Train fault diagnosis method and device and electronic equipment

Abstract

The invention provides a train fault diagnosis method and device and electronic equipment, and belongs to the technical field of fault detection.The method comprises the steps that first interface data obtained from an intelligent operation and maintenance interface and second interface data obtained from a train information service interface of a train to be diagnosed are utilized; and performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree step by step to obtain a fault diagnosis result of the to-be-diagnosed train. According to the train fault diagnosis method and device and the electronic equipment provided by the invention, the fault diagnosis decision tree is constructed in advance, different data of the train to be diagnosed are actually acquired from different IMS interfaces and TIAS interfaces, step-by-step fault diagnosis analysis based on the fault diagnosis decision tree is carried out, and the fault diagnosis accuracy is improved. According to the train fault detection method, the fault condition of the train component indirectly or directly connected with the IMS interface and the TIAS interface can be quickly and accurately diagnosed, the train fault detection efficiency, accuracy and reliability are improved, and powerful technical support can be provided for reliable operation of the train.

Description

Technical Field

[0001] The present invention relates to the technical field of fault detection, and particularly to a train fault diagnosis method, device and electronic device. Background Art

[0002] Train fault detection is an important means for train maintenance and ensuring the safe and efficient operation of trains.

[0003] Traditional train fault detection methods rely on the experience and intuition of maintenance personnel to detect faults in train systems and components, and cannot directly identify the specific types of train faults. The real-time performance, accuracy and reliability of train fault detection are limited, and it is difficult to meet the fault detection requirements under the high-speed, safe and large-scale operation of trains.

[0004] Therefore, it is necessary to provide a train fault detection solution with higher efficiency, accuracy and reliability. Summary of the Invention

[0005] The present invention provides a train fault diagnosis method, device and electronic device to solve the defect of relying on the experience and intuition of maintenance personnel for train fault detection in the prior art, and to implement a train fault detection solution with higher efficiency, accuracy and reliability.

[0006] The present invention provides a train fault diagnosis method, including: Using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, gradually perform train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed.

[0007] According to a train fault diagnosis method provided by the present invention, the fault diagnosis decision tree is pre-constructed based on the following method: According to the theoretically obtainable interface data of the intelligent operation and maintenance interface and the train information service interface, define a state variable table; define a fault state table for each component of the train; based on the operation state variables corresponding to each train operation state in the state variable table and the fault state variables corresponding to each fault state of each component of the train in the fault state table, construct a fault diagnosis truth table; based on the fault diagnosis truth table, construct a fault diagnosis decision tree.

[0008] According to a train fault diagnosis method provided by the present invention, the step of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, gradually performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed includes: Based on the first interface data, determine whether the train to be diagnosed is online; if the train to be diagnosed is online, obtain that the fault diagnosis result is that there is no fault with the train to be diagnosed.

[0009] According to a train fault diagnosis method provided by the present invention, by using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, and gradually performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed, it further includes: If the train to be diagnosed is not online, then based on the train access unit status data in the first interface data, determine whether there is a fault with the train access unit; if there is a fault with the train access unit, obtain that the fault diagnosis result is that the train access unit of the train to be diagnosed is faulty.

[0010] According to a train fault diagnosis method provided by the present invention, by using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, and gradually performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed, it further includes: If there is no fault with the train access unit, then determine whether the first interface data includes the alarm information of the automatic train protection unit fed back by the monitoring board; if the alarm information is included, obtain that the fault diagnosis result is that the automatic train protection unit of the train to be diagnosed is faulty.

[0011] According to a train fault diagnosis method provided by the present invention, by using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, and gradually performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed, it further includes: If the alarm information is not included, then based on the second interface data, determine whether the train to be diagnosed is a communication vehicle; if the train to be diagnosed is a communication vehicle, obtain that the fault diagnosis result is that the monitoring board of the train to be diagnosed is faulty.

[0012] According to a train fault diagnosis method provided by the present invention, by using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, and gradually performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed, it further includes: If the train to be diagnosed is not a communication vehicle, determine whether the reception of the second interface data is normal; if the reception of the second interface data is normal, and it is determined based on the second interface data that the train to be diagnosed is on the main line and the train to be diagnosed is not a communication control train, the obtained fault diagnosis result is that both the automatic train protection unit and the monitoring board of the train to be diagnosed have failed.

