is applicable to the generation of rail transit emergency information, and the method can be executed by a rail transit emergency information generation device, which can be implemented in the form of hardware and / or software, and can be configured in a rail transit emergency information generation device.

[0037] See also Figure 1 The rail transit emergency information generation method shown includes:

[0038] S101. Obtain at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each fault parameter item.

[0039] Among them, rail transit train can be used to describe a type of transportation vehicle that needs to travel on a specific track. Rail transit fault type can be used to describe the type of fault that affects the operation of rail transit trains. Fault parameter items can be used to describe the fault determination indicators corresponding to rail transit fault types. Fault parameter data can be used to describe the values ​​corresponding to fault parameter items.

[0040] Specifically, there are many types of faults that affect the operation of rail transit trains, for example, mudslides, communication signal interruptions, on-board equipment failures or brake failures, etc. Different rail transit fault types correspond to different fault parameter items and fault parameter data corresponding to the fault parameter items. The type of rail transit fault can be determined by the fault parameter items and the fault parameter data corresponding to the fault parameter items. At least one fault parameter item corresponding to at least one rail transit fault type and the fault parameter data corresponding to each fault parameter item are obtained, and the acquisition method includes but is not limited to: depth-first traversal algorithm or breadth-first traversal algorithm, etc., which is not limited in the embodiment of the present invention.

[0041] In an example, the priority traversal algorithm is used to obtain the rail transit fault type as a mudslide, and the fault parameter items corresponding to the rail transit fault type are precipitation and foreign matter amount. The fault parameter data corresponding to the precipitation item is 1.5 mm / h, and the fault parameter data corresponding to the foreign matter amount is 50%.

[0042] S102: Acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, and sensor data collected by at least one sensor device.

[0043] Among them, the system monitoring parameter item can be a monitoring indicator of an electronic monitoring system that monitors the operating status of rail transit facilities and equipment. The system monitoring parameter data can be used to describe the monitoring value corresponding to the system monitoring parameter item. The sensor device can be used to describe the sensor that monitors the operating status of rail transit facilities and equipment. The sensor data can be used to describe the data detected by the sensor device.

[0044] Specifically, there are multiple monitoring electronic systems to monitor the operating status of rail transit facilities and equipment. At least one system monitoring parameter item of the system monitoring and the system monitoring parameter data corresponding to each system monitoring parameter item are obtained, and the acquisition method includes but is not limited to: sequential search algorithm, binary search algorithm, block search algorithm or hash table search algorithm, etc., and the embodiment of the present invention does not limit this. At the same time, there is at least one sensor device to monitor the operating status of rail transit facilities and equipment, and obtain the sensor data collected by each sensor device. The sensor device can be a camera device, a temperature sensor or a humidity sensor, etc.

[0045] In one example, the system monitoring parameter items obtained by the sequential search algorithm are precipitation and passenger flow, the system monitoring parameter data corresponding to precipitation is 1.5 mm / h, and the system monitoring parameter data corresponding to passenger flow is 10,000 people / h. The sensor device is a camera device, and the sensor data collected by the sensor device is video data.

[0046] S103. For each system monitoring parameter item, compare the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item to obtain the risk parameter item and the risk parameter data corresponding to the risk parameter item.

[0047] The risk parameter item can be used to describe the system monitoring parameter item with the risk of failure. The system monitoring parameter data can be used to describe the value corresponding to the risk parameter item.

[0048] Specifically, by comparing the system monitoring parameter data corresponding to the system monitoring parameter items with the fault parameter data of the fault parameter items corresponding to the system monitoring parameter items, the risk parameter items and the risk parameter data corresponding to the risk parameter items can be obtained to determine the operation status of the rail transit facilities and equipment currently monitored in real time, and whether there are fault indicators can be monitored. If there are parameter items in the system monitoring parameter items that may cause faults, there is a risk of failure in the operation of the rail transit facilities and equipment.

[0049] In one example, the fault parameter items corresponding to the rail transit fault type are precipitation and foreign matter. The fault parameter data corresponding to the fault parameter item precipitation is 1.5mm / h, and the fault parameter data corresponding to the fault parameter item foreign matter is 50%. The system monitoring parameter items are precipitation, foreign matter and passenger flow. The system monitoring parameter data corresponding to precipitation is 1.5mm / h, the system monitoring parameter data corresponding to foreign matter is 50%, and the system monitoring parameter data corresponding to passenger flow is 10,000 people / h. Compare the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item, and obtain the risk parameter items of precipitation and foreign matter. The risk parameter data corresponding to the risk parameter item precipitation is 1.5mm / h, and the risk parameter data corresponding to the risk parameter item foreign matter is 50%.

[0050] S104, calculating according to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item, and the sensor data collected by each sensor device to obtain a predicted fault type.

[0051] The predicted fault type may be used to describe the type of predicted fault of rail transit facilities and equipment.

[0052] Specifically, each risk parameter item and the risk parameter data corresponding to each risk parameter item are compared with each fault parameter item and the fault parameter data corresponding to each rail transit fault type to determine whether a fault occurs in the operation of rail transit facilities and equipment and the type of rail transit fault that occurs. At the same time, the rail transit fault type is verified by analyzing the sensor data collected by each sensor device to obtain the predicted fault type.

[0053] In one example, the fault parameter items corresponding to the rail transit fault type are precipitation and foreign matter amount. The fault parameter data corresponding to the fault parameter item precipitation is 1.5mm / h, and the fault parameter data corresponding to the fault parameter item foreign matter amount is 50%. The risk parameter items are precipitation and foreign matter amount. The risk parameter data corresponding to the risk parameter item precipitation is 1.5mm / h, and the risk parameter data corresponding to the risk parameter item foreign matter amount is 50%. The rail transit fault type is obtained as a debris flow. The sensing device is a camera device, and the sensing data collected by the sensing device is video data. By analyzing the video data, the rail transit fault type is obtained as a debris flow, and the predicted fault type is obtained as a debris flow.

