Method and device for monitoring equipment in train control center system cabinet

Abstract

The invention provides a monitoring method and device for equipment in a train control center system cabinet, and relates to the technical field of train control systems. The main purpose is to accurately determine the position of a fault device when the device in a train control center system cabinet fails, and the technical scheme of the invention comprises the following steps: collecting real-time operation data of the device in the train control center system cabinet; identifying abnormal data and abnormal reasons in the real-time operation data based on historical operation data; according to the identification information of the abnormal data, target equipment generating the abnormal data and position information are determined through a positioning model, and the positioning model is used for simulating layout of equipment in a train control center system cabinet and graphical display of the running state; and through the position information, displaying the layout of a cabinet to which the target equipment belongs in a terminal interface, and displaying the abnormal reason beside the corresponding target equipment.

Description

Technical Field

[0001] The present application relates to the technical field of train control systems, and in particular to a method and device for monitoring equipment in a cabinet of a train control center system. Background Art

[0002] With the development of railway transportation, CTCS-2 train control system is widely used. The train control center, as the core of the system's ground safety equipment, undertakes many important functions such as driving permit generation and transmission, track circuit coding and control, etc., which is crucial to the safety of train operation.

[0003] At present, in order to ensure the safe operation of trains, the train control center system is fully monitored by microcomputer monitoring. This monitoring method relies on adding data acquisition devices and data processing devices to each device in the train control center system to obtain and analyze the data of the equipment in the train control center system, thereby achieving effective monitoring of the operating status of the equipment in the train control center system.

[0004] However, in actual application scenarios, when adding a data acquisition device and a data processing device to a train control center system, there are compatibility issues between the data acquisition device and / or the data processing device and the train control center system, which results in the inability to achieve all-round monitoring of the equipment in the train control center system. Therefore, an improved solution is proposed to solve the problem of accurately determining the location of the faulty equipment when a device in a cabinet of a train control center system fails. Summary of the invention

[0005] The embodiment of the present application provides a method and device for monitoring equipment in a cabinet of a train control center system, the purpose of which is to accurately determine the location information of the failed equipment when equipment in the cabinet of the train control center system fails.

[0006] In order to solve the above technical problems, the embodiments of the present application provide the following technical solutions:

[0007] In a first aspect, the present application provides a method for monitoring equipment in a cabinet of a train control center system, the method comprising:

[0008] Collect real-time operation data of equipment in the cabinet of the train control center system;

[0009] Identify abnormal data and abnormal causes in the real-time operation data based on historical operation data;

[0010] According to the identification information of the abnormal data, a target device and location information generating the abnormal data are determined using a positioning model, wherein the positioning model is used to simulate the layout of the devices in the system cabinet of the train control center and the graphical display of the operating status;

[0011] Through the location information, the layout of the cabinet to which the target device belongs is displayed in the terminal interface and the cause of the abnormality is displayed next to the corresponding target device.

[0012] In a second aspect, the present application provides a monitoring device for equipment in a cabinet of a train control center system, comprising:

[0013] The acquisition unit is used to collect real-time operation data of the equipment in the cabinet of the train control center system;

[0014] An identification unit, used to identify abnormal data and abnormal causes in the real-time operation data in the acquisition unit based on historical operation data;

[0015] a determination unit, configured to determine, according to the identification information of the abnormal data in the identification unit, a target device generating the abnormal data and location information by using a positioning model, wherein the positioning model is used to simulate the layout of devices in a system cabinet of a train control center and a graphical display of an operating status;

[0016] The display unit is used to display the layout of the cabinet to which the target device belongs in the terminal interface through the position information in the determination unit and to display the abnormal reason next to the corresponding target device.

[0017] In a third aspect, the present application also provides a computing device, comprising: at least one processor, and a memory, wherein the memory stores instructions executable by the processor, and the instructions are executed by the processor, so that the processor can execute the above-mentioned method for monitoring equipment in a cabinet of a train control center system.

[0018] In a fourth aspect, the present application also provides a readable storage medium, which is used to store a computer program, wherein when the computer program is running, it controls the device where the storage medium is located to execute the above-mentioned monitoring method for equipment in a cabinet of a train control center system.

[0019] By means of the above technical scheme, the present application provides a method and device for monitoring equipment in a cabinet of a train control center system. The scheme is automatically executed according to predetermined steps, that is, real-time operation data of equipment in a cabinet of a train control center system is collected, and the current status of the equipment can be fully captured to provide basic data for subsequent analysis; anomalies and causes are identified based on historical operation data, and more accurate judgments can be made with the help of past rules to provide a basis for determining abnormal data and abnormal causes; the target device and the location information of the target device are determined by combining the identification information of the abnormal data with the positioning model, and after the positioning model determines the target device, the positioning model simulates the layout of the cabinet and graphically displays the operating status of the equipment, so that the device that outputs fault data can intuitively present the location of the faulty device; finally, according to the location of the device that outputs the abnormal data, the layout of the cabinet to which the target device belongs is displayed on the terminal interface and the cause of the abnormality is displayed next to the corresponding target device, so that the operation and maintenance personnel can quickly and accurately obtain the location of the faulty equipment and the cause of the abnormality, carry out maintenance work efficiently, and ensure the safe operation of the train. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become easy to understand. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0021] Figure 1 A flow chart of a method for monitoring equipment in a cabinet of a train control center system proposed in one embodiment of the present application is shown;

