Operation and maintenance data management method, device and equipment for urban rail train door opening and closing scene and storage medium

Abstract

The invention discloses an operation and maintenance data management method, device and equipment for an urban rail train door opening and closing scene and a storage medium. The method comprises the following steps: collecting real-time operation and maintenance data of an urban rail train door opening and closing scene; time stamps are marked on the real-time operation and maintenance data; obtaining historical operation and maintenance data of the door opening and closing scene according to the real-time operation and maintenance data marked with the timestamps and the data based on the table relational database; preprocessing the historical operation and maintenance data, and constructing a knowledge ontology according to the preprocessed historical operation and maintenance data; constructing an operation and maintenance knowledge base according to the knowledge ontology and the real-time operation and maintenance data; the operation and maintenance knowledge base constructed by the method can flexibly cope with continuously changing data structures and complex data volumes, dynamic generation of new data can be updated in real time, and the expansibility is higher.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance data processing of urban rail trains, and particularly to an operation and maintenance data management method, device, equipment, and storage medium for the door opening and closing scenarios of urban rail trains. Background Art

[0002] In the development and application of urban rail transit, the door opening and closing state of urban rail trains directly determines the safety and stability of train operation, making the operation and maintenance of doors a key research object. When urban rail trains are in operation, a large amount of operation and maintenance data is generated for the door opening and closing state, which is characterized by a large scale and a wide coverage range. Therefore, operation and maintenance big data urgently needs to be processed and analyzed through intelligent methods.

[0003] Currently, traditional data storage and management methods use relational database software to collect data sets. However, relational databases based on tables have poor query performance when dealing with deep association relationships, require table adjustment and schema migration when facing frequently changing data structures, and have low scalability.

[0004] The information disclosed in this background art section is only intended to enhance the overall understanding of the present invention and should not be regarded as an admission or any form of suggestion that this information constitutes prior art already known to those of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to flexibly cope with changing data structures and have scalability when facing complex data volumes.

[0006] The present invention provides an operation and maintenance data management method for the door opening and closing scenarios of urban rail trains, including the steps of:

[0007] S11. Collect real-time operation and maintenance data for the door opening and closing scenarios of urban rail trains; and mark timestamps for the real-time operation and maintenance data;

[0008] S12. Obtain historical operation and maintenance data for the door opening and closing scenarios based on the real-time operation and maintenance data marked with timestamps and data based on a table relational database; wherein, the data based on the table relational database is: converting the original data stored in the table relational database into data with the same timestamp format as the real-time operation and maintenance data;

[0009] S13. Preprocess the historical operation and maintenance data, and construct a knowledge ontology based on the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships;

[0010] S14. Construct an operation and maintenance knowledge base based on the knowledge ontology and the real-time operation and maintenance data.

[0011] Preferably, in the embodiment of the present invention, it further includes:

[0012] S15. Retrieve the historical operation and maintenance data and the real-time operation and maintenance data according to the operation and maintenance knowledge base.

[0013] Preferably, in the embodiment of the present invention, the acquisition of the real-time operation and maintenance data of the urban rail transit train door opening and closing scenario includes:

[0014] Based on sensors, acquire the operation and maintenance data of the rotation speed, torque, and rotation angle of the urban rail transit train door opening and closing; and obtain the door number, equipment SN number, door opening and closing time, and door state of the urban rail transit train door.

[0015] Preferably, in the embodiment of the present invention, the preprocessing of the historical operation and maintenance data includes: performing structured processing on the historical operation and maintenance data; and obtaining the data structure and data content.

[0016] Preferably, in the embodiment of the present invention, constructing the knowledge ontology includes:

[0017] Define the ontology for knowledge extraction according to the data structure and the data content; the ontology includes: the urban rail transit train door and the operation and maintenance data;

[0018] According to the extracted knowledge ontology, organize and define the entity, the entity attribute, and the entity relationship, and store them in the graph database.