[0054] S105: Obtain resource supply information corresponding to the predicted fault type.

[0055] Among them, resource supply information can be used to describe information on solving rail transit failures and mobilizing material resources or human resources.

[0056] Specifically, resource supply information corresponding to the predicted fault type is obtained, and the obtaining method includes but is not limited to: mouse selection or keyboard input, etc., which is not limited in the embodiment of the present invention.

[0057] In one example, the resource supply information corresponding to the predicted fault type is obtained by selecting by mouse, that is, obtaining 10 maintenance tools from location A.

[0058] S106. Generate rail transit emergency information according to the predicted fault type and resource supply information corresponding to the predicted fault type.

[0059] Among them, rail transit emergency information can be used to describe the resource call information of human or material resources required to deal with the failures encountered by rail transit facilities and equipment during operation.

[0060] Specifically, rail transit emergency information may include at least one predicted fault type. One predicted fault type corresponds to one resource supply information. One resource supply information includes at least one scheduling method of human or material resources.

[0061] In one example, the predicted fault type is a mudslide, and the resource supply information corresponding to the predicted fault type is obtaining 10 maintenance tools from site A and obtaining 10 boxes of detection tools from site B.

[0062] The technical solution of the embodiment of the present invention can improve the accuracy of fault type analysis by performing fault type analysis through multi-dimensional data by obtaining fault parameter items corresponding to multiple fault types and fault parameter data corresponding to the fault parameter items. At least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, as well as sensor data collected by at least one sensor device, are obtained, the system monitoring data and the sensor data are obtained, and the operating status of rail transit facilities and equipment is monitored in real time through multi-dimensional data to obtain the real-time operating status of rail transit facilities and equipment. For each system monitoring parameter item, the system monitoring parameter data corresponding to the system monitoring parameter item is compared with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item, and the risk parameter item and the risk parameter data corresponding to the risk parameter item are obtained, so that the fault condition of rail transit facilities and equipment can be detected in time, and the efficiency of rail transit emergency handling can be improved. According to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item and the sensor data collected by each sensor device, calculation is performed to obtain the predicted fault type, and the resource supply information corresponding to the predicted fault type is obtained in real time; according to the predicted fault type and the resource supply information corresponding to the predicted fault type, rail transit emergency information is generated, the fault of rail transit facilities and equipment can be predicted in time, and the resource supply information of the fault can be obtained in time, thereby improving the efficiency of generating rail transit emergency information.

[0063] Embodiment 2

[0064] Figure 2 This is a flow chart of a rail transit emergency information generation method provided by Embodiment 2 of the present invention. Based on the above embodiments, this embodiment of the present invention optimizes and improves the rail transit emergency information generation method.

[0065] Further, "obtaining resource supply information corresponding to the predicted fault type" is refined into "according to the predicted fault type, querying at least one emergency resource item corresponding to the predicted fault type; for each emergency resource item, querying at least one resource supply location corresponding to the emergency resource item and the quantity of resources corresponding to each resource supply location according to the emergency resource item; for each emergency resource item, screening among the resource supply locations corresponding to the emergency resource item to obtain the emergency supply location corresponding to the emergency resource item; for each emergency resource item, obtaining the quantity of resources corresponding to the emergency supply location corresponding to the emergency resource item; according to the emergency supply locations corresponding to each emergency resource item corresponding to the predicted fault type and the quantity of resources corresponding to the emergency supply locations corresponding to each emergency resource item, obtain the resource supply information corresponding to the predicted fault type" to improve the rail transit emergency information generation method.

[0066] It should be noted that for the parts not described in detail in the embodiments of the present invention, reference may be made to the descriptions of other embodiments.

[0067] See also Figure 2 The rail transit emergency information generation method shown includes:

[0068] S201. Obtain at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each fault parameter item.

[0069] S202: Acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, and sensor data collected by at least one sensor device.

[0070] S203. For each system monitoring parameter item, compare the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item to obtain the risk parameter item and the risk parameter data corresponding to the risk parameter item.

[0071] S204, calculating according to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item, and the sensor data collected by each sensor device to obtain a predicted fault type.

[0072] S205. According to the predicted fault type, query at least one emergency resource item corresponding to the predicted fault type.

[0073] Among them, the emergency resource item can be used to describe the resources required to maintain the fault corresponding to the predicted fault type.

[0074] Specifically, different predicted fault types correspond to different emergency resource items. The number of emergency resource items corresponding to different predicted fault types may be the same or different. According to the predicted fault type, at least one emergency resource item corresponding to the predicted fault type is queried. The query method includes but is not limited to: neural network or natural language processing, etc., which is not limited in the embodiment of the present invention.

[0075] In one example, the predicted fault type is a debris flow, and the emergency resource items corresponding to the predicted fault type obtained through neural network query are maintenance tools and detection tools.

[0076] S206. For each emergency resource item, query at least one resource supply location corresponding to the emergency resource item and the resource quantity corresponding to each resource supply location according to the emergency resource item.

[0077] The resource supply location can be used to describe the location where the resources corresponding to the emergency resource item can be supplied. The resource quantity corresponding to the resource supply location can be used to describe the quantity of the resources corresponding to the emergency resource item that can be supplied.

[0078] Specifically, for each emergency resource item, the supply locations and supply quantities of different emergency resource items are not necessarily the same, and the same resource supply location may not be able to provide resources corresponding to all emergency resource items. Even if all types of emergency resource items exist, the quantity of emergency resource items that can be supplied is limited. Therefore, querying at least one resource supply location corresponding to the emergency resource item and the quantity of resources corresponding to each resource supply location based on the emergency resource item facilitates the planning of scheduling plans for each emergency resource item.