[0022] Figure 2 A flowchart of a method for determining a positioning model proposed in one embodiment of the present application is shown;

[0023] Figure 3 A flow chart of another method for monitoring equipment in a cabinet of a train control center system proposed in one embodiment of the present application is shown;

[0024] Figure 4 A schematic diagram of the structure of a monitoring device for equipment in a cabinet of a train control center system provided by an embodiment of the present application is shown;

[0025] Figure 5 A schematic diagram of the structure of a monitoring device for equipment in a cabinet of a train control center system provided by another embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0027] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by technicians in the field to which this application belongs.

[0028] In the actual operation of the train control system CTCS2, the train control center system, as the core of ground safety equipment, shoulders important responsibilities such as driving permit generation and transmission, track circuit coding control, etc., which is crucial to the safety of train operation. At present, in order to ensure the safe operation of trains, microcomputer monitoring is used to monitor the train control center system in all directions. However, this monitoring method requires adding data acquisition and processing devices to the cabinet equipment of the train control center system to obtain analysis data and monitor the operation status of the equipment. However, in actual application, adding data acquisition devices and data processing devices to the train control center system will cause compatibility issues between the added devices and the train control center system, making it impossible to monitor the equipment in the system in all directions.

[0029] To this end, the inventor of the present application has proposed a method for monitoring equipment in a cabinet of a train control center system. The method can be automatically executed according to predetermined steps, that is, after collecting the real-time operating data of the equipment in the cabinet of the train control center system, it identifies whether the real-time operating data is abnormal based on the historical operating data, and uses the positioning model to determine the target device and location information that outputs the abnormal data based on the abnormal data and the cause of the abnormality, and displays the layout of the cabinet to which the target device belongs in the terminal interface according to its location information and displays the cause of the abnormality next to the corresponding target device, so as to accurately and clearly determine the location of the faulty equipment and the cause of the fault. A method for monitoring equipment in a cabinet of a train control center system in an embodiment of the present application, the specific steps of which are as follows: Figure 1 As shown, including:

[0030] Step 101: Collect real-time operating data of equipment in the cabinet of the train control center system.

[0031] In this step, real-time operation data refers to various types of data generated by each device in the system cabinet of the train control center during its current operation. These data can reflect the current working status of the equipment, such as the equipment's temperature, voltage, current, operating frequency, working status codes of each component, and other information. By collecting and analyzing these real-time data, the equipment's operating status can be understood in a timely manner.

[0032] Before executing this step, it is necessary to connect the monitoring system to the lower machine position of the train control center system, that is, through a professional data acquisition card or an information acquisition terminal with multiple interfaces, the monitoring system can be connected to the communication interface corresponding to each device in the lower machine position of the train control center system, so as to obtain the real-time operation data of the equipment in the cabinet of the train control center system.

[0033] Step 102: Identify abnormal data and abnormal causes in the real-time operation data based on historical operation data.

[0034] In this step, the historical operation data is the data record accumulated when the equipment in the cabinet of the train control center system was running in the past period of time. It contains the operating parameters and status information of the equipment under different working conditions and different time periods. Abnormal data refers to data generated when the equipment is running, which does not match the data characteristics generated when the equipment is in normal operation. The appearance of abnormal data indicates that there is a fault in the equipment. The cause of the abnormality refers to the root cause of the abnormal data generated by the equipment. It may be a fault in the hardware of the equipment itself, such as damage to a component, aging of the line, etc.; it may also be a software problem, such as program running errors, abnormal configuration parameters, etc. It may also be affected by external environmental factors, such as excessive temperature, electromagnetic interference, etc.

[0035] After the real-time operation data of the equipment in the cabinet of the train control center system is collected in step 101, this step identifies the abnormal data and the abnormal reasons in the real-time operation data according to the historical operation data. Specifically, it can be that after the operation data value of each device during normal operation is determined by using the statistical analysis method according to the historical operation data, the real-time operation data of the equipment in the cabinet of the train control center system is matched with the operation data value of its corresponding device during normal operation. If there is no match, the real-time operation data of the corresponding device is determined to be abnormal data. Before the operation data of each device during normal operation is determined by using the statistical analysis method according to the historical operation data, the historical operation data is also pre-processed, including data cleaning, data format unification and other operations. Data cleaning can be to remove noise, duplicate data, obviously erroneous data, etc. in the data to ensure the quality of the data. Data format unification is to convert real-time operation data and historical operation data of different sources and formats into a unified format that is convenient for subsequent analysis and processing, such as converting all data into numerical data and arranging them in a specific field order. In addition, before using statistical analysis methods based on historical operating data to determine the operating data of each device during normal operation, the historical operating data is also classified. The specific classification method can be based on the type of equipment, time, or function of the equipment, so that when abnormal data is identified, historical data of relevant dimensions can be quickly retrieved for comparative analysis.