[0019] Preferably, in the embodiment of the present invention, constructing the operation and maintenance knowledge base includes:

[0020] Establish a connection with the graph database through the Graph function, and use the Node() function to create the entities of the urban rail transit train door and the operation and maintenance data;

[0021] Form entities from the information of the urban rail transit train door and the corresponding operation and maintenance data and write them into the operation and maintenance knowledge base;

[0022] Write the data information other than the information of the urban rail transit train door and the data generated during the corresponding operation and maintenance process as the attributes of the entity into the operation and maintenance knowledge base;

[0023] Use the Relationship function to create the relationship between the urban rail transit train door and the operation and maintenance data, and provide timestamp information with the door opening and closing time as the attribute of the relationship.

[0024] On the other hand of the present invention, there is also provided an operation and maintenance data management device for the urban rail transit train door opening and closing scenario, including:

[0025] A real-time operation and maintenance data acquisition unit, configured to acquire the real-time operation and maintenance data of the urban rail transit train door opening and closing scenario; and mark a timestamp for the real-time operation and maintenance data;

[0026] A historical operation and maintenance data generation unit, configured to obtain historical operation and maintenance data of the door opening and closing scenario according to the real-time operation and maintenance data marked with timestamps and the data based on a relational database; wherein, the data based on the relational database is: converting the original data stored in the relational database into data with the same timestamp format as the real-time operation and maintenance data;

[0027] A knowledge ontology construction unit, configured to preprocess the historical operation and maintenance data and construct a knowledge ontology according to the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships;

[0028] An operation and maintenance knowledge base construction unit, configured to construct an operation and maintenance knowledge base according to the knowledge ontology and the real-time operation and maintenance data.

[0029] Preferably, in an embodiment of the present invention, it further includes:

[0030] A retrieval unit, configured to retrieve the historical operation and maintenance data and the real-time operation and maintenance data according to the operation and maintenance knowledge base.

[0031] On the other hand of the embodiment of the present invention, there is also provided an operation and maintenance data management device for the door opening and closing scenario of urban rail trains; the operation and maintenance data management device for the door opening and closing scenario of urban rail trains includes a computer program stored on a medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer is made to execute the methods described in the above aspects and achieve the same technical effects.

[0032] On the other hand of the embodiment of the present invention, there is also provided a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it realizes each step of the operation and maintenance data management method for the door opening and closing scenario of urban rail trains as described in any one of the above.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] In the present invention, first, the real-time operation and maintenance data of the door opening and closing scenario of urban rail trains is collected; and timestamps are marked on the real-time operation and maintenance data; secondly, the historical operation and maintenance data of the door opening and closing scenario is obtained according to the real-time operation and maintenance data marked with timestamps and the data based on a relational database; then the historical operation and maintenance data is preprocessed, and a knowledge ontology is constructed according to the preprocessed historical operation and maintenance data; finally, an operation and maintenance knowledge base is constructed according to the knowledge ontology and the real-time operation and maintenance data; the operation and maintenance knowledge base constructed by the present invention can flexibly cope with the continuously changing data structure and complex data volume, and can be updated in real time for the dynamically generated new data, and has stronger scalability.

[0035] Furthermore, the knowledge ontology constructed by the present invention makes the operation and maintenance data more understandable and operable.

[0036] Furthermore, the present invention provides a query and retrieval method based on knowledge graph technology, enabling users to quickly locate the required operation and maintenance data through multiple information query methods, significantly improving data utilization rate and facilitating the daily work of operation and maintenance personnel.

[0037] In addition, the present invention provides important support for the intelligent operation and maintenance of urban rail trains. Based on this application, big data analysis and intelligent retrieval can be carried out, which not only improves the operation and maintenance efficiency, but also promotes the implementation of intelligent decision-making and improves the reliability and automation level of urban rail train operation and maintenance.

[0038] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and be able to implement it according to the content of the specification, and in order to make the above and other purposes, technical features and advantages of the present invention more understandable, one or more preferred embodiments are listed below and described in detail with reference to the accompanying drawings as follows. Brief Description of the Drawings

[0039] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0040] Figure 1 is the step diagram of the operation and maintenance data management method for the urban rail train door opening and closing scenario described in the present invention;

[0041] Figure 2 is the schematic diagram of the operation and maintenance knowledge triple described in the present invention;

[0042] Figure 3 is the schematic diagram of the triple query for door number query described in the present invention;

[0043] Figure 4 is the schematic diagram of the triple query for data ID query described in the present invention;

