A non-line side urban rail control data analysis management system

Abstract

This invention relates to a non-track-side urban rail transit train control data analysis and management system, comprising a track-side end and a non-track-side end. The track-side end includes: an ATS server, used to provide real-time raw data and connect to a data access server via a backbone network; a data access server, used to acquire real-time raw data from the ATS server and send encapsulated UDP packets to a first data forwarding server and a second data forwarding server respectively via a one-way network gateway; the first and second data forwarding servers, used to parse the received UDP packets to recover ATS log data and save it locally, and store data within a specified time period for data retransmission backup, and transmit the received UDP packets to a web application server via a VAP virtual network. This invention enables real-time remote acquisition of ATS log data for each line outside the signaling system, online data preprocessing and efficient storage, and a flexible and user-friendly functional interface software framework.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rail transit data analysis, in particular to a non-line side urban rail train control data analysis and management system. BACKGROUND

[0002] According to the technical specification requirements of the urban rail transit signal system ATS, ATS needs to classify and display (including maintenance information) and prompt the alarm / event, and provide basic functions such as filtering and querying. At present, the key functions of the ATS system provided by domestic signal system suppliers still focus on control center display, signal control, train tracking and control, control area management, etc., and the processing of log-type data such as alarms / events still stays at the basic display and query functions. In recent years, the complexity of the signal train control system has been increasing, and the log data of each subsystem has been increasing day by day. At the same time, with the rapid development of intelligent operation and maintenance related technologies, analyzing log data from each subsystem has become one of the important means for signal systems to cope with intelligent operation and maintenance. However, it is difficult to meet the high standards of intelligent operation and maintenance by relying solely on the basic functions provided by ATS. And it is difficult for ATS as part of the signal system to be flexibly expanded. Therefore, it is impossible to carry out multi-line network-level comprehensive operation and maintenance work.

[0003] In order to make full use of the log data collected by ATS from each subsystem and carry out fault analysis and preventive maintenance of the signal system, there are currently two main ways to obtain data:

[0004] Outside the signal system network: log data is stored in the form of files (csv / gz / sql, etc.) on the local disk of each subsystem. Due to network security restrictions, manual login to the ATS server is required in the internal network at regular intervals, and data files are copied out through a removable disk (mobile hard disk).

[0005] Inside the signal system network: deploy related application services in the maintenance network (firewall connected to the signal production network), at this time the network supports two-way communication, and can use third-party data synchronization tools (rsync, etc.) to synchronize the above data files to the local server, or the application service itself can synchronize data to the local database in real time by polling the ATS database at regular intervals.

[0006] There are various processing and analysis modes for log data, one of which is to provide specific functions through customized data analysis tools, such as ATO (Automatic Train Operation) stopping accuracy analysis, and to extract records related to ATO stopping accuracy (stopping log, train mode, etc.) in the log file by using specific script tools to generate stopping statistical results for different trains. The second, which is currently being widely promoted, is to extract and analyze logs in real time through an intelligent operation and maintenance system deployed in the maintenance network, which can also effectively realize centralized management of data, such as the intelligent operation and maintenance platform organized by the Shanghai Metro Maintenance and Guarantee Co., Ltd.

[0007] Although the above two methods can complement each other, they have their own problems, making it difficult for ATS log data to directly and efficiently participate in fault maintenance analysis outside the signal system network (non-line side, signal system supplier network). The main problems are:

[0008] The data set of the customized data analysis tool is only effective for this analysis process, and does not have continuity and integrity before and after the time period, making it difficult to ensure data consistency. Different users may need to re-analyze or partially calculate repetitive data based on different analysis periods and different alarm sets, which is low in efficiency.

[0009] Due to network security architecture restrictions, the intelligent operation and maintenance system within the signal system has certain difficulties in realizing comprehensive analysis of line network-level data. At the same time, data is difficult to share with non-line side operation and maintenance personnel, resulting in limitations in the application range of system functions, such as the difficulty for signal suppliers to obtain real-time operation and fault data on the line side in the company intranet. SUMMARY

[0010] The purpose of the present application is to overcome the existing defects and provide a non-line side urban rail train control data analysis management system that can realize real-time remote acquisition of ATS log data of each line outside the signal system, online data preprocessing and efficient storage, and a flexible and friendly function interface software framework.

