A monitoring system for rail transit signals

Abstract

The present application discloses a rail transit signal monitoring system, comprising: a cloud monitoring platform, one or more local monitoring nodes, wherein each local monitoring node comprises: a first communication unit for establishing a communication connection with the cloud monitoring platform; a signal acquisition unit for acquiring real-time signals of the current device; a feature acquisition unit for acquiring and storing signal feature values of abnormal events from the cloud monitoring platform; a signal analysis unit for analyzing real-time signals according to the signal feature values and obtaining analysis results; and an instruction output unit for issuing corresponding operation instructions to the current device according to the analysis results. In the present application, the local monitoring node autonomously monitors the operating status of the equipment without the participation of a dispatcher. At the same time, since the judgment is based on targeted signal feature values, the scope of information acquisition is relatively small, thereby quickly obtaining analysis results and quickly responding to the current device.

Description

Technical Field

[0001] The present invention relates to the field of signal control, and in particular to a monitoring system for rail transit signals. Background Art

[0002] Urban rail transit, characterized by high capacity, high speed, and punctuality, is gradually becoming a vital public transportation tool and essential infrastructure in major Chinese cities. Urban rail transit signal control technology is widely used to control train safety and prevent signaling. Its product reliability and functional safety focus are directly related to the normal operation of urban rail transit.

[0003] Typically, a communication signal failure triggers a series of sequential activations of protection and control devices. Communication signal dispatchers must quickly determine the cause of the failure, triggering the protection and control actions, and implement dispatching operations to minimize the impact of the failure. However, in the vast majority of current communication signal failures, dispatching actions are performed by human operators. Dispatchers lack timely access to detailed information about the fault signal and rely solely on telesignaling messages from the substation and system status changes monitored by separate data acquisition and supervisory control systems. Consequently, most communication signal fault diagnosis systems struggle to accurately diagnose complex faults.

[0004] Therefore, how to provide a solution to the above technical problems is a problem that those skilled in the art need to solve. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a rail transit signal monitoring system that can accurately and quickly judge and respond to the current situation. The specific scheme is as follows:

[0006] A rail transit signal monitoring system includes: a cloud monitoring platform and one or more local monitoring nodes, wherein each local monitoring node includes:

[0007] A first communication unit, configured to establish a communication connection with the cloud monitoring platform;

[0008] Signal acquisition unit, used to collect real-time signals of current equipment;

[0009] A feature acquisition unit, configured to acquire and store signal feature values of abnormal events from the cloud monitoring platform;

[0010] A signal analysis unit, configured to analyze the real-time signal according to the signal characteristic value and obtain an analysis result;

[0011] The instruction output unit is used to issue corresponding operation instructions to the current device according to the analysis result.

[0012] Preferably, the cloud monitoring platform includes:

[0013] A second communication unit, configured to establish communication connections with all of the local monitoring nodes;

[0014] a data acquisition unit, configured to receive uploaded data from all the local monitoring nodes, the uploaded data including the real-time signal, the analysis result, and the operation instruction;

[0015] The data analysis unit is used to modify the judgment condition values of various events in the monitoring model according to the uploaded data, and the judgment condition values include the signal characteristic values of the abnormal events.

[0016] Preferably, the cloud monitoring platform further includes:

[0017] A large-capacity memory is used to store all the uploaded data and all the judgment condition values.

[0018] Preferably, the large-capacity memory includes eMMC.

[0019] Preferably, the data analysis unit is specifically a CPU array and / or an FPGA array.

[0020] Preferably, the data analysis unit is further used for:

[0021] Process host computer instructions and / or establish the monitoring model.

[0022] Preferably, the cloud monitoring platform further includes: a plurality of external ports of different protocols.

[0023] Preferably, the external port includes a UART interface, and / or an Ethernet interface, and / or a CAN protocol interface, and / or a PCIE interface, and / or an SPI interface, and / or an RS485 interface.