[0079] In one example, the emergency resource items are maintenance tools and detection tools. According to the query of the emergency resource item maintenance tool, the corresponding resource supply locations of the emergency resource item maintenance tool are A, which is 500 meters away from the fault location, and B, which is 1000 meters away from the fault location. The number of resources corresponding to the resource supply location of A is 5, and the number of resources corresponding to the resource supply location of B is 10. According to the query of the emergency resource item detection tool, the corresponding resource supply locations of the emergency resource item detection tool are C, which is 100 meters away from the fault location, and D, which is 800 meters away from the fault location. The number of resources corresponding to the resource supply location of C is 10, and the number of resources corresponding to the resource supply location of D is 60.

[0080] S207 . For each emergency resource item, filter among the resource supply locations corresponding to the emergency resource item to obtain the emergency supply location corresponding to the emergency resource item.

[0081] The emergency supply location may be used to describe a location where resources corresponding to the emergency resource item are to be supplied.

[0082] Specifically, for each emergency resource item, there is at least one resource supply location corresponding to the emergency resource item. However, not every supply location meets the supply requirements. The optimal supply location is selected from the resource supply locations corresponding to the emergency resource item to obtain the emergency supply location corresponding to the emergency resource item.

[0083] In one example, as described in the previous example, the resource supply locations A and B corresponding to the emergency resource item maintenance tool are screened, and the emergency supply location corresponding to the emergency resource item is obtained as location B. The resource supply locations C and D corresponding to the emergency resource item detection tool are screened, and the emergency supply location corresponding to the emergency resource item is obtained as location D.

[0084] S208. For each emergency resource item, obtain the resource quantity corresponding to the emergency supply location corresponding to the emergency resource item.

[0085] Among them, the number of resources corresponding to the emergency supply location can be used to describe the number of resources corresponding to the emergency resource item that the emergency supply location can supply.

[0086] Specifically, there is a mapping relationship between a resource supply location and the resource quantity corresponding to the resource supply location. By acquiring the resource supply location, the resource quantity corresponding to the resource supply location can be obtained. The emergency supply location is selected from the resource supply locations. Therefore, the resource quantity corresponding to the emergency resource item can be obtained through the mapping relationship corresponding to the emergency resource location.

[0087] In one example, the emergency resource item maintenance tool queries the resource supply locations corresponding to the emergency resource item maintenance tool, which are A, 500 meters away from the fault location, and B, 1000 meters away from the fault location. The number of resources corresponding to the resource supply location of A is 5, and the number of resources corresponding to the resource supply location of B is 10. The resource supply locations A and B corresponding to the emergency resource item maintenance tool are screened, and the emergency supply location corresponding to the emergency resource item is B. The number of resources corresponding to the emergency supply location B corresponding to the emergency resource item maintenance tool is 10.

[0088] S209. Obtain resource supply information corresponding to the predicted fault type according to the emergency supply locations corresponding to each emergency resource item corresponding to the predicted fault type and the resource quantities corresponding to the emergency supply locations corresponding to each emergency resource item.

[0089] Specifically, the resource supply information may be used to describe the resource supply information of each emergency resource item corresponding to the predicted fault type.

[0090] In one example, a resource supply information corresponding to the predicted fault type includes an emergency supply location corresponding to at least one emergency resource item and a resource quantity corresponding to the emergency supply location corresponding to each emergency resource item.

[0091] S210. Generate rail transit emergency information according to the predicted fault type and resource supply information corresponding to the predicted fault type.

[0092] In an embodiment of the present invention, at least one emergency resource item corresponding to the predicted fault type is queried according to the predicted fault type; for each emergency resource item, at least one resource supply location corresponding to the emergency resource item and the resource quantity corresponding to each resource supply location are queried according to the emergency resource item; for each emergency resource item, the resource supply locations corresponding to the emergency resource item are screened to obtain the emergency supply location corresponding to the emergency resource item. By screening each resource supply location, the amount of data corresponding to the resource supply location is reduced, thereby improving the efficiency of rail transit emergency information generation. For each emergency resource item, the resource quantity corresponding to the emergency supply location corresponding to the emergency resource item is obtained; according to the emergency supply location corresponding to each emergency resource item corresponding to the predicted fault type and the resource quantity corresponding to the emergency supply location corresponding to each emergency resource item, the resource supply information corresponding to the predicted fault type is obtained. Through multi-dimensional data analysis, the emergency supply locations are screened, and the resource supply is more accurate, thereby improving the accuracy of rail transit emergency information generation.

[0093] Optionally, the emergency supply location corresponding to the emergency resource item is obtained by screening among the resource supply locations corresponding to the emergency resource item, including: obtaining fault location information; for each resource supply location, calculating the distance between the resource supply location and the fault location information to obtain the supply distance corresponding to the resource supply location; calculating according to the supply distance corresponding to each resource supply location and the quantity of resources corresponding to each resource supply location to obtain at least one supply weight; selecting the maximum supply weight among the supply weights, and determining the resource supply location corresponding to the maximum supply weight as the emergency supply location corresponding to the emergency resource item.

[0094] Among them, the fault location information can be used to describe the location information of the fault location. The supply distance can be used to describe the distance between the resource supply location and the fault location information. The supply weight can be used to describe the efficiency of resource supply at the resource supply location. The maximum supply weight can be used to describe the maximum value in the supply weight.

[0095] Specifically, the higher the supply weight, the higher the efficiency of resource supply at the resource supply location, and the lower the supply weight, the lower the efficiency of resource supply at the resource supply location. At least one supply weight is obtained by calculating the supply distance corresponding to each resource supply location and the resource quantity corresponding to each resource supply location. The supply weights calculated by the supply distance corresponding to each resource supply location and the resource quantity corresponding to each resource supply location can be different or the same. The calculation method can be to find the product of the supply distance corresponding to the resource supply location and the resource quantity corresponding to the resource supply location, and the embodiment of the present invention is not limited to this.