[0011] The technical solution to achieve the above purpose is:

[0012] A non-line side urban rail train control data analysis management system, comprising a line side end and a non-line side end, the line side end comprising:

[0013] An ATS server for providing real-time raw data and connecting a data access server through a maintenance backbone network;

[0014] The data access server is configured to acquire real-time original data in the ATS server, and send encapsulated UDP messages to the first data forwarding server and the second data forwarding server through a one-way gateway respectively.

[0015] The first data forwarding server and the second data forwarding server are configured to parse the received UDP messages to restore the ATS log data to a local, store data in a specified time period for data retransmission backup, and transmit the received UDP messages to a Web application server through a VAP virtual network.

[0016] The non-line side end comprises:

[0017] The Web application server is configured to receive the UDP messages sent by the first data forwarding server and the second data forwarding server, parse and restore the original ATS log data, provide user authentication, parameter analysis, function item data analysis, query function, and save the ATS log data to a disk array.

[0018] The disk array is configured to save the ATS log data and mount to the Web application server through file mounting.

[0019] Preferably, the network cards of the first data forwarding server and the second data forwarding server are connected to the one-way gateway in a bonding mode, and the first data forwarding server and the second data forwarding server acquire the UDP messages from the data access server and parse the UDP messages in a dual-hardware hot backup mode.

[0020] Preferably, the data access server comprises:

[0021] The first application program is configured to acquire real-time original data from the ATS server in a polling mode, re-encapsulate the original data into UDP messages in a protocol format, and push the serialized messages to the first message middleware.

[0022] The first message middleware is configured to forward the same UDP messages to the second application program and the third application program.

[0023] The second application program and the third application program are configured to send the acquired UDP messages to the first data forwarding server and the second data forwarding server through a one-way gateway respectively.

[0024] Preferably, the first data forwarding server comprises:

[0025] The fourth application is used to receive UDP packets sent from the second application, transmit them to the Web application server through the VAP virtual network, parse the received UDP packets, restore them to the original ATS log data, and save them to the first database;

[0026] The first database is used to store the ATS log data restored to its original state.

[0027] Preferably, the second data forwarding server includes:

[0028] The fifth application is used to receive UDP packets sent from the third application, transmit them to the Web application server through the VAP virtual network, parse the received UDP packets, restore them to the original ATS log data, and save them to the second database.

[0029] The second database is used to store the ATS log data restored to its original state.

[0030] Preferably, a UDP message mainly includes a two-byte transmission sequence number, a CRC redundancy check code, and a data packet.

[0031] Preferably, the web application server includes:

[0032] The second message middleware is used to receive UDP packets sent from the fourth and fifth applications and forward them to the data parsing module;

[0033] The data parsing module is used to parse the received UDP packets back into the original ATS log data and submit it to the disk array;

[0034] The raw data classification and retrieval module is used to perform category retrieval on the disk array based on the search criteria submitted by the user in the browser page form and to display the final results in tabular form.

[0035] Preferably, before the data parsing module parses the UDP packets, the received UDP packets need to be cleaned and filtered according to predefined filtering conditions, and some parameters are converted and preprocessed during the parsing process.

[0036] Preferably, for UDP packets with multiple lines and multiple types, after cleaning and parsing, they are classified and stored in the disk array.

[0037] Preferably, the web application server adopts the Flask web framework, the Bootstrap front-end framework, Postgres+Redis data storage, and an Nginx+uWSGI+Docker deployment scheme.

[0038] The beneficial effects of this invention are as follows: This invention utilizes a one-way network gateway and VPN virtual network technology to ensure that ATS log data on the line side can be securely transmitted to a remote non-line side over the Internet without affecting the network security of either party. Furthermore, it employs a direct polling method against the ATS server, enabling data to directly and in real-time reach the external data access server. The data access server deployed on the line side uses two physical network cards connected to the one-way network gateway to achieve directional isolation of data transmission, preventing modification or damage to the urban rail operator's data. This ensures that the second and third applications can send identical message information to the remote first and second data forwarding servers, respectively, preventing data loss on one line. Finally, it employs a dual-machine hot standby method, storing data received within a recent period separately in the first and second databases. In the database, when a data retransmission command is received from a web application server on the non-line side, missing data can be retransmitted. After receiving the message, the web application server determines whether the message is lost by verifying the continuity of the TSN (1-65535). The software uses a cache sorting method to deal with occasional out-of-order problems of UDP messages and verifies the validity of the message data through CRC. This invention realizes real-time remote acquisition of ATS log data of each line, online data preprocessing and efficient storage, and a flexible and user-friendly functional interface software framework. It has greatly improved the consistency, accuracy, multi-dimensional analysis, maintainability and functional scalability of data. It enables personnel in various functional departments of the signal supplier to conveniently obtain various subsystem operation data from the ATS server without being restricted by time and geographical location, saving a lot of time and manpower costs. Attached Figure Description