[0044] Figure 5 is the schematic diagram of the triple query for door opening and closing time query described in the present invention;

[0045] Figure 6 is the structural schematic diagram of the operation and maintenance data management device for the urban rail train door opening and closing scenario described in the present invention;

[0046] Figure 7 is the structural schematic diagram of the operation and maintenance data management equipment for the urban rail train door opening and closing scenario described in the present invention. Detailed Embodiments

[0047] The following will describe in detail the specific embodiments of the present invention with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0048] Unless otherwise clearly stated, in the whole specification and claims, the term "comprising"

[0049] or its variations such as "including" or "comprising" etc. will be understood to include the stated elements or components, without excluding other elements or other components.

[0050] In this article, the terms "first", "second", etc. are used to distinguish two different elements or parts, and are not used to limit a specific position or relative relationship. In other words, in some embodiments, the terms "first", "second", etc. can also be interchanged with each other.

[0051] Embodiment 1

[0052] In order to flexibly respond to changing data structures and have scalability when facing complex data volumes, as Figure 1 shown, in the embodiment of the present invention, a method for managing operation and maintenance data for the door opening and closing scenario of urban rail trains is provided, including the steps:

[0053] S11. Collect the real-time operation and maintenance data of the door opening and closing scenario of urban rail trains; and mark the time stamp for the real-time operation and maintenance data;

[0054] In the embodiment of the present invention, based on sensors, the operation and maintenance data of the rotation speed, torque, and rotation angle of the door opening and closing of urban rail trains are collected; and the door number, device SN number, door opening and closing time, and door state of the urban rail train door are obtained, and a process of one door opening or closing is taken as a set of data, the data ID is marked, and the operation and maintenance data of the rotation speed, torque, and rotation angle are recorded in the form of an array.

[0055] When collecting the real-time operation and maintenance data, the time at the first moment of door opening or closing is marked as the time stamp.

[0056] S12. Obtain the historical operation and maintenance data of the door opening and closing scenario according to the real-time operation and maintenance data marked with the time stamp and the data based on the relational database; wherein, the data based on the relational database is: converting the data originally stored in the relational database into data with the same format as the time stamp of the real-time operation and maintenance data;

[0057] In the embodiments of the present invention, the historical operation and maintenance data of the door opening and closing scenario mainly includes two types: one is the real-time operation and maintenance data collected in the door opening and closing operation and maintenance scenario in step S11. When collecting the real-time operation and maintenance data, the time of the first moment of door opening or closing is marked as the timestamp; the real-time operation and maintenance data is defined as historical data; the second type is the data originally stored in the table-based relational database. Such data usually has information with a time dimension, and it is converted into data with the same format as the timestamp of the real-time operation and maintenance data for preparing further data processing and storage.

[0058] S13. Preprocess the historical operation and maintenance data, and construct a knowledge ontology based on the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships.

[0059] In the embodiments of the present invention, preprocessing the historical operation and maintenance data includes: performing structured processing on the historical operation and maintenance data; and obtaining the data structure and data content.

[0060] Specifically, based on Python, read the historical operation and maintenance data obtained in the above steps, perform data processing on the historical operation and maintenance data, structure the historical data in the background and obtain the data content. By calling the csv library, read the files under the data storage path, and by separating the arrays within each group of data, obtain data information such as data ID, door number of the car door, device SN number, door opening and closing time and status, rotation speed, torque, and rotation angle of door opening and closing, as shown in Table 1 below:

[0061] Table 1

[0062] Data Structure Data Content Data ID Such as, 1 Door Number Such as, CQ010410408 Device SN Number Such as, 2003130041700408 Door Opening / Closing Time Such as, 2022-04-26 22:40:27.478 Door Opening / Closing Status 0 for opening, 1 for closing Whether the data is abnormal 0 for normal, 1 for fault, 2 - 4 for abnormal Door Data Status 0 for sub - healthy, 1 for normal, 2 for debugging Station ID Such as, 0 Up / Down Status 0 for down - bound, 1 for up - bound, 2 for platform door Original Rotation Speed Data Such as, [1,329,1168,1357,1352,1302,…] Original Torque Data Such as, [131,120,74,53,61,72,71,65,238,…] Original Angle of Rotation Data Such as, [6,17,27,39,51,61,71,80,87,94,…]