[0024] Preferably, the signal analysis unit is further used for:

[0025] When the current device is started, outputting the preset analysis result of the device startup to the instruction output unit, so that the instruction output unit issues an operation instruction corresponding to normal operation to the current device;

[0026] An initial real-time signal when the current device is started is obtained through the signal acquisition unit, and an analysis model corresponding to the current device is determined based on the initial real-time signal, so that during the operation of the current device, the real-time signal is analyzed according to the signal characteristic value using the analysis model to obtain an analysis result.

[0027] Preferably, the feature acquisition unit is specifically used to:

[0028] The signal characteristic value of the abnormal event corresponding to the current device is obtained and stored from the cloud monitoring platform.

[0029] Preferably, the operation instruction is specifically used to:

[0030] Control the current device to output an analog signal of a preset value or stop outputting the analog signal.

[0031] Preferably, the signal analysis unit is specifically an MCU, FPGA or CPLD.

[0032] Preferably, when the signal analysis unit is the MCU, the MCU is a dual-core single MCU.

[0033] Preferably, the local monitoring node further includes:

[0034] The data temporary storage unit is used to store the real-time signal, the signal characteristic value, the analysis result and the operation instruction.

[0035] Preferably, the local monitoring node also includes a device debugging port.

[0036] The present application discloses a rail transit signal monitoring system, in which a local monitoring node can, while only acquiring the real-time signal of the current device, make a judgment on the operating status of the current device based on the signal characteristic value of an abnormal event, obtain an analysis result, and then issue an operation instruction to the current device. This process is carried out autonomously and does not require the participation of a dispatcher. At the same time, since the judgment is based on targeted signal characteristic values, the scope of information acquisition is relatively small, so that the analysis result can be obtained quickly and the current device can be responded to quickly. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0038] Figure 1 This is a structural distribution diagram of a rail transit signal monitoring system according to an embodiment of the present invention;

[0039] Figure 2 This is a structural distribution diagram of a specific cloud monitoring platform in an embodiment of the present invention;

[0040] Figure 3 This is an action flow chart of a signal analysis unit in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0042] Currently, when most communication signal failures occur, dispatching actions are performed by dispatchers. Dispatchers are unable to obtain detailed information about the fault signals in a timely manner and can only rely on remote signaling messages from substations, separate data acquisition systems, and system status changes monitored by monitoring and control systems to diagnose faults. Therefore, most communication signal fault diagnosis systems find it difficult to accurately diagnose complex faults.

[0043] The present application discloses a rail transit signal monitoring system, in which a local monitoring node can, while only acquiring the real-time signal of the current device, make a judgment on the operating status of the current device based on the signal characteristic value of an abnormal event, obtain an analysis result, and then issue an operation instruction to the current device. This process is carried out autonomously and does not require the participation of a dispatcher. At the same time, since the judgment is based on targeted signal characteristic values, the scope of information acquisition is relatively small, so that the analysis result can be obtained quickly and the current device can be responded to quickly.

[0044] The embodiment of the present invention discloses a rail transit signal monitoring system, see Figure 1 As shown, it includes: a cloud monitoring platform 1, one or more local monitoring nodes 2, wherein each local monitoring node 2 includes:

[0045] The first communication unit 20 is used to establish a communication connection with the cloud monitoring platform 1;

[0046] The signal acquisition unit 21 is used to collect the real-time signal of the current device 3;

[0047] A feature acquisition unit 22 is used to acquire and store signal feature values of abnormal events from the cloud monitoring platform 1;

[0048] The signal analysis unit 23 is used to analyze the real-time signal according to the signal characteristic value and obtain the analysis result;

[0049] The instruction output unit 24 is used to send corresponding operation instructions to the current device 3 according to the analysis result.