[0039] Figure 1 This is a block diagram of a non-track side urban rail transit train control data analysis and management system according to the present invention;

[0040] Figure 2 This is a detailed module diagram of the data access server in this invention.

[0041] Figure 3 This is a detailed block diagram of the first data forwarding server and the second data forwarding server in this invention;

[0042] Figure 4 This is a specific module diagram of the Web application server in this invention.

[0043] In the diagram: 1. ATS server; 2. Data access server; 3. First data forwarding server; 4. Second data forwarding server; 5. Web application server; 6. Disk array; 21. First application program; 22. First message middleware; 23. Second application program; 24. Third application program; 31. Fourth application program; 32. First database; 41. Fifth application program; 42. Second database; 51. Second message middleware; 52. Data parsing module; 53. Raw data classification and retrieval module. Detailed Implementation

[0044] The technical solution of the present invention will now be clearly and completely described in conjunction with the accompanying drawings. In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0045] The invention will now be further described with reference to the accompanying drawings.

[0046] like Figures 1-4 As shown, a non-track side urban rail transit train control data analysis and management system includes a track side end and a non-track side end. The track side end includes an ATS server 1, a data access server 2, a first data forwarding server 3, and a second data forwarding server 4. The non-track side end includes a Web application server 5 and a disk array 6.

[0047] ATS server 1 is used to provide real-time raw data and connect to data access server 2 via the backbone network.

[0048] Data access server 2 is used to obtain real-time raw data from ATS server 1 and send the encapsulated UDP packets to the first data forwarding server 3 and the second data forwarding server 4 respectively through a one-way network gateway.

[0049] The data access server 2 specifically includes: a first application 21, used to obtain real-time raw data from the ATS server 1 through polling, and re-encapsulate the raw data into UDP packets of the protocol format, and push the serialized packets to the first message middleware 22; the first message middleware 22 is used to forward the same UDP packets to the second application 23 and the third application 24; the second application 23 and the third application 24 are used to send the obtained UDP packets to the first data forwarding server 3 and the second data forwarding server 4 respectively through a one-way network gateway; the network cards of the first data forwarding server 3 and the second data forwarding server 4 are connected to the one-way network gateway in a bonding manner, and the first data forwarding server 3 and the second data forwarding server 4 adopt dual-machine hot standby. The system obtains and parses UDP packets from data access server 2, and uses a one-way network gateway and VPN virtual network technology to ensure that ATS log data on the line side can be securely transmitted to the remote non-line side of the Internet without affecting the network security of either party. It also adopts a direct polling method for ATS server 1, so that the data can directly reach the external data access server 2 in real time. The data access server 2 deployed on the line side uses two physical network cards connected to the one-way network gateway to achieve directional isolation of data transmission, prevent the data of the urban rail operator from being modified or destroyed, and ensure that the second application 23 and the third application 24 can send the same message information to the remote first data forwarding server 3 and the second data forwarding server 4 respectively, so as to prevent the loss of data on one line.

[0050] In this embodiment, the UDP packet mainly includes a two-byte transmission sequence number, a CRC redundancy check code, and a data packet. The timing of the packet is guaranteed by using a two-byte transmission sequence number (TSN) combined with a cache sorting method, and the validity of the entire packet is verified by the CRC check code.

[0051] The first data forwarding server 3 and the second data forwarding server 4 are used to parse the received UDP packets, restore them to ATS log data and save them locally, store data within a specified time period for data retransmission backup, and transmit the received UDP packets to the Web application server 5 through the VAP virtual network.