[0063] Constructing the knowledge ontology is specifically as follows:

[0064] According to the analysis of the data structure and data content shown in Table 1, the historical data in the operation and maintenance process mainly includes two types of objects, namely the urban rail transit train doors from which data is collected and the data collected for corresponding door opening and closing. Therefore, the main ontology objects for knowledge extraction are defined as urban rail transit train doors and operation and maintenance data. Therefore, the ontology includes two types of entities, namely urban rail transit train doors and operation and maintenance data, and stores and manages knowledge in the Neo4j graph database. Establish the relationship between entities with the door opening and closing time as the relationship, and store the information of the urban rail transit train doors and the data information other than the data generated during the corresponding operation and maintenance process as the attributes of the entities in the Neo4j graph database.

[0065] S14. Construct an operation and maintenance knowledge base based on the knowledge ontology and the real-time operation and maintenance data.

[0066] In the embodiments of the present invention, constructing the operation and maintenance knowledge base includes:

[0067] Establish a connection with the graph database through the Graph function, and use the Node() function to create the urban rail train door and operation and maintenance data entities;

[0068] Form an entity with the information of the urban rail train door and the corresponding operation and maintenance data and write it into the operation and maintenance knowledge base;

[0069] Take the data information other than the information of the urban rail train door and the data generated during the corresponding operation and maintenance process as the attributes of the entity and write them into the operation and maintenance knowledge base;

[0070] Use the Relationship function to create the relationship between the urban rail train door and the operation and maintenance data, and provide timestamp information with the door opening and closing time as the attribute of the relationship.

[0071] Specifically, the main implementation of building the operation and maintenance knowledge base for the urban rail train door opening and closing operation and maintenance scenario has two key objectives: to solve the management requirements of operation and maintenance data and efficient data and knowledge retrieval. For the operation and maintenance data of the door opening and closing scenario, based on Python, call the csv library to read the operation and maintenance data and structure the historical data of the processed data. Specifically, it includes splitting the data information in the csv file into an array through ",", and obtaining the data ID, door number, device SN number, door opening and closing time, etc. of each historical data; then call the py2neo library to establish a connection with the background Neo4j graph database through the Graph() function, use the Node() function to create two types of entities, the door and the operation and maintenance data, form an entity with the door information and the data generated during its operation and maintenance process and write it into the operation and maintenance knowledge base, store the remaining data information as the attributes of the entity, and use the Relationship() function to create the relationship between the door and the operation and maintenance data, and provide timestamp information with the door opening and closing time as the attribute of the relationship.

[0072] In Neo4j, the brown entity represents the door, the green entity represents the data with normal door data status, and the orange entity represents the data with sub-healthy door data status, specifically as Figure 2 shown in the operation and maintenance knowledge triple. Based on the Neo4j graph database, it can be intuitively seen that more than 99% of the door data is in a normal state, and only part of the time is in a sub-healthy state.

[0073] Preferably, in the embodiment of the present invention, it further includes:

[0074] S15. Retrieve the historical operation and maintenance data and the real-time operation and maintenance data according to the operation and maintenance knowledge base.

[0075] In the embodiments of the present invention, in order to call the operation and maintenance knowledge base to effectively manage and retrieve operation and maintenance data, Cypher statements are formulated based on the construction rules of the operation and maintenance knowledge base. The stored historical data and real-time data need to be further retrieved and applied to realize the management and application of operation and maintenance knowledge data. Based on the Cypher statements, information such as door numbers, data IDs, and door opening and closing times of the historical data of the door opening and closing operation and maintenance knowledge in the Neo4j graph database is queried.

[0076] The Cypher statement for retrieving historical data by door number is as follows:

[0077] MATCH path = ((Door)-[Time]->(Data))

[0078] WHERE Door.Door_Number = 'CQ010410408'

[0079] RETURN path

[0080] The result of retrieving the operation and maintenance knowledge base by door number is specifically as Figure 3 shown in the triple query by door number. In the figure, the central brown circle represents the door entity, and the door number information is inside the circle; the surrounding green circles represent the operation and maintenance data entities, and if the door is in a normal state, and if it is orange, it means the door is in a sub-healthy state. The number inside the circle represents the data ID information; the directed arrow connecting the circles is the relationship between the entities, and the number represents the timestamp information, that is, when the data of this door is generated.