[0050] It is understandable that the cloud monitoring platform 1 stores signal characteristic values corresponding to various abnormal events. When the first communication unit 20 establishes a communication connection between the local monitoring node 2 and the cloud monitoring platform 1, the characteristic acquisition unit 22 can obtain the signal characteristic values corresponding to various abnormal events in the cloud monitoring platform 1. By comparing the real-time signal of the current device 3 obtained by the signal acquisition unit 21 with the signal characteristic value, the operating status of the current device 3 can be quickly obtained and sent to the instruction output unit 24 as an analysis result. The instruction output unit 24 can make corresponding response operations based on the analysis results, and the operation is specifically to send corresponding operation instructions to the current device 3. The current device 3 here refers to the monitoring object of the local monitoring node 2, that is, any load of the transportation track system, including various power electronic devices, such as inverters, rectifiers or inverters.

[0051] It can be understood that the monitoring system utilizes the architecture of a cloud-based monitoring platform 1 and multiple local monitoring nodes 2. The cloud-based monitoring platform 1 completes comprehensive data analysis tasks that require large computing power and are time-consuming, while the local monitoring nodes 2 analyze real-time signals based on typical signal characteristic values. This analysis process requires little computing power and can quickly obtain analysis results, thereby achieving a rapid response to the current device 3.

[0052] The present application discloses a rail transit signal monitoring system, in which a local monitoring node can, while only acquiring the real-time signal of the current device, make a judgment on the operating status of the current device based on the signal characteristic value of an abnormal event, obtain an analysis result, and then issue an operation instruction to the current device. This process is carried out autonomously and does not require the participation of a dispatcher. At the same time, since the judgment is based on targeted signal characteristic values, the scope of information acquisition is relatively small, so that the analysis result can be obtained quickly and the current device can be responded to quickly.

[0053] The embodiment of the present invention discloses a specific rail transit signal monitoring system. Compared with the previous embodiment, this embodiment further explains and optimizes the technical solution. Figure 2 As shown:

[0054] Specifically, the cloud monitoring platform 1 includes:

[0055] The second communication unit 10 is used to establish a communication connection with all local monitoring nodes 2;

[0056] The data acquisition unit 11 is used to receive the uploaded data from all local monitoring nodes 2, including real-time signals, analysis results and operation instructions;

[0057] The data analysis unit is used to modify the judgment condition values of various events in the monitoring model according to the uploaded data. The judgment condition values include the signal characteristic values of abnormal events.

[0058] Among them, the second communication unit 10 and the first communication unit 20 establish a communication connection between the cloud monitoring platform 1 and all local monitoring nodes 2. The second communication unit 10 can be selected for wireless communication or wired communication, and different technical means are selected according to the different requirements of the size, importance and communication speed of the data transmitted to the local monitoring node 2.

[0059] Furthermore, the cloud monitoring platform 1 further includes: a large-capacity memory for storing all uploaded data and all judgment condition values. Specifically, the large-capacity memory includes but is not limited to eMMC (Embedded Multi Media Card, embedded memory standard specification).

[0060] Furthermore, the data analysis unit is specifically a CPU (Central Processing Unit) array and / or an FPGA array (Field Programmable Gate Array).

[0061] Furthermore, the data analysis unit is also used to: process host computer instructions, and / or establish a monitoring model.

[0062] Furthermore, the cloud monitoring platform 1 also includes: a plurality of external ports of different protocols. Specifically, the external ports include but are not limited to a UART (Universal Asynchronous Receiver / Transmitter) interface, and / or an Ethernet interface, and / or a CAN (Controller Area Network) protocol interface, and / or a PCIE (Peripheral Component Interconnect Express, the latest bus and interface standard) interface, and / or an SPI (Serial Peripheral Interface) interface, and / or an RS485 interface.

[0063] Specifically, the host computer is connected to the cloud monitoring platform 1 through an Ethernet interface, so that it can send host computer instructions to the cloud monitoring platform 1; the eMMC is generally connected to the cloud monitoring platform 1 through an SPI interface, and other external interfaces, such as the CAN protocol interface can be connected to the CAN transceiver, the RS485 interface can be connected to the field data bus, and an external port can be set as a debugging port. The specific protocol is set or selected according to the debugging device.