[0052] The first data forwarding server 3 specifically includes: a fourth application 31, used to receive UDP packets sent from the second application 23, transmit them to the Web application server 5 through the VAP virtual network, parse the received UDP packets, restore them to the original ATS log data, and save them to the first database 32; the first database 32 is used to store the restored original ATS log data.

[0053] The second data forwarding server 4 specifically includes: a fifth application 41, used to receive UDP packets sent from the third application 24, transmit them to the Web application server 5 through the VAP virtual network, parse the received UDP packets, restore them to the original ATS log data, and save them to the second database 42; the second database 42 is used to store the restored original ATS log data.

[0054] Web application server 5 is used to receive UDP packets sent from the first data forwarding server 3 and the second data forwarding server 4, parse and restore the original ATS log data, provide user authentication, parameter parsing, function item data analysis and query functions, and save the ATS log data to disk array 6. After receiving the UDP packet, Web application server 5 determines whether the UDP packet is lost by checking the continuity of TSN (1-65535). The software adopts a cache sorting method to deal with the occasional out-of-order problem of UDP packets and uses CRC to check the validity of the packet data.

[0055] Web application server 5 specifically includes: a second message middleware 51, used to receive UDP packets sent from the fourth application 31 and the fifth application 41, and forward them to the data parsing module 52; the data parsing module 52, used to parse the received UDP packets back into the original ATS log data, and submit it to the disk array 6; and the original data classification and retrieval module 53, used to perform category retrieval in the disk array 6 based on the retrieval conditions submitted by the user in the browser page form, and display the final results in tabular form.

[0056] In this embodiment, before the data parsing module 52 parses the UDP packets, the received UDP packets need to be cleaned and filtered according to predefined filtering conditions. During the parsing process, some parameters are preprocessed and converted. Since the ATS logs contain various types of data, including train dispatching information, general logs, warnings, and fault information, and the data source for this invention is mainly warning and fault information, the received data needs to be cleaned and filtered according to predefined filtering conditions. Simultaneously, to facilitate subsequent data parsing and processing by the data parsing module 52, some parameters need to be preprocessed and converted during the parsing and recovery of the original data. For example, train position parameters are converted into section information, effectively improving the efficiency of statistical analysis by section ID in the statistical analysis module.

[0057] In this embodiment, for UDP packets of multiple lines and types, after cleaning and parsing, they are classified and stored in disk array 6. For the raw data, a relational database table is created monthly for each line in disk array 6 (the target is to store 5 years of data, corresponding to 60 tables, hereinafter referred to as the monthly data table). At the same time, a mapping table is used to maintain the correspondence between the monthly data table and the month, and a cyclic replacement algorithm is used to update the data in the monthly data table and the mapping table. For data associated with specific functions, the data is classified by line and function and stored in the designated relational database table to improve the retrieval efficiency of specific functions. For data with high timeliness, such as emergency alarms in the most recent hour, Redis caching is used to improve the processing efficiency of fault location.

[0058] In this embodiment, the raw data classification and retrieval module 53 is used to perform a category search in the disk array 6 based on the search conditions submitted by the user in the browser page form and display the final results in a table format. The search conditions include: a list of lines or predefined product line names, a list of alarm IDs or predefined alarm combination names, a date range (by year, month, and day), and an operating time period (by hour and minute).

[0059] In this embodiment, for alarms of interest to users, statistical dimensions are defined according to alarm parameter categories. For each statistical dimension, a predefined general stub function method is matched. The raw data retrieved from disk array 6 is analyzed using the stub function method, and the browser interface displays the final statistical results graphically using bar charts, pie charts, etc. Based on the statistical analysis, some predefined statistical rules and factors are overlaid, and the time axis is extended to obtain the trend changes of certain faults with corresponding statistical factors, effectively assessing the health of related devices. Multi-dimensional data analysis, compared to simple data statistics, provides backend technicians with multi-faceted health assessments, offering valuable decision-making basis for fault diagnosis, prevention, prediction, and intelligent and smart maintenance.

[0060] In this embodiment, parameter parsing is performed on fault alarms that can be associated with devices or device boards. There are two basic scenarios: the parameters of a single fault alarm are associated with a specific device, and the occurrence sequence of multiple fault alarms is combined with the parameters of a core alarm to be associated with a specified device; real-time faults are associated with relevant devices or boards to achieve the purpose of real-time fault location.