[0013] According to a train fault diagnosis method provided by the present invention, the method of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface to perform step-by-step train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed further includes: If the reception of the second interface data is abnormal, based on the last received second interface data, obtain the last position of the train to be diagnosed; if the last position is on the main line, the obtained fault diagnosis result is that both the automatic train protection unit and the monitoring board of the train to be diagnosed have failed.

[0014] The present invention also provides a train fault diagnosis device, including: A decision tree fault diagnosis module, configured to use the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface to perform step-by-step train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and running on the processor, where when the processor executes the computer program, it implements the train fault diagnosis method as described in any one of the above.

[0016] The train fault diagnosis method, device, and electronic device provided by the present invention, by pre-constructing a fault diagnosis decision tree and combining different data of the train to be diagnosed actually obtained from different IMS interfaces and TIAS interfaces to perform step-by-step fault diagnosis analysis based on the fault diagnosis decision tree, can quickly and accurately diagnose the fault conditions of train components indirectly or directly connected to the IMS interface and TIAS interface, which helps assist maintenance personnel in quickly solving train fault problems, greatly reduces the time for train fault troubleshooting, improves the efficiency, accuracy, and reliability of train fault detection, and can provide strong technical support for the reliable operation of trains. Description of the Drawings

[0017] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the attached drawings required for the description of the embodiments or the prior art. Obviously, the attached drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other attached drawings can also be obtained based on these attached drawings.

[0018] Figure 1 It is a schematic flow chart of the train fault diagnosis method provided by the present invention.

[0019] Figure 2 It is a schematic data flow diagram of the intelligent operation and maintenance interface provided by the present invention.

[0020] Figure 3 It is a schematic data flow diagram of the train information service interface provided by the present invention.

[0021] Figure 4 It is an example diagram of the fault diagnosis decision tree provided by the present invention.

[0022] Figure 5 It is a schematic structural diagram of the train fault diagnosis device provided by the present invention.

[0023] Figure 6 It is a schematic structural diagram of the electronic device provided by the present invention. Specific embodiments

[0024] To make the objectives, technical solutions and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the attached drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts fall within the scope of protection of the present invention.

[0025] It should be noted that in the description of the present invention, the term "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. For those of ordinary skill in the art, the specific meaning of the above terms in the present invention can be understood according to specific circumstances.

[0026] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0027] The following will describe the train fault diagnosis method, device, and electronic device provided by the present invention in conjunction with Figures 1-6 Describe the train fault diagnosis method, device, and electronic device provided by the present invention.

[0028] Figure 1 is a schematic flowchart of the train fault diagnosis method provided by the present invention. As Figure 1 shown, the train fault diagnosis method includes but is not limited to step 101.

[0029] It should be noted that the execution subject of the train fault diagnosis method provided by the present invention can be a server or a computer device, such as a mobile phone, a tablet computer, a notebook computer, a handheld computer, an in-vehicle electronic device, a wearable device, an Ultra-Mobile Personal Computer (UMPC), a netbook, or a Personal Digital Assistant (PDA), etc.

[0030] Step 101: Use the first interface data obtained by the train to be diagnosed from the Intelligent Maintenance System (IMS) interface and the second interface data obtained from the Train Information and Announcement System (TIAS) interface to perform hierarchical train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree, and obtain the fault diagnosis result of the train to be diagnosed.

[0031] Figure 2 is a schematic data flow diagram of the intelligent maintenance system interface provided by the present invention. As Figure 2 shown, the IMS interface is connected to the Train Access Unit (TAU), the TAU unit is connected to the monitoring board (also called the recording board), the monitoring board is connected to the Automatic Train Protection (ATP) unit, and the arrow indicates the flow direction of the data flow.

[0032] The ATP unit is used to generate train operation control data and transmit the train operation control data to the IMS interface through the monitoring board and the TAU unit.

[0033] The monitoring board is used to preliminarily process the data from the ATP unit, and will generate alarm information when the ATP unit fails, and transmit the alarm information to the IMS interface through the TAU unit.