[0096] In one example, the emergency resource item maintenance tool queries the resource supply locations corresponding to the emergency resource item maintenance tool, which are A, 500 meters away from the fault location, and B, 1000 meters away from the fault location. The number of resources corresponding to the resource supply location of location A is 5, and the number of resources corresponding to the resource supply location of location B is 10. The product of the supply distance corresponding to the resource supply location and the number of resources corresponding to the resource supply location is calculated, and the supply weight corresponding to location A is 2500, and the supply weight corresponding to location B is 10000. The resource supply locations A and B corresponding to the emergency resource item maintenance tool are screened, and the maximum supply weight of 10000 is selected from each supply weight, and the emergency supply location corresponding to the emergency resource item is location B. The resource supply location B corresponding to the maximum supply weight of 10000 is determined as the emergency supply location corresponding to the emergency resource item maintenance tool.

[0097] By obtaining fault location information; for each resource supply location, calculating the distance between the resource supply location and the fault location information, and obtaining the supply distance corresponding to the resource supply location; calculating according to the supply distance corresponding to each resource supply location and the number of resources corresponding to each resource supply location, and obtaining at least one supply weight; selecting the maximum supply weight among each supply weight, and determining the resource supply location corresponding to the maximum supply weight as the emergency supply location corresponding to the emergency resource item; by calculating the supply weight corresponding to each resource supply location, screening each resource supply location, reducing the number of resource supply locations, reducing the amount of data to be processed, and improving the efficiency of rail transit emergency information generation.

[0098] Optionally, a predicted fault type is obtained by performing calculations based on each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item, and the sensor data collected by each sensor device, including: comparing the risk parameter data corresponding to each risk parameter item with the fault parameter data corresponding to each fault parameter item corresponding to each risk parameter item corresponding to each rail transit fault type to obtain the number of type parameter items corresponding to each rail transit fault type; screening the rail transit fault type corresponding to the maximum number of type parameter items from the number of type parameter items corresponding to each rail transit fault type to determine it as the first fault type; identifying the sensor data collected by each sensor device to obtain the second fault type; if the second fault type is the same as the first fault type, determining the first fault type as the predicted fault type.

[0099] Among them, the number of type parameter items can be used to describe the number of risk parameter items whose risk parameter data corresponding to the risk parameter item and the fault parameter data corresponding to the fault parameter item corresponding to the risk parameter item are the same. The first fault type can be used to describe the type of rail transit fault predicted by analyzing the risk parameter data corresponding to the risk parameter item. The second fault type can be used to describe the type of rail transit fault predicted by sensor data.

[0100] Specifically, the risk parameter data corresponding to each risk parameter item is compared with the fault parameter data corresponding to each fault parameter item corresponding to each risk parameter item corresponding to each rail transit fault type to obtain the number of type parameter items corresponding to each rail transit fault type; the rail transit fault type corresponding to the maximum number of type parameter items in the number of type parameter items corresponding to each rail transit fault type is screened and determined as the first fault type; the sensor data collected by each sensor device is identified to obtain the second fault type; if the second fault type is the same as the first fault type, the first fault type is determined as the predicted fault type.

[0101] In one example, the rail transit fault type is a mudslide, and the fault parameter items are precipitation and foreign matter. The precipitation corresponds to 1.5 mm / h, and the foreign matter corresponds to 50%. The rail transit fault type is a large passenger flow, and the fault parameter item is passenger flow, which corresponds to 10,000 passengers / h. The risk parameter items are precipitation and foreign matter. The risk parameter data corresponding to each risk parameter item is compared with the fault parameter data corresponding to each risk parameter item corresponding to each rail transit fault type. The rail transit fault type is a mudslide, and the number of corresponding type parameter items is 2; the rail transit fault type is a large passenger flow, and the number of corresponding type parameter items is 0. The rail transit fault type corresponding to the maximum number of type parameter items 2 is selected from the number of type parameter items corresponding to each rail transit fault type, and the mudslide is determined as the first fault type; the sensor data collected by the sensor device is identified, and the second fault type identified by the video data is mudslide; if the second fault type is the same as the first fault type, the first fault type is determined as the predicted fault type.

[0102] By comparing the risk parameter data corresponding to each risk parameter item with the fault parameter data corresponding to each fault parameter item corresponding to each risk parameter item corresponding to each rail transit fault type, the number of type parameter items corresponding to each rail transit fault type is obtained; the rail transit fault type corresponding to the maximum number of type parameter items in the number of type parameter items corresponding to each rail transit fault type is screened and determined as the first fault type; by analyzing a variety of risk parameter data, the first fault type is obtained, the accuracy of fault type prediction is improved, the sensor data collected by each sensor device is identified, and the second fault type is obtained; if the second fault type is the same as the first fault type, the first fault type is determined as the predicted fault type; by analyzing the sensor data and verifying the first fault type, the accuracy of prediction is improved.

[0103] Optionally, obtaining at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each fault parameter item includes: obtaining at least one historical fault parameter item corresponding to at least one rail transit fault type and historical parameter data corresponding to each historical fault parameter item; obtaining at least one preset fault parameter item corresponding to at least one rail transit fault type and preset parameter data corresponding to each preset fault parameter item; fusing each historical fault parameter item corresponding to each rail transit fault type and historical parameter data corresponding to each historical fault parameter item, as well as each preset fault parameter item and preset parameter data corresponding to each preset fault parameter item, to obtain at least one fault parameter item corresponding to each rail transit fault type and fault parameter data corresponding to each fault parameter item.

[0104] Among them, the historical fault parameter item can be used to describe the indicators corresponding to the faults that occurred in the rail transit facilities and equipment in the past period of time. The historical parameter data can be used to describe the values ​​corresponding to the historical fault parameter items. The preset fault parameter item can be used for the indicators corresponding to the faults pre-set according to industry experience. The preset parameter data can be used to describe the values ​​corresponding to the preset fault parameter items.