[0061] In this embodiment, the Web application server 5 adopts the Flaskweb framework, the Bootstrap front-end framework, Postgres+Redis data storage, and the Nginx+uWSGI+docker deployment scheme, which realizes the rapid deployment and centralized management of the back-end application; it enables relevant technical support personnel to obtain on-site data of each line more timely and accurately, and provide accurate data analysis results; it greatly improves the efficiency of remote support, thereby quickly recovering from faults and reducing the impact on urban rail operation.

[0062] Disk array 6 is used to store ATS log data. It is mounted to Web application server 5 via file mounting. Disk array 6 is configured in RAID 5 redundancy mode.

[0063] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A non-line side urban rail train control data analysis management system, characterized in that, The line side end includes a line side end and a non-line side end, and the line side end includes: The ATS server is used for providing real-time raw data and accessing the data access server by maintaining the backbone network connection data; The data access server is used for obtaining the real-time raw data in the ATS server, and sending the encapsulated UDP packet to the first data forwarding server and the second data forwarding server through the one-way gate respectively; The first data forwarding server and the second data forwarding server are used for analyzing and restoring the received UDP packet to the ATS log data saved in the local, and storing the data in a specified time period for data retransmission backup, and transmitting the received UDP packet to the Web application server through the VAP virtual network; The non-line side end includes: The Web application server is used for receiving the UDP packet sent by the first data forwarding server and the second data forwarding server, analyzing and restoring the raw ATS log data, providing user authentication, parameter analysis, function item data analysis, query function, and saving the ATS log data to the disk array; The disk array is used for saving the ATS log data and mounting to the Web application server through file mounting; The network card of the first data forwarding server and the second data forwarding server is connected to the one-way gate in a bonding mode, and the first data forwarding server and the second data forwarding server obtain the UDP packet from the data access server and analyze it in a dual-machine hot backup mode; The data access server includes: The first application program is used for obtaining real-time raw data from the ATS server by polling, and encapsulating the raw data into UDP packet of protocol format, and pushing the serialized packet to the first message middleware; The first message middleware is used for forwarding the same UDP packet to the second application program and the third application program; The second application program and the third application program are used for sending the obtained UDP packet to the first data forwarding server and the second data forwarding server through the one-way gate respectively; The first data forwarding server includes: The fourth application program is used for receiving the UDP packet sent by the second application program, transmitting it to the Web application server through the VAP virtual network, analyzing the received UDP packet, restoring it to the raw ATS log data, and saving it to the first database; The first database is used for storing the raw ATS log data; The second data forwarding server includes: The fifth application program is used for receiving the UDP packet sent by the third application program, transmitting it to the Web application server through the VAP virtual network, analyzing the received UDP packet, restoring it to the raw ATS log data, and saving it to the second database; The second database is used for storing the raw ATS log data.

2. The non-line side urban rail control data analysis and management system according to claim 1, characterized in that, The UDP packet mainly includes a double-byte sending sequence number, a CRC redundancy check code and a data packet.

3. The non-line side urban rail control data analysis and management system according to claim 1, characterized in that, The Web application server includes: The second message middleware is configured to receive UDP messages sent by the fourth application and the fifth application and forward the UDP messages to the data analysis module; The data analysis module is configured to parse the received UDP messages to restore original ATS log data and submit the original ATS log data to the disk array; The original data classification retrieval module is configured to perform classification retrieval in the disk array according to retrieval conditions submitted by a user in a browser page form and display final results in a table form.

4. The non-line side urban rail control data analysis and management system according to claim 3, characterized in that, Before the data analysis module parses the UDP messages, the received UDP messages need to be cleaned and filtered according to predefined filtering conditions, and some parameters need to be converted and preprocessed in the parsing process.

5. The non-line side urban rail control data analysis and management system according to claim 4, characterized in that, For multi-line and multi-type UDP messages, after cleaning and parsing, the UDP messages are classified and stored in the disk array.

6. The non-line side urban rail control data analysis and management system according to claim 1, characterized in that, The web application server adopts a Flask web framework, a Bootstrap front-end framework, a Postgres+Redis data storage and an Nginx+uWSGI+docker deployment scheme.

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