[0036] In this step, the abnormal cause of the real-time operation data can be determined by searching the preset cause strategy table according to the identification information of the abnormal data, or it can be determined based on a trained abnormal cause search machine learning model, that is, the identification information data of the abnormal data is input into the trained abnormal cause search machine learning model, and the model will directly input the abnormal cause. Among them, the abnormal cause search machine learning model is trained based on the abnormal data and the abnormal data causes in the historical operation data. After the model output data accuracy reaches the target probability, it is determined that the abnormal cause search machine learning model is the trained abnormal cause search machine learning model.

[0037] Step 103: Determine the target device and location information that generates the abnormal data using a positioning model according to the identification information of the abnormal data.

[0038] In this step, the positioning mode is used to simulate the layout of the equipment in the system cabinet of the train control center and the graphical display of the operating status.

[0039] After the abnormal data and the abnormal cause in the real-time operation data are identified in step 102, this step matches the device that outputs the abnormal data according to the identification information of the abnormal data, and the positioning model displays the status of the device that outputs the abnormal data on the terminal interface of the positioning model according to the identification information of the device that outputs the abnormal data. At this time, the maintenance personnel can directly determine the specific location of the faulty device in the system cabinet of the train control center according to the status display of the device on the terminal interface and the location of the device on the terminal interface.

[0040] It is worth noting that if this step 102 determines that there is no abnormal data in the real-time operation data, the device identification information in the real-time operation data is directly matched with the device identification information in the positioning model to determine the name and location of the normally operating device, so that the operating status and location of the normally operating device are displayed in the terminal interface.

[0041] Step 104: Using the location information, display the layout of the cabinet to which the target device belongs in the terminal interface and display the abnormality reason next to the corresponding target device.

[0042] In this step, the terminal interface is a human-computer interaction interface for operation and maintenance personnel to view the equipment monitoring information in the cabinet of the train control center system. It is a software interface that can be installed on computers, mobile terminals and other devices in the monitoring room. This interface can display various related information such as cabinet layout, equipment location information, equipment operating status, abnormal data and reasons, so that operation and maintenance personnel can intuitively understand the equipment status and perform corresponding operations. When displaying the layout of the cabinet to which the target device belongs in the terminal interface, the color of the device icon at the corresponding position in the terminal interface can be set to be different from the icon color when the device is operating normally based on the location information of the faulty device.

[0043] After determining the target device and location information that generated the abnormal data in step 103, the location of the cabinet to which the target device belongs is displayed in the terminal interface, and the abnormal cause is displayed next to the corresponding target device. In this step, the abnormal cause can be displayed in a manner that combines sound reminders with color reminders. For example, when the abnormal cause of abnormal temperature rise is detected, the system can clearly broadcast "The temperature of the device [specific device name] is too high, please check the heat dissipation in time" through voice, so that the operation and maintenance personnel can check the specific device location information in the terminal display interface as soon as possible after hearing the prompt. At the same time, the display of the device location on the terminal display interface can be displayed in a flashing prompt manner, so that the icon of the target device flashes at a specific frequency on the terminal interface, wherein different flashing frequencies or colors can correspond to abnormal causes of different severity. For example, a relatively minor abnormality is displayed in a slower yellow flashing, prompting the operation and maintenance personnel to check and handle it at an appropriate time, while an abnormality that seriously endangers the safety of equipment operation is presented in a fast red flashing, so as to attract the attention of the operation and maintenance personnel and prompt them to take immediate action. In addition, the cause of the abnormality can be displayed in the form of a pop-up information box. In addition to the detailed text description of the cause of the abnormality, the information box can also be accompanied by links to historical fault records of related equipment, possible solutions, etc., so that operation and maintenance personnel can fully understand the situation and quickly make accurate processing decisions. The cause of the abnormality can even be displayed in the form of a dynamic chart, such as using a line chart to intuitively present the change trend of a certain parameter of the equipment over time, marking the time point when the equipment outputs abnormal data and the corresponding abnormal cause in the chart, so that operation and maintenance personnel can have a deeper understanding of the process and cause of the equipment abnormality from the perspective of data changes.

[0044] It is worth noting that the display method of the abnormal cause is not overly limited here. If the monitoring system does not need to display the abnormal cause, the abnormal cause can be replaced by an identification symbol next to the corresponding target device. For example, a small icon of a specific shape (such as an exclamation mark icon indicates an abnormality but the detailed cause is not displayed for the time being) is used to remind the operation and maintenance personnel that the device has an abnormality. The operation and maintenance personnel can further click on the icon to obtain detailed abnormality information according to actual needs, or control whether to expand to view the complete abnormal cause content through specific options in the system settings, so as to avoid visual interference caused by too much information, and quickly obtain comprehensive and accurate abnormality-related information when the operation and maintenance personnel need in-depth information.