[0081] Through Figure 3 it can be seen that the returned door with the door number CQ010410408 and its related data IDs include 1, 32, 1244, etc., and the door opening and closing time and other data can be further obtained.

[0082] The Cypher statement for retrieving historical data by data ID is as follows:

[0083] MATCH path = ((Door)-[Time]->(Data))

[0084] WHERE Data.ID = '1482'

[0085] RETURN path

[0086] The result of retrieving the operation and maintenance knowledge base by data ID is as Figure 4 shown in the triple query by data ID, returning the historical data with the data ID of 1482, which is the sub-healthy data that occurred at 2022-04-27T06:38:58.103 for the corresponding door CQ010410107.

[0087] The Cypher statement for retrieving historical data for door opening and closing times is as follows:

[0088] MATCH path = ((Door)-[Time]->(Data))

[0089] WHERE Time.Time = '2022-04-27T01:31:31.545000'

[0090] RETURN path

[0091] The result of retrieving the operation and maintenance knowledge base for door opening and closing times is specifically as follows Figure 5 shown in the triple query for door opening and closing times, returning the operation and maintenance historical data with ID 659 generated by door CQ010390603 at the door opening and closing time of 2022-04-27T01:31:31.545.

[0092] In summary, in the embodiment of the present invention, first, real-time operation and maintenance data of the urban rail train door opening and closing scenario is collected; and time stamps are marked on the real-time operation and maintenance data; secondly, historical operation and maintenance data of the door opening and closing scenario is obtained based on the time-stamped real-time operation and maintenance data and data based on a relational database; then, the historical operation and maintenance data is preprocessed, and a knowledge ontology is constructed based on the preprocessed historical operation and maintenance data; finally, an operation and maintenance knowledge base is constructed based on the knowledge ontology and real-time operation and maintenance data; the operation and maintenance knowledge base constructed by the present invention can flexibly handle changing data structures and complex data volumes, can be updated in real time for the dynamic generation of new data, and has stronger scalability.

[0093] Furthermore, the knowledge ontology constructed by the present invention makes the operation and maintenance data more understandable and operable.

[0094] Furthermore, the present invention provides a query and retrieval method based on knowledge graph technology, enabling users to quickly locate the required operation and maintenance data through multiple information query methods, significantly improving data utilization, and facilitating the daily work of operation and maintenance personnel.

[0095] In addition, the present invention provides important support for the intelligent operation and maintenance of urban rail trains. Based on this application, big data analysis and intelligent retrieval can be carried out, which not only improves the operation and maintenance efficiency, but also promotes the implementation of intelligent decision-making, and improves the reliability and automation level of urban rail train operation and maintenance.

[0096] Embodiment 2

[0097] Corresponding to the method embodiment, on the other hand of the embodiment of the present invention, an operation and maintenance data management device for the urban rail train door opening and closing scenario is also provided. Figure 6The structural schematic diagram of the operation and maintenance data management device for the urban rail train door opening and closing scenario provided by the embodiment of the present invention is shown. The operation and maintenance data management device for the urban rail train door opening and closing scenario is Figure 1 The device corresponding to the operation and maintenance data management method for the urban rail train door opening and closing scenario in the corresponding embodiment, that is, it is implemented in the form of a virtual device Figure 1 The operation and maintenance data management method for the urban rail train door opening and closing scenario in the corresponding embodiment. Each virtual module constituting the operation and maintenance data management device for the urban rail train door opening and closing scenario can be executed by an electronic device, such as a network device, a terminal device, or a server. Specifically, the operation and maintenance data management device for the urban rail train door opening and closing scenario in the embodiment of the present invention includes:

[0098] The real-time operation and maintenance data acquisition unit 01 is used to acquire the real-time operation and maintenance data of the urban rail train door opening and closing scenario; and mark a time stamp for the real-time operation and maintenance data;

[0099] In the embodiment of the present invention, the operation and maintenance data of the rotation speed, torque, and rotation angle of the urban rail train door opening and closing are acquired based on sensors; and the door number, equipment SN number, door opening and closing time, and door state of the urban rail train door are obtained. Taking the process of one door opening or closing as a group of data, a data ID is marked, and the operation and maintenance data of the rotation speed, torque, and rotation angle are recorded in the form of an array.