[0034] The TAU unit, as the transmission medium between the train to be diagnosed and the IMS interface, is used to send the data processed by the monitoring board from the monitoring board to the IMS interface.

[0035] The IMS interface is connected to the intelligent operation and maintenance system, and is used to receive the data from the TAU unit, so that the intelligent operation and maintenance system can monitor the train status information (including but not limited to information such as whether the train is online), and perform further fault diagnosis and analysis on the train status information.

[0036] The first interface data is also the interface data generated or processed by the ATP unit, the monitoring board, and the TAU unit, and directly or indirectly transmitted to the IMS interface.

[0037] Figure 3 It is a schematic diagram of the data flow of the train information service interface provided by the present invention, as Figure 3 shown, the TIAS interface is respectively connected to the ATP unit and the Interlocking Control (CI) unit, the ATP unit is connected to the TAU unit, and the arrow indicates the flow direction of the data flow.

[0038] At this time, the TAU unit is used to directly send the data generated by the ATP unit to the TIAS interface without being processed by the monitoring board.

[0039] The CI unit is used to generate train position data and transmit the train position data to the TIAS interface.

[0040] The TIAS interface is used to receive the data from the TAU unit and the CI unit, and can obtain train-related information including but not limited to train position, whether it is a communication vehicle, and whether it is a communication-based train control (CBTC) train through parsing.

[0041] The second interface data is also the interface data generated or processed by the ATP unit, the TAU unit, and the CI unit, and directly or indirectly transmitted to the TIAS interface.

[0042] The fault diagnosis decision tree is a decision tree constructed using the fault diagnosis logic for judging the train components directly or indirectly connected to the IMS interface and the TIAS interface, which is determined based on expert knowledge and the interface data that can be received by the IMS interface and the TIAS interface.

[0043] Specifically, based on expert knowledge, interface data that can theoretically be received from the IMS interface and the TIAS interface, a fault diagnosis logic is constructed, and a fault diagnosis decision tree is pre-constructed based on the fault diagnosis logic. When actually performing fault diagnosis on the train, the first interface data actually obtained from the IMS interface and the second interface data actually obtained from the TIAS interface are received and utilized, and hierarchical fault diagnosis analysis is performed according to the fault diagnosis decision tree to obtain the fault diagnosis results of each component of the train directly or indirectly connected to the IMS interface and the TIAS interface.

[0044] Optionally, after obtaining the fault diagnosis results of the train to be diagnosed, it further includes: based on the fault diagnosis results, determining and outputting response handling information to enable maintenance personnel to quickly repair and solve train fault problems.

[0045] For example, the handling information includes, but is not limited to, at least one of the information such as prompting maintenance personnel to check the train ATP, monitoring board, or replacing the corresponding board.

[0046] The train fault diagnosis method provided by the present invention pre-constructs a fault diagnosis decision tree, combines different data of the train to be diagnosed actually obtained from different IMS interfaces and TIAS interfaces, and performs hierarchical fault diagnosis analysis based on the fault diagnosis decision tree, which can quickly and accurately diagnose the fault conditions of the train components indirectly or directly connected to the IMS interface and the TIAS interface, helps assist maintenance personnel in quickly solving train fault problems, greatly reduces the time for train fault troubleshooting, improves the efficiency, accuracy, and reliability of train fault detection, and can provide strong technical support for the reliable operation of the train.

[0047] Based on the above embodiments, as an optional embodiment, the fault diagnosis decision tree is pre-constructed based on the following method: According to the theoretically acquirable interface data of the intelligent operation and maintenance interface and the train information service interface, a status variable table is defined; Define a fault status table for each component of the train; Based on the operation status variables corresponding to each train operation status in the status variable table and the fault status variables corresponding to each fault status of each component of the train in the fault status table, a fault diagnosis truth table is constructed; Based on the fault diagnosis truth table, a fault diagnosis decision tree is constructed.

[0048] Among them, the status variable table includes the operation status variables corresponding to several train operation statuses and their value ranges; the fault status table includes the fault status variables corresponding to several fault statuses of each component of the train and their values.