[0045] Based on the above Figure 1 It can be seen from the implementation method that the present application provides a monitoring method for equipment in the cabinet of the train control center system. The scheme is automatically executed according to the established steps, that is, the real-time operation data of the equipment in the cabinet of the train control center system is collected, which can comprehensively capture the current status of the equipment and provide basic data for subsequent analysis; based on the historical operation data, the abnormalities and causes are identified, and more accurate judgments can be made with the help of past rules to provide a basis for determining abnormal data and abnormal causes; by combining the identification information of the abnormal data with the positioning model, the target device and the location information of the target device are determined, and after the positioning model determines the target device, the graphical display of the cabinet layout and the operating status is simulated, so that the device that outputs fault data can intuitively present the location of the faulty device; finally, according to the location of the device that outputs the abnormal data, the layout of the cabinet to which the target device belongs is displayed on the terminal interface and the cause of the abnormality is displayed next to the corresponding target device, so that the operation and maintenance personnel can quickly and accurately obtain the location of the faulty equipment and the cause of the abnormality, carry out maintenance work efficiently, and ensure the safe operation of the train.

[0046] Furthermore, according to the above Figure 1 In the embodiment of the present invention shown in FIG. 1 , before determining the target device and location information of the abnormal data using the positioning model according to the identification information of the abnormal data, how to determine the positioning model is described. The embodiment of the present invention will be described in more detail. The specific steps are as follows: Figure 2 As shown, including:

[0047] Step 201: Acquire parameter data of a system cabinet of a train control center and location information of equipment in the system cabinet of a train control center.

[0048] In this step, the parameter data of the train control center system cabinet refers to various characteristics and setting data related to the train control center system cabinet itself. For example, it can be the number of layers and slot information of the train control center system cabinet, or the size information of the train control center system cabinet, or the type of the train control center system cabinet, the type and number of cabinet interface, cabinet capacity, etc. The location information of the equipment in the train control center system cabinet refers to the specific location of the equipment in the train control center system cabinet. For example, the existing train control center system integrated cabinet has 5 layers, each layer has 10 slots, and at this time, switch 1 is in the 4th slot of the 2nd layer, so the location information of switch 1 is the 4th slot of the 2nd layer.

[0049] In this step, the parameter data of the cabinet of the train control center system can be obtained by consulting the official documents such as the product manual and technical manual of the cabinet to obtain accurate information such as size, type, capacity, etc., or by directly extracting the relevant configuration files from the train control center system, parsing the configuration files, and then obtaining the parameter data of the cabinet of the train control center system. The location information of the equipment in the cabinet of the train control center system can be obtained by making detailed records when the equipment is initially installed, or by using automated positioning technology, such as installing sensors with positioning functions in the cabinet (such as infrared sensors, radio frequency identification (RFID) tags and readers, etc.), using sensors to monitor and feedback the location information of the equipment in real time, or by directly extracting the relevant configuration files from the train control center system, parsing the configuration files, and then obtaining the location information of the equipment in the cabinet of the train control center system.

[0050] Here are some examples to illustrate the above content:

[0051] For example: the monitoring system establishes a connection with the train control center system, obtains the *HDW file from the train control center system, stores the file in the corresponding folder, such as the CFG folder, and then parses the *HDW file in the CFG folder. The parsed data is that the central cabinet of the train control system is a comprehensive cabinet and a mining and driving cabinet. Among them, there are five layers in the comprehensive cabinet, there is no equipment in the slot on the first layer, there are two slots and equipment in the slot on the second layer, there are three slots and equipment in the slot on the third layer, there is no equipment in the slot on the fourth layer, and there are two slots and equipment in the slot on the fifth layer; there are five layers in the mining and driving cabinet, there is no equipment in the slot on the first layer, there are two slots and equipment in the slot on the second layer, there are three slots and equipment in the slot on the third layer, there are two slots and equipment in the slot on the fourth layer, and there are two slots and equipment in the slot on the fifth layer. The integrated cabinet contains A / B machine master control, standby, offline status indicator lights, switches and other equipment. The procurement and drive cabinet contains VLE boards, VPS boards, IOBUS boards, DVCOM boards, IOBE boards, VIIB boards, VOOB boards and other boards. The monitoring system also parses from the *HDW file that the A / B machine master control is in the first slot on the second layer of the integrated cabinet, the standby and offline status indicator lights are in the second slot on the second layer of the integrated cabinet, and the switch is in the second slot on the fifth layer of the integrated cabinet. The VLE board is in the first slot on the second layer of the procurement and drive cabinet, the VPS board is in the first slot on the third layer of the procurement and drive cabinet, the IOBUS board is in the third slot on the third layer of the procurement and drive cabinet, the DVCOM board is in the second slot on the fourth layer of the procurement and drive cabinet, the IOBE board is in the first slot on the fourth layer of the procurement and drive cabinet, the VIIB board is in the first slot on the fifth layer of the procurement and drive cabinet, and the VOOB board is in the second slot on the fifth layer of the procurement and drive cabinet. At this time, the parameters of the train control center system cabinet of the current station are obtained, including the location information of the equipment in the train control center system cabinet, such as the cabinet structure and the location information of the equipment in the cabinet (switches, displays, power modules, boards, etc.).