[0100] When acquiring the real-time operation and maintenance data, the time of the first moment of door opening or closing is used as the time stamp for marking.

[0101] The historical operation and maintenance data generation unit 02 is used to obtain the historical operation and maintenance data of the door opening and closing scenario according to the real-time operation and maintenance data marked with a time stamp and the data based on the table relational database; wherein, the data based on the table relational database is: converting the original data stored in the table relational database into data with the same format as the time stamp of the real-time operation and maintenance data;

[0102] In the embodiment of the present invention, the historical operation and maintenance data of the door opening and closing scenario mainly includes two types: one is the real-time operation and maintenance data collected in the door opening and closing operation and maintenance scenario, and when collecting the real-time operation and maintenance data, the time of the first moment of door opening or closing is used as the time stamp for marking; defining the real-time operation and maintenance data as historical data; the second is the original data stored in the table-based relational database.

[0103] The knowledge ontology construction unit 03 is used to preprocess the historical operation and maintenance data and construct a knowledge ontology according to the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships;

[0104] In the embodiment of the present invention, preprocessing the historical operation and maintenance data includes: performing structural processing on the historical operation and maintenance data; and obtaining the data structure and data content.

[0105] Construct a knowledge ontology, specifically as follows:

[0106] By analyzing the data structure and data content, it can be known that the historical data in the operation and maintenance process mainly includes two types of objects, namely the urban rail transit train doors from which data is collected and the data collected for corresponding door opening and closing operations. Therefore, the main ontology objects for knowledge extraction are defined as urban rail transit train doors and operation and maintenance data. Thus, the ontology includes two types of entities, namely urban rail transit train doors and operation and maintenance data, and stores and manages knowledge in the Neo4j graph database. Establish the relationship between entities with the door opening and closing time as the relationship, and store the information of urban rail transit train doors and data information other than the data generated during the corresponding operation and maintenance process as the attributes of the entities in the Neo4j graph database.

[0107] The operation and maintenance knowledge base construction unit 04 is used to construct an operation and maintenance knowledge base according to the knowledge ontology and the real-time operation and maintenance data.

[0108] In the embodiment of the present invention, constructing an operation and maintenance knowledge base includes:

[0109] Establish a connection with the graph database through the Graph function, and use the Node() function to create the entities of urban rail transit train doors and operation and maintenance data;

[0110] Form entities from the information of urban rail transit train doors and the corresponding operation and maintenance data and write them into the operation and maintenance knowledge base;

[0111] Write the information of urban rail transit train doors and data information other than the data generated during the corresponding operation and maintenance process as the attributes of the entities into the operation and maintenance knowledge base;

[0112] Use the Relationship function to create the relationship between urban rail transit train doors and operation and maintenance data, and provide timestamp information with the door opening and closing time as the attribute of the relationship.

[0113] Preferably, in the embodiment of the present invention, it may further include:

[0114] The retrieval unit 05 is used to retrieve the historical operation and maintenance data and the real-time operation and maintenance data according to the operation and maintenance knowledge base.

[0115] In the embodiment of the present invention, in order to call the operation and maintenance knowledge base and effectively manage and retrieve operation and maintenance data, Cypher statements are formulated based on the construction rules of the operation and maintenance knowledge base. The stored historical data and real-time data need to be further retrieved and applied to realize the management and application of operation and maintenance knowledge data. Query the information such as door numbers, data IDs, and door opening and closing times of the historical data of door opening and closing operation and maintenance knowledge in the Neo4j graph database based on Cypher statements.

[0116] The Cypher statement for retrieving historical data facing the door number is as follows:

[0117] MATCH path = ((Door)-[Time]->(Data))

[0118] WHERE Door.Door_Number = 'CQ010410408'

[0119] RETURN path

[0120] Results of retrieving the operation and maintenance knowledge base by door number, specifically as Figure 3 shown in the triple query by door number.