[0105] Specifically, fault parameter items and fault parameter data can be obtained through information on historical faults that occurred in rail transit facilities and equipment, or can be obtained by preset evaluation indicators corresponding to faults based on industry experience. Each historical fault parameter item corresponding to each rail transit fault type and the historical parameter data corresponding to each historical fault parameter item, as well as each preset fault parameter item and the preset parameter data corresponding to each preset fault parameter item are merged, and the historical fault parameter items and preset fault parameter items corresponding to the same fault type are merged, and parameter items with the same content are merged, and parameter items with different contents are spliced. The parameter data corresponding to the same parameter item are merged, and the numerical values ​​corresponding to the same parameter item are saved as a data set, so as to obtain at least one fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item.

[0106] In an example, the rail transit fault type is a mudslide, and the historical fault parameter item corresponding to the rail transit fault type is precipitation, and the historical parameter data corresponding to the historical fault parameter item is greater than 1.5 mm / h; the preset fault parameter item corresponding to the rail transit fault type is the amount of foreign matter, and the preset parameter data corresponding to the preset fault parameter item is greater than 50%; the historical fault parameter items corresponding to the rail transit fault type and the historical parameter data corresponding to each historical fault parameter item, as well as each preset fault parameter item and the preset parameter data corresponding to each preset fault parameter item are fused to obtain the fault parameter items corresponding to the rail transit fault type as precipitation and foreign matter, the fault parameter data corresponding to the precipitation is greater than 1.5 mm / h, and the fault parameter data corresponding to the foreign matter amount is greater than 50%.

[0107] By obtaining at least one historical fault parameter item corresponding to at least one rail transit fault type and historical parameter data corresponding to each historical fault parameter item; obtaining at least one preset fault parameter item corresponding to at least one rail transit fault type and preset parameter data corresponding to each preset fault parameter item; fusing each historical fault parameter item corresponding to each rail transit fault type and historical parameter data corresponding to each historical fault parameter item, as well as each preset fault parameter item and preset parameter data corresponding to each preset fault parameter item, at least one fault parameter item corresponding to each rail transit fault type and fault parameter data corresponding to each fault parameter item are obtained, and by combining information on historical faults with information on preset faults based on industry experience, an evaluation index for rail transit fault types is generated, so that the fault classification result is more accurate, the accuracy of fault type prediction is improved, and thus the accuracy of rail transit emergency information generation is improved.

[0108] Optionally, after generating rail transit emergency information based on the predicted fault type and the resource supply information corresponding to the predicted fault type, it also includes: obtaining the contact information of the commander; querying the fault warning range corresponding to the predicted fault type based on the predicted fault type; filtering the emergency personnel contact information in the commander's contact information based on the fault location information and the fault warning range; and sending the rail transit emergency information corresponding to the fault location information and the predicted fault type to the emergency personnel based on the emergency personnel contact information, so that the emergency personnel can perform fault maintenance.

[0109] Among them, the contact information of the commander can be used to describe the communication information of the personnel who can perform maintenance on the rail transit facilities and equipment after the failure occurs during the operation. The fault warning range can be used to describe the range within which the fault can be maintained in time. The contact information of the emergency personnel can be used to describe the communication information of the personnel who perform maintenance on the fault within the fault warning range. Emergency personnel can be used to describe the personnel corresponding to the contact information of the emergency personnel.

[0110] Specifically, the contact information of the commander is obtained, and the acquisition method includes but is not limited to: interpolation search algorithm, Fibonacci search algorithm or tree table search algorithm, etc., and the embodiment of the present invention does not limit this. According to the predicted fault type, query the fault warning range corresponding to the predicted fault type. Different predicted fault types have different corresponding fault warning ranges. For example, when encountering heavy rain, the fault warning range is a circle 500 meters away from the fault location. When encountering mudslides, the fault warning range is a circle 2000 meters away from the fault location. According to the fault location information and the fault warning range, the emergency personnel contact information is filtered in the commander's contact information. According to the emergency personnel contact information, the fault location information and the rail transit emergency information corresponding to the predicted fault type are sent to the emergency personnel, so that the emergency personnel can perform fault maintenance.

[0111] In one example, the contact information of the commander is obtained through the interpolation search algorithm. The predicted fault type is a mudslide. When a mudslide occurs, the fault warning range is a circle 2000 meters away from the fault location.

[0112] By predicting the fault type, querying the fault warning range corresponding to the predicted fault type, filtering the emergency personnel contact information in the commander's contact information according to the fault location information and the fault warning range, sending the rail transit emergency information corresponding to the fault location information and the predicted fault type to the emergency personnel so that the emergency personnel can perform fault maintenance, and judging the number of emergency personnel required by predicting the fault type, thereby obtaining the fault warning range, filtering the commander's contact information according to the warning range, and selecting different emergency personnel for different faults. The screening method is more refined, which improves the accuracy of emergency personnel screening and the efficiency of rail transit emergency handling.

[0113] Optionally, after generating rail transit emergency information based on the predicted fault type and the resource supply information corresponding to the predicted fault type, it also includes: obtaining at least one recovery parameter item and recovery parameter data corresponding to each recovery parameter item; obtaining a recovery threshold corresponding to each recovery parameter item; for each recovery parameter item, comparing the recovery parameter data corresponding to the recovery parameter item with the recovery threshold corresponding to the recovery parameter item to obtain a recovery comparison result; for each recovery comparison result, querying a time optimization plan and an equipment optimization plan corresponding to the recovery comparison result; for each recovery comparison result, optimizing the rail transit emergency information through the time optimization plan and the equipment optimization plan corresponding to the recovery comparison result.

[0114] Among them, the recovery parameter item can be used to describe the detection index of the recovery status of the fault occurred in the rail transit facility equipment. The recovery parameter data can be used to describe the value corresponding to the recovery parameter item. The recovery threshold can be used to describe the threshold corresponding to the recovery parameter item. The recovery comparison result can be used to describe the result of comparing the recovery parameter data corresponding to the recovery parameter item with the recovery threshold corresponding to the recovery parameter item. The time optimization scheme can be used to describe the method of reducing the recovery time of the fault occurred in the rail transit facility equipment. The equipment optimization scheme is used to describe the method of equipment optimization when recovering from the fault occurred in the rail transit facility equipment.