[0052] Step 202: Determine the framework of the positioning model based on the parameter data of the system cabinet of the train control center.

[0053] In this step, a specific method is given for determining the framework of the positioning model, such as obtaining the number of layers information of the system cabinet of the train control center and the slot information of each layer, and determining the positioning model framework according to the number of layers information of the system cabinet of the train control center and the slot information of each layer. For example, the number of layers of the system cabinet of the train control center of the current station is 5, and the number of slots of each layer is 3, 5, 6, 2, 5 respectively. At this time, the framework of the positioning model is determined to be "the number of layers is 5, and the number of slots of each layer is 3, 5, 6, 2, 5 respectively". In this embodiment, the size information, the number of layers information and the slot information of each layer of the train control center cabinet can also be jointly determined, and the determination method is consistent with the above method, that is, the framework of the positioning model that is consistent with the size information, the number of layers information and the slot information of each layer of the train control center cabinet is selected.

[0054] Step 203: Render the framework of the positioning model based on the location information of the equipment in the cabinet of the train control center system to obtain the positioning model.

[0055] After determining the framework of the positioning model in step 202, this step renders the framework of the positioning model in combination with the location information of the equipment in the cabinet of the train control center system. The specific rendering method is as follows: classify the equipment location information according to the number of layers to obtain equipment location information of different levels; match the slot information of each layer according to the equipment location information of different levels to obtain the positioning model.

[0056] Specifically, the location information of the equipment in the cabinet of the train control center system is first classified according to the number of layers of the cabinet to obtain the location information of the equipment in different layers, and the location information of the equipment at any layer of the cabinet of the train control center system is obtained according to the order of the layers of different layers, and the location information of the equipment at any layer of the cabinet of the train control center system is matched according to the slot sequence in the slot information. For example, the framework of the existing positioning model is "the number of layers is 4, and the number of slots in each layer is 3, 5, 6, and 2 respectively". At this time, according to this framework, the rendering starts from the first layer to determine whether there is a device in the first slot of the first layer. If not, fill in the blank; if so, the device is rendered in the framework of the positioning model according to the device location information. After the rendering of the equipment in the first slot is completed, the second slot is continued to be rendered in the same way as the first slot, that is, it is determined whether there is a device in the second slot... After the first layer is rendered, the second layer is rendered in the same way as the first layer, and so on until the positioning model is obtained.

[0057] It is worth noting that in this step, the order of the layers of different levels can be from low to high, from high to low, or a preset order of layers, and no further restrictions are made here. For the groove sequence, it can be from high to low, from low to high, or a preset groove sequence, and no further restrictions are made here.

[0058] In summary, in this embodiment, by selecting the positioning model framework according to the specific parameter information of the cabinet of the train control center system of the current station, it is ensured that the positioning model framework is the same as the actual cabinet framework, avoiding the selection of a framework that is too small, and the device icon cannot be displayed on the terminal interface, thereby ensuring that the device can be displayed on the terminal interface; the positioning model framework is rendered according to the order of the cabinet layers and the slot sequence of each layer, ensuring that the equipment in the cabinet of the train control center system of the current station is accurately rendered into the positioning model, ensuring that the layout of the cabinet where the target device is located is accurate and correct when the terminal interface is displayed, so that the maintenance personnel can accurately determine the faulty equipment in the cabinet of the train control center of the current station according to the terminal interface display.

[0059] Furthermore, according to the above Figure 1In the embodiment of the present invention shown in the figure, after collecting the real-time operation data of the equipment in the cabinet of the train control center system, when the equipment in the cabinet of the train control center system fails, how to enable the maintenance personnel to accurately determine the location information of the failed equipment. The embodiment of the present invention will be described in more detail, and the specific steps are as follows Figure 3 As shown, including:

[0060] Step 301: Identify abnormal data in the real-time operation data based on historical operation data.

[0061] Before identifying abnormal data in real-time operation data according to historical operation data, this embodiment also classifies and processes the historical operation data. The specific method is: according to the equipment category information in the cabinet of the train control center system in the historical operation data, the historical operation data is classified and stored, and the classified historical operation data is cleaned to obtain classified historical operation data. It is worth noting that the equipment category information can be determined based on the equipment function information, such as acquisition function, drive function, control operation function, etc., or it can be determined by the equipment name, and there is no excessive limitation on this. In terms of data cleaning, it can be judged whether the classified data is missing according to the timestamp, or whether there is an instantaneous jump in the equipment data within the preset time period. If there is an instantaneous jump, the data is removed, and the average value of the value before and after the removal is used as the normal data value. By classifying the historical operation data, it is possible to make it unnecessary to search and judge in a large number of data when identifying abnormal data later, and it is only necessary to judge within the category described, thereby improving the efficiency and accuracy of identifying abnormal data. In addition, data cleaning of the historical operation data can ensure the accuracy of the historical operation data, thereby making the abnormal data in the real-time operation data identified according to the historical operation data more accurate.