[0121] The Cypher statement for retrieving historical data by data ID is as follows:

[0122] MATCH path = ((Door)-[Time]->(Data))

[0123] WHERE Data.ID = '1482'

[0124] RETURN path

[0125] Results of retrieving the operation and maintenance knowledge base by data ID are as Figure 4 shown in the triple query by data ID.

[0126] The Cypher statement for retrieving historical data by door opening / closing time is as follows:

[0127] MATCH path = ((Door)-[Time]->(Data))

[0128] WHERE Time.Time = '2022-04-27T01:31:31.545000'

[0129] RETURN path

[0130] Results of retrieving the operation and maintenance knowledge base by door opening / closing time, specifically as Figure 5 shown in the triple query by door opening / closing time, return the operation and maintenance historical data with ID 659 generated by door CQ010390603 at door opening / closing time 2022-04-27T01:31:31.545.

[0131] It should be noted that the specific implementation method and technical effect of the operation and maintenance data management device for urban rail train door opening / closing scenarios in the embodiments of the present invention can refer to Figure 1 the corresponding operation and maintenance data management method for urban rail train door opening / closing scenarios, which will not be elaborated here.

[0132] Embodiment III

[0133] Corresponding to the method embodiments, in the embodiments of the present invention, there is also provided an operation and maintenance data management device for the door opening and closing scenario of urban rail trains, such as a terminal, a server, etc. Among them, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto.

[0134] An example diagram of the hardware structure block diagram of the operation and maintenance data management device for the door opening and closing scenario of urban rail trains provided by the embodiments of the present invention is as Figure 7 shown, and may include:

[0135] Processor 1, communication interface 2, memory 3, and communication bus 4;

[0136] Among them, the processor 1, the communication interface 2, and the memory 3 complete mutual communication through the communication bus 4;

[0137] Optionally, the communication interface 2 can be an interface of a communication module, such as an interface of a GSM module;

[0138] The processor 1 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0139] The memory 3 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0140] Among them, the processor 1 is specifically configured to execute the computer program stored in the memory 3 to perform the following steps:

[0141] S11. Collect the real-time operation and maintenance data of the door opening and closing scenario of the urban rail train; and mark a time stamp for the real-time operation and maintenance data;

[0142] S12. Obtain the historical operation and maintenance data of the door opening and closing scenario according to the real-time operation and maintenance data marked with a time stamp and the data based on the relational database; wherein, the data based on the relational database is: converting the data originally stored in the relational database into data with the same format as the time stamp of the real-time operation and maintenance data;

[0143] S13. Preprocess the historical operation and maintenance data, and construct a knowledge ontology based on the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships;

[0144] S14. Construct an operation and maintenance knowledge base based on the knowledge ontology and the real-time operation and maintenance data.

[0145] The above product can execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the method for managing operation and maintenance data for the door opening and closing scenario of urban rail trains provided by the embodiment of the present invention.

[0146] Embodiment 4

[0147] In the embodiment of the present invention, a storage medium is further provided. The storage medium can store a program suitable for execution by a processor, and the program is used for:

[0148] S11. Collect real-time operation and maintenance data for the door opening and closing scenario of urban rail trains; and mark time stamps for the real-time operation and maintenance data;

[0149] S12. Obtain historical operation and maintenance data for the door opening and closing scenario based on the real-time operation and maintenance data marked with time stamps and the data based on a relational database; wherein, the data based on the relational database is: converting the original data stored in the relational database into data with the same time stamp format as the real-time operation and maintenance data;

[0150] S13. Preprocess the historical operation and maintenance data, and construct a knowledge ontology based on the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships;

[0151] S14. Construct an operation and maintenance knowledge base based on the knowledge ontology and the real-time operation and maintenance data.

[0152] Optionally, the refined functions and extended functions of the program can be referred to the above description.

[0153] The above product can execute the method provided by the embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the methods provided by other embodiments of the present invention.

[0154] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0155] In several embodiments provided by this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. Additionally, the couplings, direct couplings, or communication connections shown or discussed among each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0156] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0157] In addition, in each embodiment of this application, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0158] It should be understood that in the embodiments of this application, the dependent claims, each embodiment, and features can be combined with each other to achieve the solution of the aforementioned technical problems.