[0115] Specifically, detect the recovery status of the operation of rail transit facilities and equipment after the execution of rail transit emergency information. Detect the recovery status of the operation of rail transit facilities and equipment through various recovery parameter items. Obtain at least one recovery parameter item and the recovery parameter data corresponding to each recovery parameter item; obtain the recovery threshold corresponding to each recovery parameter item; for each recovery parameter item, compare the recovery parameter data corresponding to the recovery parameter item with the recovery threshold corresponding to the recovery parameter item to obtain a recovery comparison result; for each recovery comparison result, query the time optimization plan and equipment optimization plan corresponding to the recovery comparison result; for each recovery comparison result, optimize the rail transit emergency information through the time optimization plan and equipment optimization plan corresponding to the recovery comparison result.

[0116] In an example, the recovery parameter item obtained is the recovery time, and the recovery parameter data corresponding to the recovery parameter item is 10 hours; the recovery threshold corresponding to the recovery parameter item is obtained as 8 hours; for the recovery parameter item, the recovery parameter data corresponding to the recovery parameter item is compared with the recovery threshold corresponding to the recovery parameter item, and the recovery comparison result is that the recovery time is longer; for the recovery comparison result, the time optimization plan corresponding to the query recovery comparison result is to modify the sequential search algorithm of the fault parameter item and the fault parameter data corresponding to the query rail transit fault type to a binary search algorithm, and the equipment optimization plan is to double the number of transport resource vehicles; for the recovery comparison result, the rail transit emergency information is optimized through the time optimization plan and the equipment optimization plan corresponding to the recovery comparison result.

[0117] By obtaining at least one recovery parameter item and the recovery parameter data corresponding to each recovery parameter item; obtaining the recovery threshold corresponding to each recovery parameter item; for each recovery parameter item, comparing the recovery parameter data corresponding to the recovery parameter item with the recovery threshold corresponding to the recovery parameter item to obtain a recovery comparison result; for each recovery comparison result, querying the time optimization plan and the equipment optimization plan corresponding to the recovery comparison result; for each recovery comparison result, optimizing the rail transit emergency information through the time optimization plan and the equipment optimization plan corresponding to the recovery comparison result, the rail transit emergency information can be evaluated according to the recovery parameter items, the accuracy and efficiency of the rail transit emergency information can be obtained, and targeted optimization operations can be performed according to the evaluation results to improve the accuracy and efficiency of the rail transit emergency information.

[0118] Embodiment 3

[0119] Figure 3 This is a schematic diagram of the structure of a rail transit emergency information generation device provided in Embodiment 3 of the present invention. The embodiment of the present invention can be applied to the situation of rail transit emergency information generation, the device can use the rail transit emergency information generation method, the device can be implemented in the form of hardware and / or software, and the device can be configured in the rail transit emergency information generation device.

[0120] See also Figure 3 The rail transit emergency information generating device shown includes: a fault data acquisition module 301, a monitoring data acquisition module 302, a risk data acquisition module 303, a prediction type acquisition module 304, a supply information acquisition module 305 and an emergency information generating module 306, wherein:

[0121] A fault data acquisition module 301 is used to obtain at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each fault parameter item;

[0122] A monitoring data acquisition module 302, used to acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, and sensor data collected by at least one sensor device;

[0123] The risk data acquisition module 303 is used to compare the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item for each system monitoring parameter item, so as to obtain the risk parameter item and the risk parameter data corresponding to the risk parameter item;

[0124] The prediction type acquisition module 304 is used to calculate according to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item, and the sensor data collected by each sensor device to obtain the predicted fault type;

[0125] The supply information acquisition module 305 is used to obtain resource supply information corresponding to the predicted fault type;

[0126] The emergency information generation module 306 is used to generate rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type.

[0127] The technical solution of the embodiment of the present invention can improve the accuracy of fault type analysis by performing fault type analysis through multi-dimensional data by obtaining fault parameter items corresponding to multiple fault types and fault parameter data corresponding to the fault parameter items. At least one system monitoring parameter item and system monitoring parameter data corresponding to each system monitoring parameter item, as well as sensor data collected by at least one sensor device, are obtained, the system monitoring data and the sensor data are obtained, and the operating status of rail transit facilities and equipment is monitored in real time through multi-dimensional data to obtain the real-time operating status of rail transit facilities and equipment. For each system monitoring parameter item, the system monitoring parameter data corresponding to the system monitoring parameter item is compared with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item, and the risk parameter item and the risk parameter data corresponding to the risk parameter item are obtained, so that the fault condition of rail transit facilities and equipment can be detected in time, and the efficiency of rail transit emergency handling can be improved. According to each fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item, each risk parameter item and the risk parameter data corresponding to each risk parameter item and the sensor data collected by each sensor device, calculation is performed to obtain the predicted fault type, and the resource supply information corresponding to the predicted fault type is obtained in real time; according to the predicted fault type and the resource supply information corresponding to the predicted fault type, rail transit emergency information is generated, the fault of rail transit facilities and equipment can be predicted in time, and the resource supply information of the fault can be obtained in time, thereby improving the efficiency of generating rail transit emergency information.

[0128] Optionally, the supply information acquisition module 305 includes:

[0129] A resource item acquisition unit, configured to query at least one emergency resource item corresponding to the predicted fault type according to the predicted fault type;

[0130] A resource query unit, configured to query, for each emergency resource item, at least one resource supply location corresponding to the emergency resource item and the quantity of resources corresponding to each resource supply location according to the emergency resource item;

[0131] A location screening unit, for screening each emergency resource item among various resource supply locations corresponding to the emergency resource item, to obtain the emergency supply location corresponding to the emergency resource item;

[0132] A quantity acquisition unit, used for acquiring, for each emergency resource item, the resource quantity corresponding to the emergency supply location corresponding to the emergency resource item;

[0133] The resource information determination unit is used to obtain resource supply information corresponding to the predicted fault type according to the emergency supply locations corresponding to the emergency resource items corresponding to the predicted fault type and the resource quantities corresponding to the emergency supply locations corresponding to the emergency resource items.