[0062] In this step, the method for identifying abnormal data may be to obtain category information of equipment in the cabinet of the train control center system, match the classified historical operation data according to the category information, and after determining the classified historical operation data, use statistical analysis to identify abnormal data in the real-time operation data.

[0063] Specifically, based on the real-time operation data, the category information of the equipment in the system cabinet of the train control center is obtained, and the classified historical operation data is matched according to the category information to determine the classified historical operation data to which the real-time operation data to be judged belongs, and the abnormal data in the real-time operation data is identified according to the statistical analysis method. If the category information of the equipment in the system cabinet of the train control center does not match the corresponding classified historical operation data, the data supplement instruction is triggered, and according to the data supplement instruction, the historical operation data corresponding to the equipment in the system cabinet of the train control center is extracted from the backup data source.

[0064] After determining the abnormal data in the real-time operation data, the present embodiment also analyzes the abnormal cause of the abnormal data. The specific analysis method is to search according to the identification information of the abnormal data and the preset cause strategy table determined according to the historical operation data to determine the abnormal cause. After determining the abnormal cause, the number of abnormalities of the equipment in the cabinet of the train control center system is counted according to the identification information of the abnormal data. When the number of abnormalities of the equipment is greater than the preset threshold within the first preset time, the equipment is marked as a high-frequency abnormality. At this time, the icon of the high-frequency abnormal equipment on the terminal interface can be highlighted to ensure that the maintenance personnel can intuitively observe the operating status of the high-frequency abnormal equipment. The method of determining the preset cause strategy table according to the historical operation data can be determined according to the situation of abnormal data appearing in the historical operation data and the abnormal cause determined by the maintenance personnel when the abnormal data appears, and this preset cause strategy table is updated in real time, and its update method is data cumulative update, that is, when the output data of the equipment in the train control center system is abnormal, the data abnormal cause and the equipment identification information are added to the preset cause strategy table.

[0065] It is worth noting that the data supplement instruction contains relevant information about the equipment to be supplemented, which may be the amount of data for which historical operating data is required. The backup data source is the data stored in the cloud disk of the column control center system. The statistical analysis method is to determine the normal working range value based on the operating status and output data value of the classified historical operating data within a preset time, and the output data when the equipment is operating normally, and compare the normal working range value with the real-time operating data to judge the abnormal data in the real-time operating data. In summary, according to the category information of the equipment in the real-time operating data, the corresponding classified historical operating data is matched. When identifying abnormal data based on the historical operating data, the influence of historical operating data that is not related to the real-time operating data to be judged is avoided, which not only improves the judgment efficiency, but also improves the accuracy of judging whether there is abnormal data in the real-time operating data.

[0066] Step 302: According to the identification information of the abnormal data, a positioning model is used to determine the target device and location information that generates the abnormal data.

[0067] After the abnormal data is determined in step 301, this step obtains the identification information of the device that outputs the abnormal data based on the identification information of the abnormal data, and matches the device identification information with the identification information of the device in the positioning model to determine the target device and location information of the abnormal data.

[0068] Specifically, the device that outputs abnormal data and the location information of the device are determined by matching the device identifier of the abnormal data with the identifier of the device in the positioning model. The abnormal data identifier may refer to data carrying the identifier information of the device that outputs abnormal data.

[0069] Step 303: Using the location information, a layout of the cabinet to which the target device belongs and a graphical display of the operating status are displayed in the terminal interface.

[0070] After determining the target device and location information of the output abnormal data in step 302, the specific location of the target device in the corresponding cabinet is displayed in the terminal interface. There is also a reason display button at the target device display of the terminal interface. When the maintenance personnel directly determine the abnormal cause after determining the target device and its location, the reason display button can be turned off; if the maintenance personnel cannot directly determine the abnormal cause after determining the target device and its location, the reason display button can be turned on, so that the maintenance personnel can accurately locate the faulty device and repair it according to the display position and abnormal cause on the terminal interface.

[0071] In this embodiment, the historical operation data is classified according to the category information of the equipment, which provides a basis for the subsequent identification of abnormal data in the real-time operation data based on the historical operation data. The historical operation data of the target equipment can be determined for the target equipment, thereby ensuring the accuracy of identifying abnormal data in the real-time operation data. Secondly, the target equipment and location information that generate the abnormal data are determined using the positioning model, and the equipment that outputs the abnormal data can be accurately determined, providing an accurate data basis for the subsequent display of the location information on the terminal interface. Finally, based on the location data determined using the positioning model, the layout of the cabinet to which the target equipment belongs and the graphical display of the operating status are displayed on the final model, so that maintenance personnel can determine the location of the equipment that outputs the abnormal data at a glance based on the graphical display of the terminal interface.