[0049] Specifically, when pre - constructing a fault diagnosis decision tree, based on the expert knowledge in the field of train operation data analysis, analyze the theoretically obtainable interface data of the IMS interface and the TIAS interface (i.e., all the interface data that can be obtained theoretically), determine several train operation states that can be determined by the first interface data obtained by analyzing the IMS interface and the second interface data obtained by the TIAS interface, and then determine the operation state variables corresponding to several train operation states and the value ranges of each operation state variable. Define a state variable table according to each operation state variable and its value range.

[0050] Based on the expert knowledge in the field of train fault diagnosis, obtain several fault states of each train component that can be determined by analyzing the IMS interface data and the TIAS interface data, and then determine the fault state variables corresponding to several fault states and the values of each fault state variable. Define a fault state table for each train component according to each fault state variable and its value.

[0051] Furthermore, based on the operation state variables corresponding to each train operation state in the state variable table and the fault state variables corresponding to each fault state of each train component in the fault state table, analyze the diagnosable fault states in different cases where the operation state variables are different and the actual values of the operation state variables are different, and obtain a fault diagnosis truth table composed of multiple operation state records. Each operation state record includes the specific values of the variable combination composed of the operation state variables of several train operation states and the specific values of the corresponding fault state variables.

[0052] Finally, according to the fault diagnosis truth table, use each operation state variable in the state variable table as the root or internal node of the fault diagnosis decision tree, and use each fault state variable in the fault state table as the leaf of the fault diagnosis decision tree, so as to construct a fault diagnosis decision tree to be able to diagnose the relevant faults of each train component through a series of yes / no questions.

[0053] Table 1 is the state variable table provided by the present invention. As shown in Table 1, by analyzing the theoretically obtainable interface data of the IMS interface and the TIAS interface, 8 train operation states can be determined. The corresponding 8 operation state variables include "whether the train is online", "whether the TAU unit is faulty", "whether the ATP unit is faulty", "whether the train is a communication vehicle", "whether the train normally receives TIAS interface data", "whether the train is a CBTC vehicle", "whether the train is on the main line", and "whether the last position of the train is on the main line". The value ranges of the 8 operation state variables all include "0 (corresponding to no)" and "1 (corresponding to yes)". According to the 8 operation state variables and their corresponding value ranges, the state variable table as shown in Table 1 is obtained.

[0054] Table 1 State Variable Table

[0055] Table 2 is the fault status table provided by the present invention. As shown in Table 2, by analyzing the theories of the IMS interface and the TIAS interface, interface data, train operation status, etc. can be obtained, and 6 fault statuses can be determined. The corresponding 6 fault status variables successively include "no fault", "TAU unit fault", "ATP unit fault", "monitoring board fault", "both ATP and monitoring board fault", and "unable to judge", and the values of the 6 fault status variables correspond to "1", "2", "3", "4", "5", and "6" in sequence. According to the 6 fault status variables and their corresponding values, the fault status table as described in Table 2 is obtained.

[0056] Table 2 Fault Status Table

[0057] Table 3 is the fault diagnosis truth table provided by the present invention. As shown in Table 3, the fault diagnosis truth table includes 7 operation status records. Each operation status record includes a variable combination composed of specific values of operation status variables of several train operation statuses based on Table 1, and the corresponding fault status value (i.e., the specific value of the fault status variable) based on Table 2.

[0058] Table 3 Fault Diagnosis Truth Table

[0059] Figure 4 is an example diagram of the fault diagnosis decision tree provided by the present invention. As Figure 4 described, after constructing the fault diagnosis truth table in Table 3 to analyze and judge the fault status of each train component, a fault diagnosis decision tree as shown in Figure 4 can be constructed based on Table 3 to diagnose train faults through a series of yes / no questions.

[0060] The train fault diagnosis method provided by the present invention analyzes the interface data that can be theoretically obtained from the IMS interface and the TIAS interface, constructs a state variable table and a fault status table according to the train operation status and possible fault statuses, and constructs a fault diagnosis truth table based on the state variable table and the fault status table, and then constructs a fault diagnosis decision tree more scientifically and reasonably, which helps to quickly and accurately identify the fault conditions of train components during actual fault diagnosis and helps auxiliary maintenance personnel quickly solve train fault problems.