[0134] Optional, location filter unit, specifically used to:

[0135] Obtain fault location information;

[0136] For each resource supply location, calculate the distance between the resource supply location and the fault location information to obtain the supply distance corresponding to the resource supply location;

[0137] Calculate at least one supply weight according to the supply distance corresponding to each resource supply location and the resource quantity corresponding to each resource supply location;

[0138] The maximum supply weight is selected from among the supply weights, and the resource supply location corresponding to the maximum supply weight is determined as the emergency supply location corresponding to the emergency resource item.

[0139] Optionally, the prediction type acquisition module 304 is specifically used to:

[0140] Compare the risk parameter data corresponding to each risk parameter item with the fault parameter data corresponding to each fault parameter item corresponding to each risk parameter item corresponding to each rail transit fault type, and obtain the number of type parameter items corresponding to each rail transit fault type;

[0141] The rail transit fault type corresponding to the maximum number of type parameter items is selected from the number of type parameter items corresponding to each rail transit fault type and is determined as the first fault type;

[0142] Identify the sensor data collected by each sensor device to obtain a second fault type;

[0143] If the second fault type is the same as the first fault type, the first fault type is determined as the predicted fault type.

[0144] Optionally, the fault data acquisition module 301 is specifically used for:

[0145] Acquire at least one historical fault parameter item corresponding to at least one rail transit fault type and historical parameter data corresponding to each historical fault parameter item;

[0146] Acquire at least one preset fault parameter item corresponding to at least one rail transit fault type and preset parameter data corresponding to each preset fault parameter item;

[0147] Each historical fault parameter item corresponding to each rail transit fault type and the historical parameter data corresponding to each historical fault parameter item, as well as each preset fault parameter item and the preset parameter data corresponding to each preset fault parameter item are merged to obtain at least one fault parameter item corresponding to each rail transit fault type and the fault parameter data corresponding to each fault parameter item.

[0148] Optionally, the rail transit emergency information generating device further includes:

[0149] A personnel information acquisition module, used to acquire the contact information of the commanding personnel after generating rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type;

[0150] A range query module is used to query the fault warning range corresponding to the predicted fault type according to the predicted fault type;

[0151] An information screening module is used to screen the emergency personnel contact information from the command personnel contact information according to the fault location information and the fault warning range;

[0152] The information sending module is used to send the rail transit emergency information corresponding to the fault location information and the predicted fault type to the emergency personnel according to the emergency personnel contact information, so that the emergency personnel can perform fault maintenance.

[0153] Optionally, the rail transit emergency information generating device further includes:

[0154] A recovery data acquisition module, used to acquire at least one recovery parameter item and recovery parameter data corresponding to each recovery parameter item after generating rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type;

[0155] A threshold acquisition module is used to obtain the restoration threshold corresponding to each restoration parameter item;

[0156] A result acquisition module is used to compare the recovery parameter data corresponding to the recovery parameter item with the recovery threshold value corresponding to the recovery parameter item for each recovery parameter item to obtain a recovery comparison result;

[0157] The optimization scheme acquisition module is used to query the time optimization scheme and the equipment optimization scheme corresponding to each recovery comparison result;

[0158] The information optimization module is used to optimize rail transit emergency information according to the time optimization plan and equipment optimization plan corresponding to each recovery comparison result.

[0159] The rail transit emergency information generating device provided in the embodiment of the present invention can execute the rail transit emergency information generating method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the rail transit emergency information generating method.

[0160] Embodiment 4

[0161] Figure 4 A schematic structural diagram of a rail transit emergency information generating device 400 that can be used to implement an embodiment of the present invention is shown.

[0162] like Figure 4As shown, the rail transit emergency information generating device 400 includes at least one processor 401, and a memory connected to the at least one processor 401, such as a read-only memory (ROM) 402, a random access memory (RAM) 403, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 401 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 402 or the computer program loaded from the storage unit 408 to the random access memory (RAM) 403. In RAM403, various programs and data required for the operation of the rail transit emergency information generating device 400 can also be stored. The processor 401, ROM402 and RAM403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0163] Multiple components in the rail transit emergency information generating device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the rail transit emergency information generating device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0164] The processor 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 401 executes the various methods and processes described above, such as a rail transit emergency information generation method.

[0165] In some embodiments, the rail transit emergency information generation method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the rail transit emergency information generation device 400 via ROM402 and / or communication unit 409. When the computer program is loaded into RAM403 and executed by processor 401, one or more steps of the rail transit emergency information generation method described above may be performed. Alternatively, in other embodiments, processor 401 may be configured to execute the rail transit emergency information generation method in any other appropriate manner (e.g., by means of firmware).

[0166] 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 chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0167] Computer programs for implementing 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, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0168] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0169] In order to provide interaction with the user, the systems and techniques described herein can be implemented on a rail transit emergency information generation device, which has: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or trackball), through which the user can provide input to the rail transit emergency information generation device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and the input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0170] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0171] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS (Virtual Private Server) services.

[0172] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0173] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A rail transit emergency information generation method, characterized in that: The method comprises: Obtaining at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each of the fault parameter items; Acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each of the system monitoring parameter items, and sensor data collected by at least one sensor device; For each of the system monitoring parameter items, comparing the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item to obtain a risk parameter item and the risk parameter data corresponding to the risk parameter item; Calculate according to each of the fault parameter items corresponding to each of the rail transit fault types and the fault parameter data corresponding to each of the fault parameter items, each of the risk parameter items and the risk parameter data corresponding to each of the risk parameter items, and the sensor data collected by each of the sensor devices to obtain a predicted fault type; Obtaining resource supply information corresponding to the predicted fault type; Rail transit emergency information is generated according to the predicted fault type and resource supply information corresponding to the predicted fault type.