[0072] Furthermore, as a response to the above Figure 1-3 In order to realize the embodiment of the method shown, the embodiment of the present invention also provides a monitoring device for equipment in the cabinet of the train control center system. The device is used to accurately and automatically determine the fault location of the equipment in the cabinet of the train control center system when a fault occurs in the equipment in the cabinet of the train control center system. The embodiment of the device corresponds to the aforementioned method embodiment. For ease of reading, this embodiment will no longer repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Specifically, Figure 4 As shown, the device comprises:

[0073] The collection unit 41 is used to collect real-time operation data of the equipment in the cabinet of the train control center system;

[0074] An identification unit 42, configured to identify abnormal data and abnormal causes in the real-time operation data in the acquisition unit 41 based on historical operation data;

[0075] A determination unit 43 is used to determine the target device and location information that generates the abnormal data using a positioning model according to the identification information of the abnormal data in the identification unit 42, wherein the positioning model is used to simulate the layout of the devices in the system cabinet of the train control center and the graphical display of the operating status;

[0076] The display unit 44 is used to display the layout of the cabinet to which the target device belongs in the terminal interface through the location information in the determination unit 43 and to display the abnormality cause next to the corresponding target device.

[0077] Further, such as Figure 5 As shown, the device further includes a model determination unit 45, and the model determination unit 45 includes:

[0078] The acquisition module 451 is used to acquire parameter data of the train control center system cabinet and location information of equipment in the train control center system cabinet;

[0079] A framework determination module 452 is used to determine the framework of the positioning model based on the parameter data of the cabinet of the train control center system in the acquisition module 451;

[0080] The rendering module 453 is used to render the framework of the positioning model of the determining framework module 452 based on the location information of the equipment in the cabinet of the train control center system obtained by the obtaining module 451 to obtain the positioning model.

[0081] Further, such as Figure 5 As shown, the determining framework module 452 includes:

[0082] The acquisition submodule 4521 is used to obtain the number of layers of the cabinets of the train control center system and the slot information of each layer;

[0083] The framework determination submodule 4522 is used to determine the positioning model framework according to the number of layers information of the system cabinet of the train control center and the channel information of each layer obtained by the submodule 4521.

[0084] Further, such as Figure 5 As shown, the rendering module 453 includes:

[0085] The acquisition position submodule 4531 is used to classify the position information based on the layer number information to obtain device position information of different layers;

[0086] The matching submodule 4532 is used to match the channel information of each layer based on the device location information of different layers to obtain the positioning model.

[0087] The matching submodule 4532 also includes obtaining the device location information of any level of the system cabinet of the train control center based on the order of the levels of different levels; and matching the device location information of any level of the system cabinet of the train control center based on the slot sequence in the slot information.

[0088] Further, such as Figure 5 As shown, before the identification unit 42, the device further includes a processing unit 46, and the processing unit 46 includes:

[0089] A classification storage module 461 is used to classify and store the historical operation data according to the equipment category information in the cabinet of the train control center system in the historical operation data;

[0090] The data processing module 462 is used to clean the classified historical operation data in the classification storage module 461 to obtain classified historical operation data.

[0091] Further, such as Figure 5 As shown, the identification unit 42 includes:

[0092] The category acquisition module 421 is used to obtain category information of the equipment in the cabinet of the train control center system;

[0093] A matching historical data module 422 is used to match the classified historical operation data based on the category information in the obtaining category module 421;

[0094] An abnormality determination module 423 is used to identify abnormal data in the real-time operation data by using a statistical analysis method after the matching historical data module 422 determines the classified historical operation data;

[0095] The abnormality determination module 423 is used to determine the abnormality cause based on the abnormal data in combination with a preset cause strategy table.

[0096] Further, such as Figure 5 As shown, the matching history data module 422 includes:

[0097] The trigger instruction submodule 4221 is used to trigger a data supplement instruction if the category information of the equipment in the cabinet of the train control center system does not match the corresponding classified historical operation data;

[0098] The extraction submodule 4222 is used to extract the historical operation data corresponding to the equipment in the cabinet of the train control center system from the backup data source based on the data supplement instruction of the trigger instruction submodule 4221.

[0099] Further, such as Figure 5 As shown, the device further includes a marking unit 47, specifically including:

[0100] A statistics module 471 is used to count the number of abnormalities of the device according to the identification information of the abnormal data;

[0101] The marking module 472 is used to mark the device as a high-frequency abnormality if the number of abnormalities of the device in the statistical module 471 is greater than a preset threshold within a preset time period.