[0061] Based on the above embodiments, as an alternative embodiment, the train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree is performed step by step on the first interface data obtained from the intelligent operation and maintenance interface of the train to be diagnosed and the second interface data obtained from the train information service interface, and the fault diagnosis result of the train to be diagnosed is obtained, including: Based on the first interface data, determine whether the train to be diagnosed is online; If the train to be diagnosed is online, obtain the fault diagnosis result that there is no fault in the train to be diagnosed.

[0062] Specifically, in combination with Figure 4 As shown, when performing train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step, first obtain relevant data from the first interface data acquired from the IMS interface to determine whether the train to be diagnosed is online. If the train to be diagnosed is online, that is, the train to be diagnosed is normal, it means that the train to be diagnosed can communicate normally through the IMS interface, and the fault diagnosis result is obtained as that there is no fault in the train to be diagnosed.

[0063] The train fault diagnosis method provided by the present invention, when performing train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step, first determines whether the train is online according to the IMS interface data, and determines that there is no fault in the train when the train is online, and can quickly and accurately make a judgment on whether the train is faulty.

[0064] Based on the above embodiments, as an alternative embodiment, the method of using the first interface data acquired by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data acquired from the train information service interface to perform train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If the train to be diagnosed is not online, then based on the TAU unit status data in the first interface data, determine whether the TAU unit has a fault; If the TAU unit has a fault, obtain the fault diagnosis result that the TAU unit of the train to be diagnosed is faulty.

[0065] Specifically, in combination with Figure 4 As shown, if the train to be diagnosed is not online, it means that there is a fault in the components of the train to be diagnosed, but the train component with the specific fault cannot be determined yet. At this time, according to the TAU unit status data in the first interface data acquired from the IMS interface, determine whether the TAU unit has a fault. If the TAU unit status data shows that the TAU unit has a fault, and at the same time represents that the train to be diagnosed is not online and cannot communicate normally, then determine the fault diagnosis result as that the TAU unit of the train to be diagnosed is faulty.

[0066] The train fault diagnosis method provided by the present invention can quickly and accurately diagnose the situation where the train cannot communicate normally due to a TAU unit fault by, when performing train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step, after determining that the train is offline according to the IMS interface data, determining whether there is a fault in the TAU unit of the train based on the TAU unit status data in the IMS interface data.

[0067] Based on the above embodiment, as an alternative embodiment, the method of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface to perform train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If there is no fault in the train access unit, it is determined whether the first interface data includes the alarm information of the ATP unit feedback by the monitoring board; If the alarm information is included, the fault diagnosis result is that the ATP unit of the train to be diagnosed is faulty.

[0068] Specifically, as shown in Figure 4 If it is determined that there is no fault in the TAU unit according to the TAU unit status data in the first interface data obtained from the IMS interface, it is further determined whether the first interface data includes the alarm information of the ATP unit feedback by the monitoring board. Because when the ATP unit is faulty but the monitoring board is operating properly, the monitoring board can transmit the alarm information of the ATP unit fault to the IMS interface through the TAU unit that is also operating properly. If the first interface data includes the alarm data, the fault diagnosis result is that the ATP unit of the train to be diagnosed is faulty.

[0069] The train fault diagnosis method provided by the present invention can quickly and accurately diagnose the situation where the ATP unit of the train is faulty while other train components are operating properly by, when performing train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step, in the case of successively determining that the train is offline and the TAU unit is not faulty, using the successive connection relationship among the ATP unit, the monitoring board, the TAU unit, and the IMS interface, and determining that the ATP unit of the train is faulty when receiving the alarm information of the ATP unit fault feedback by the monitoring board from the IMS interface.

[0070] Based on the above embodiment, as an alternative embodiment, the method of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface to perform train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If the alarm information is not included, based on the second interface data, determine whether the train to be diagnosed is a communication vehicle; If the train to be diagnosed is a communication vehicle, obtain the fault diagnosis result that the monitoring board of the train to be diagnosed is faulty.