[0064] It is understandable that the establishment of the monitoring model in the cloud monitoring platform 1 is based on existing big data analysis, integrating existing typical fault data, combining deep learning algorithms and existing rules, and can build a rich virtual load model and plan a mature fault prediction plan. The cloud monitoring platform 1 and the local monitoring node 2 have established a flexible shared interconnection mode. The external data information sent by the rich peripheral interfaces and the uploaded data of multiple local monitoring nodes 2 provide a basis for the establishment and improvement of the monitoring model. The high-computing power and high-performance data analysis unit has the ability to use typical fault data, external data information, and uploaded data to establish and correct the monitoring model. After the monitoring model is established, various types of data can be continuously updated to the large-capacity storage through various interfaces for the data analysis unit to update the monitoring model. At the same time, the cloud monitoring platform 1 also supports breakpoint resumption of various types of data.

[0065] The embodiment of the present invention discloses a specific rail transit signal monitoring system. Compared with the previous embodiment, this embodiment further illustrates and optimizes the technical solution.

[0066] Specifically, the signal analysis unit 23 is further configured to:

[0067] When the current device 3 is started, the preset analysis result of the device startup is output to the instruction output unit 24, so that the instruction output unit 24 issues an operation instruction corresponding to normal operation to the current device 3;

[0068] The signal acquisition unit 21 obtains the initial real-time signal when the current device 3 is started, and determines the analysis model corresponding to the current device 3 based on the initial real-time signal, so that during the operation of the current device 3, the analysis model is used to analyze the real-time signal according to the signal characteristic value and obtain the analysis result.

[0069] Therefore, see Figure 3 As shown, the action flow of the signal analysis unit 23 includes:

[0070] S1: When the current device is started, output the preset analysis result of the device startup to the instruction output unit, so that the instruction output unit issues an operation instruction corresponding to normal operation to the current device;

[0071] S2: Acquire the initial real-time signal when the current device is started through the signal acquisition unit, and determine the analysis model corresponding to the current device according to the initial real-time signal;

[0072] S3: During the operation of the current device, the analysis model is used to analyze the real-time signal according to the signal characteristic value and obtain the analysis result.

[0073] It can be understood that the signal analysis unit 23 cannot directly determine the device status when the current device 3 is started. It is necessary to first determine the analysis model based on the initial real-time signal obtained after the current device 3 is started according to normal operation. When the current device 3 is started and operates normally according to the operating instructions, the operating status is fed back to the local monitoring node 2, that is, the signal acquisition unit 21 collects the real-time signal of the current device 3, and then the signal analysis unit 23 performs routine status analysis and obtains the analysis results, and further instructs the output unit 24 to issue relevant operating instructions to the current device 3 according to the analysis results.

[0074] It can be understood that due to the limited storage capacity and computing speed of the local monitoring node 2, the signal characteristic values obtained by the feature acquisition unit 22 should be targeted to save computing time and storage space. Therefore, the feature acquisition unit 22 is specifically used to obtain and store the signal characteristic values of abnormal events corresponding to the current device 3 from the cloud monitoring platform 1.

[0075] Furthermore, the operation instruction is specifically used to control the current device 3 to output an analog signal of a preset value or to stop outputting the analog signal. It is understood that the operation instruction is used to control the current device 3 in order to cause the current device 3 to output a specific analog signal. This analog signal may be a preset value, such as the preset value required for normal operation of the current device 3 described above, or a preset value required to output the analog signal of the current device 3 to reduce the impact or eliminate the fault after an abnormal event occurs. When an abnormal event occurs, the current device 3 may also be directly stopped from outputting the analog signal, that is, the analog signal is required to be zero at this time. The specific implementation can be based on the response requirements of each device in the abnormality solution.

[0076] In some specific embodiments, the signal analysis unit 23 is specifically an MCU, FPGA or CPLD. Further, when the signal analysis unit 23 is an MCU, the MCU is a dual-core single MCU. It is understood that the dual-core single MCU architecture has the advantages of simple structure and high control accuracy.

[0077] In some specific embodiments, the local monitoring node 2 further includes:

[0078] The data temporary storage unit is used to store real-time signals, signal characteristic values, analysis results and operation instructions.