[0102] Further, such as Figure 5 As shown, the determining unit 43 includes:

[0103] An output identification module 431 is used to obtain identification information of a device that outputs the abnormal data based on the identification information of the abnormal data;

[0104] The target device determination module 432 is used to match the device identification information of the output identification module 431 with the identification information of the device in the positioning model to determine the target device and location information of the abnormal data.

[0105] Furthermore, an embodiment of the present application also provides a computing device, the computing device comprising: at least one processor, and a memory, wherein the memory stores instructions executable by the processor, the instructions are executed by the processor, so that the processor can perform the above-mentioned Figure 1-3 The monitoring method for equipment in the cabinet of the train control center system described in.

[0106] Furthermore, an embodiment of the present application further provides a readable storage medium, wherein the readable storage medium is used to store a computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the above Figure 1-3 The monitoring method for equipment in the cabinet of the train control center system described in.

[0107] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0108] It is understandable that the related features in the above methods and devices can be referenced to each other. In addition, the "first", "second" and the like in the above embodiments are used to distinguish the embodiments, but do not represent the advantages and disadvantages of the embodiments.

[0109] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0110] The algorithm and display provided herein are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description of the above specific languages ​​is for disclosing the best mode of the present invention.

[0111] In addition, the memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0112] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0113] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0114] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0115] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0116] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0117] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0118] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0119] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0120] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The above is only a specific implementation method of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for monitoring equipment in a cabinet of a train control center system, characterized in that: include: Collect real-time operation data of equipment in the cabinet of the train control center system; Identify abnormal data and abnormal causes in the real-time operation data based on historical operation data; According to the identification information of the abnormal data, a target device and location information generating the abnormal data are determined using a positioning model, wherein the positioning model is used to simulate the layout of the devices in the system cabinet of the train control center and the graphical display of the operating status; Through the location information, the layout of the cabinet to which the target device belongs is displayed in the terminal interface and the cause of the abnormality is displayed next to the corresponding target device.

2. The method according to claim 1, characterized in that Before determining the target device and location information of the abnormal data using the positioning model according to the identification information of the abnormal data, the method further includes: acquiring parameter data of a cabinet of a train control center system and location information of a device in the cabinet of the train control center system; Determine the framework of the positioning model based on the parameter data of the system cabinet of the train control center; Based on the location information of the equipment in the cabinet of the train control center system, the framework of the positioning model is rendered to obtain the positioning model.

3. The method according to claim 2, characterized in that The determining of the framework of the positioning model based on the parameter data of the system cabinet of the train control center includes: Obtaining the number of layers of the system cabinets of the train control center and the slot information of each layer; The positioning model framework is determined according to the number of layers of the system cabinets of the train control center and the slot information of each layer.

4. The method according to claim 3, characterized in that: The rendering of the framework of the positioning model based on the location information of the device in the cabinet of the train control center system to obtain the positioning model includes: Based on the layer number information, the location information is classified to obtain device location information of different layers; Based on the equipment location information of the different levels, the channel information of each level is matched to obtain the positioning model.

5. The method according to claim 4, characterized in that The matching of the slot information of each layer based on the device location information of different layers to obtain the positioning model includes: Based on the order of different levels, obtain the location information of equipment at any level of the system cabinet of the train control center; Based on the slot sequence in the slot information, any level of equipment location information of the system cabinet of the train control center is matched.

6. The method according to claim 1, characterized in that Before identifying abnormal data and abnormal causes in the real-time operation data based on the historical operation data, the method includes: Classify and store the historical operation data according to the equipment category information in the cabinet of the train control center system in the historical operation data; The classified historical operation data is cleaned to obtain classified historical operation data.

7. The method according to claim 6, characterized in that The identifying abnormal data and abnormal causes in the real-time operation data based on the historical operation data includes: Obtaining category information of equipment in the cabinet of the train control center system; Based on the category information, matching the classified historical operation data; After the classified historical operation data is determined, the abnormal data in the real-time operation data is identified by using statistical analysis; Based on the abnormal data, combined with the preset cause strategy table, the cause of the abnormality is determined.

8. A monitoring device for equipment in a cabinet of a train control center system, characterized in that: include: The acquisition unit is used to collect real-time operation data of the equipment in the cabinet of the train control center system; An identification unit, used to identify abnormal data and abnormal causes in the real-time operation data in the acquisition unit based on historical operation data; a determination unit, configured to determine, according to the identification information of the abnormal data in the identification unit, a target device generating the abnormal data and location information by using a positioning model, wherein the positioning model is used to simulate the layout of devices in a cabinet of a train control center system and a graphical display of an operating status; The display unit is used to display the layout of the cabinet to which the target device belongs in the terminal interface through the position information in the determination unit and to display the abnormal reason next to the corresponding target device.

9. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the method for monitoring equipment in a cabinet of a train control center system according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The device includes at least one processor, and at least one memory and a bus connected to the processor; wherein the processor and the memory communicate with each other through the bus; the processor is used to call the program instructions in the memory to execute the monitoring method for equipment in the cabinet of the train control center system according to any one of claims 1-7.

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