[0159] If the described functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of this application. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes.

[0160] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for managing operation and maintenance data in the door opening and closing scenario of urban rail trains, characterized in that, It includes the steps: S11. Collect the real-time operation and maintenance data of the urban rail train door opening and closing scenario; and mark the time stamp for the real-time operation and maintenance data; S12. Obtain the historical operation and maintenance data of the door opening and closing scenario based on the real-time operation and maintenance data with marked time stamps and the data based on the tabular relational database; wherein, the data based on the tabular relational database is: converting the originally stored data in the tabular relational database into data with the same time stamp format as the real-time operation and maintenance data; S13. Preprocess the historical operation and maintenance data, and construct a knowledge ontology according to the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships; S14. Construct an operation and maintenance knowledge base according to the knowledge ontology and the real-time operation and maintenance data.

2. The operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to claim 1, wherein It also includes: S15. Retrieve the historical operation and maintenance data and the real-time operation and maintenance data according to the operation and maintenance knowledge base.

3. The operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to claim 1, wherein The collection of the real-time operation and maintenance data of the urban rail train door opening and closing scenario includes: Collecting the operation and maintenance data of the rotation speed, torque, and rotation angle of the urban rail train door opening and closing based on sensors; and obtaining the door number, equipment SN number, door opening and closing time, and door state of the urban rail train door.

4. The operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to claim 3, wherein The preprocessing of the historical operation and maintenance data includes: Performing structured processing on the historical operation and maintenance data; and obtaining the data structure and data content.

5. The operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to claim 4, wherein The construction of the knowledge ontology includes: Defining the ontology for knowledge extraction according to the data structure and the data content; the ontology includes: urban rail train doors and operation and maintenance data; According to the extracted knowledge ontology, organizing and defining the entities, the entity attributes, and the entity relationships, and storing them in the graph database.

6. The operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to claim 5, wherein The construction of the operation and maintenance knowledge base includes: Establishing a connection with the graph database through the Graph function, and creating entities of the urban rail train doors and operation and maintenance data using the Node() function; Forming entities from the information of the urban rail train doors and the corresponding operation and maintenance data and writing them into the operation and maintenance knowledge base; Writing the data information other than the information of the urban rail train doors and the data generated during the corresponding operation and maintenance process as entity attributes into the operation and maintenance knowledge base; Using the Relationship function to create the relationship between the urban rail train doors and the operation and maintenance data, and providing time stamp information with the door opening and closing time as the attribute of the relationship.

7. An operation and maintenance data management device for the door opening and closing scenario of urban rail trains, characterized in that, It includes: A real-time operation and maintenance data collection unit, which is used to collect the real-time operation and maintenance data of the urban rail train door opening and closing scenario; And mark the time stamp for the real-time operation and maintenance data; A historical operation and maintenance data generation unit, which is used to obtain the historical operation and maintenance data of the door opening and closing scenario based on the real-time operation and maintenance data with marked time stamps and the data based on the tabular relational database; wherein, the data based on the tabular relational database is: converting the originally stored data in the tabular relational database into data with the same time stamp format as the real-time operation and maintenance data; A knowledge ontology construction unit, which is used to preprocess the historical operation and maintenance data, and construct a knowledge ontology according to the preprocessed historical operation and maintenance data; the knowledge ontology includes: entities, entity attributes, and entity relationships; An operation and maintenance knowledge base construction unit, which is used to construct an operation and maintenance knowledge base according to the knowledge ontology and the real-time operation and maintenance data.

8. The operation and maintenance data management device for the door opening and closing scenario of urban rail trains according to claim 7, characterized in that, It further includes: A retrieval unit, configured to retrieve the historical operation and maintenance data and the real-time operation and maintenance data according to the operation and maintenance knowledge base.

9. An operation and maintenance data management device for the door opening and closing scenario of urban rail trains, characterized in that, It includes: A memory, configured to store a computer program; A processor, configured to call and execute the computer program to implement the steps of the operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to any one of claims 1-6.

10. A storage medium, characterized in that, It includes a software program, and the software program is adapted to be executed by a processor to implement the steps of the operation and maintenance data management method for the door opening and closing scenario of urban rail trains according to any one of claims 1-6.

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