[0079] In some specific embodiments, the local monitoring node 2 further includes a device debugging port.

[0080] It is understood that the first communication unit 20 and the second communication unit 10 establish a communication connection between the cloud monitoring platform 1 and all local monitoring nodes 2. The second communication unit 10 can be wireless or wired communication, and different technical means are selected according to the size, importance, and communication speed of the data transmitted to the local monitoring nodes 2. If WiFi communication technology is used, a theoretical maximum data communication rate of 10 Mbps can be achieved.

[0081] It can be understood that the local monitoring node 2 in this embodiment has the characteristics of low power consumption, low cost, fast communication and safety orientation. The time taken for an independently running single task cycle does not exceed 100us, and it has faster response capability than the interconnected judgment of discrete systems.

[0082] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0083] The above is a detailed introduction to a rail transit signal monitoring system provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A rail transit signal monitoring system, characterized in that: include: A cloud-based monitoring platform and one or more local monitoring nodes, each of which includes: A first communication unit, configured to establish a communication connection with the cloud monitoring platform; Signal acquisition unit, used to collect real-time signals of current equipment; A feature acquisition unit, configured to acquire and store signal feature values of abnormal events from the cloud monitoring platform; A signal analysis unit, configured to analyze the real-time signal according to the signal characteristic value and obtain an analysis result; An instruction output unit, configured to issue corresponding operation instructions to the current device according to the analysis result; The current device is any load of a transportation track system, and the signal analysis unit is further used for: When the current device is started, outputting the preset analysis result of the device startup to the instruction output unit, so that the instruction output unit issues an operation instruction corresponding to normal operation to the current device; an action of acquiring, by the signal acquisition unit, an initial real-time signal when the current device is started, and determining an analysis model corresponding to the current device based on the initial real-time signal, so as to use the analysis model to analyze the real-time signal according to the signal characteristic value during operation of the current device and obtain an analysis result; The feature acquisition unit is specifically used for: Acquire and store the signal characteristic value of the abnormal event corresponding to the current device from the cloud monitoring platform; The operation instructions are specifically used to: Control the current device to output an analog signal of a preset value or stop outputting the analog signal; control the current device to stop outputting the analog signal when an abnormal event occurs; The local monitoring node also includes a device debugging port.

2. The monitoring system according to claim 1, characterized in that: The cloud monitoring platform includes: A second communication unit, configured to establish communication connections with all of the local monitoring nodes; a data acquisition unit, configured to receive uploaded data from all the local monitoring nodes, the uploaded data including the real-time signal, the analysis result, and the operation instruction; The data signal analysis unit is used to modify the judgment condition values of various events in the monitoring model according to the uploaded data, and the judgment condition values include the signal characteristic values of the abnormal events.

3. The monitoring system according to claim 2, characterized in that: The cloud monitoring platform also includes: A large-capacity memory is used to store all the uploaded data and all the judgment condition values.

4. The monitoring system according to claim 3, characterized in that: The large-capacity memory includes eMMC.

5. The monitoring system according to claim 2, characterized in that: The data signal analysis unit is specifically a CPU array and / or an FPGA array.

6. The monitoring system according to claim 5, characterized in that: The data signal analysis unit is further configured to: Process host computer instructions and / or establish the monitoring model.

7. The monitoring system according to claim 2, characterized in that: The cloud monitoring platform also includes: a plurality of external ports with different protocols.

8. The monitoring system according to claim 7, characterized in that: The external port includes a UART interface, and / or an Ethernet interface, and / or a CAN protocol interface, and / or a PCIE interface, and / or an SPI interface, and / or an RS485 interface.

9. The monitoring system according to claim 1, characterized in that: The signal analysis unit is specifically an MCU, FPGA or CPLD.

10. The monitoring system according to claim 9, characterized in that: When the signal analysis unit is the MCU, the MCU is a dual-core single MCU.

11. The monitoring system according to claim 1, characterized in that: The local monitoring node also includes: The data temporary storage unit is used to store the real-time signal, the signal characteristic value, the analysis result and the operation instruction.

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