2. The method according to claim 1, characterized in that The obtaining of resource supply information corresponding to the predicted fault type includes: According to the predicted fault type, query at least one emergency resource item corresponding to the predicted fault type; For each of the emergency resource items, query at least one resource supply location corresponding to the emergency resource item and the resource quantity corresponding to each of the resource supply locations according to the emergency resource item; For each of the emergency resource items, screening among the resource supply locations corresponding to the emergency resource item to obtain the emergency supply location corresponding to the emergency resource item; For each of the emergency resource items, obtaining the resource quantity corresponding to the emergency supply location corresponding to the emergency resource item; Resource supply information corresponding to the predicted fault type is obtained according to the emergency supply locations corresponding to each of the emergency resource items corresponding to the predicted fault type and the resource quantities corresponding to the emergency supply locations corresponding to each of the emergency resource items.

3. The method according to claim 2, characterized in that The screening among the resource supply locations corresponding to the emergency resource item to obtain the emergency supply location corresponding to the emergency resource item includes: Obtain fault location information; For each of the resource supply locations, calculating the distance between the resource supply location and the fault location information to obtain the supply distance corresponding to the resource supply location; Calculating according to the supply distance corresponding to each of the resource supply locations and the quantity of resources corresponding to each of the resource supply locations to obtain at least one supply weight; A maximum supply weight is selected from among the supply weights, and a resource supply location corresponding to the maximum supply weight is determined as the emergency supply location corresponding to the emergency resource item.

4. The method according to claim 1, characterized in that: The method of calculating according to each of the fault parameter items corresponding to each of the rail transit fault types and the fault parameter data corresponding to each of the fault parameter items, each of the risk parameter items and the risk parameter data corresponding to each of the risk parameter items, and the sensor data collected by each of the sensor devices to obtain a predicted fault type includes: Compare the risk parameter data corresponding to each of the risk parameter items with the fault parameter data corresponding to each of the fault parameter items corresponding to each of the risk parameter items corresponding to each of the rail transit fault types to obtain the number of type parameter items corresponding to each of the rail transit fault types; The rail transit fault type corresponding to the maximum number of type parameter items is selected from the number of type parameter items corresponding to each of the rail transit fault types, and is determined as the first fault type; Identify the sensor data collected by each of the sensor devices to obtain a second fault type; If the second fault type is the same as the first fault type, the first fault type is determined as a predicted fault type.

5. The method according to claim 1, characterized in that The obtaining of at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each of the fault parameter items includes: Acquire at least one historical fault parameter item corresponding to at least one rail transit fault type and historical parameter data corresponding to each of the historical fault parameter items; Acquire at least one preset fault parameter item corresponding to at least one rail transit fault type and preset parameter data corresponding to each of the preset fault parameter items; The historical fault parameter items corresponding to each of the rail transit fault types and the historical parameter data corresponding to each of the historical fault parameter items, as well as the preset fault parameter items and the preset parameter data corresponding to each of the preset fault parameter items are merged to obtain at least one fault parameter item corresponding to each of the rail transit fault types and the fault parameter data corresponding to each of the fault parameter items.

6. The method according to claim 1, characterized in that After generating rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type, the method further includes: Obtain command staff contact information; According to the predicted fault type, query the fault warning range corresponding to the predicted fault type; Filtering the emergency personnel contact information from the command personnel contact information according to the fault location information and the fault warning range; According to the emergency personnel contact information, the fault location information and rail transit emergency information corresponding to the predicted fault type are sent to the emergency personnel, so that the emergency personnel can perform fault maintenance.

7. The method according to claim 1, characterized in that After generating rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type, the method further includes: Acquire at least one recovery parameter item and recovery parameter data corresponding to each of the recovery parameter items; Obtaining a recovery threshold corresponding to each of the recovery parameter items; For each of the restoration parameter items, comparing the restoration parameter data corresponding to the restoration parameter item with the restoration threshold value corresponding to the restoration parameter item to obtain a restoration comparison result; For each of the recovery comparison results, query the time optimization plan and the equipment optimization plan corresponding to the recovery comparison result; For each of the recovery comparison results, the rail transit emergency information is optimized through the time optimization plan and the equipment optimization plan corresponding to the recovery comparison result.

8. A rail transit emergency information generating device, characterized in that: The device comprises: A fault data acquisition module, used to obtain at least one fault parameter item corresponding to at least one rail transit fault type and fault parameter data corresponding to each of the fault parameter items; A monitoring data acquisition module, used to acquire at least one system monitoring parameter item and system monitoring parameter data corresponding to each of the system monitoring parameter items, and sensor data collected by at least one sensor device; a risk data acquisition module, for comparing, for each of the system monitoring parameter items, the system monitoring parameter data corresponding to the system monitoring parameter item with the fault parameter data of the fault parameter item corresponding to the system monitoring parameter item, to obtain the risk parameter item and the risk parameter data corresponding to the risk parameter item; A prediction type acquisition module, used to calculate according to each of the fault parameter items corresponding to each of the rail transit fault types and the fault parameter data corresponding to each of the fault parameter items, each of the risk parameter items and the risk parameter data corresponding to each of the risk parameter items, and the sensor data collected by each of the sensor devices, to obtain a predicted fault type; A supply information acquisition module, used to acquire resource supply information corresponding to the predicted fault type; The emergency information generation module is used to generate rail transit emergency information according to the predicted fault type and the resource supply information corresponding to the predicted fault type.

9. A rail transit emergency information generating device, characterized in that: The device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the rail transit emergency information generation method described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the rail transit emergency information generation method according to any one of claims 1 to 7 when executed.

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