[0071] Specifically, in combination with Figure 4 As shown, after successively determining that the train is offline and the TAU unit has no fault, if the first interface data does not include the alarm information of the ATP unit fed back by the monitoring board, then based on the relevant data for determining whether the train is a communication vehicle in the second interface data obtained from the TIAS interface (such as the offline train status table tias_train in the second interface data), determine whether the train to be diagnosed is a communication vehicle. If the train to be diagnosed is a communication vehicle, and at this time the train is offline, the TAU unit and the ATP unit have no fault, then the fault diagnosis result can be determined to be the fault of the monitoring board of the train to be diagnosed.

[0072] The train fault diagnosis method provided by the present invention, when performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree step by step, when successively determining based on the IMS interface data that the train is offline, the TAU unit has no fault but the train has a fault, then based on the TIAS interface data, determine whether the train is a communication vehicle, and can quickly and accurately diagnose the situation where the monitoring board is faulty but other train components are operating well.

[0073] Based on the above embodiment, as an alternative embodiment, the use of the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface to perform train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If the train to be diagnosed is not a communication vehicle, then determine whether the reception of the second interface data is normal; If the reception of the second interface data is normal, and based on the second interface data, it is determined that the train to be diagnosed is on the main line and the train to be diagnosed is not a communication control train, obtain the fault diagnosis result that both the automatic train protection unit and the monitoring board of the train to be diagnosed are faulty.

[0074] Specifically, in combination with Figure 4As shown, after successively determining through IMS interface data that the train is not online, the TAU unit has no fault and no alarm information from the ATP unit can be received, and through TIAS interface data that the train to be diagnosed is not a communication vehicle, at this time, it is determined whether the reception of the second interface data received through the TIAS interface is normal. If the reception is normal, and based on the train position data generated and transmitted by the CI unit received from the TIAS interface, it is determined that the train to be diagnosed is on the main line and is not a CBTC vehicle, then a fault diagnosis result that both the ATP unit and the monitoring board of the train to be diagnosed have failed is obtained.

[0075] The train fault diagnosis method provided by the present invention, when successively performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree, when successively determining through IMS interface data that the train is not online and the TAU unit has no fault but the train has a fault, and then based on TIAS interface data, it is determined that the train is not a communication vehicle, not a CBTC vehicle, is on the main line and the reception of the second interface data is normal, so as to determine that both the ATP unit and the monitoring board have failed, can quickly and accurately diagnose the situation where both the ATP unit and the monitoring board have failed.

[0076] Based on the above embodiment, as an optional embodiment, the step of successively performing train fault diagnosis analysis based on a pre-constructed fault diagnosis decision tree by using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface to obtain the fault diagnosis result of the train to be diagnosed further includes: If the reception of the second interface data is abnormal, based on the last received second interface data, obtain the last position of the train to be diagnosed; If the last position is on the main line, obtain the fault diagnosis result that both the automatic train protection unit and the monitoring board of the train to be diagnosed have failed.

[0077] Specifically, as shown in Figure 4 If the reception of the second interface data of the TIAS interface is abnormal, then based on the train position data generated and transmitted by the CI unit in the last received second interface data, obtain the last position of the train to be diagnosed. If the last position of the train to be diagnosed is on the main line, the situation where the train to be diagnosed has returned to the depot normally can be excluded, and then the fault diagnosis result is determined to be that both the ATP unit and the monitoring board of the train to be diagnosed have failed.

[0078] The train fault diagnosis method provided by the present invention, when performing train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step, in the case of successively determining that the train is not online and there is a fault in the train but the TAU unit has no fault based on the IMS interface data, and then based on the TIAS interface data, determining that the train is not a communication vehicle, not a CBTC vehicle and the reception of the second interface data is abnormal, and excluding the situation that the train to be diagnosed has returned to the depot normally by judging whether the last position is on the main line, and thus can quickly and accurately diagnose the situation where both the ATP unit and the monitoring board have failed.

[0079] Generally speaking, the train fault diagnosis method provided by the present invention analyzes the functions and fault modes of components such as the train ATP unit, TAU unit, and monitoring board, combines expert knowledge and fault diagnosis logic to pre-construct a fault diagnosis decision tree, and in the actual process of performing step-by-step diagnosis of train faults based on the decision tree, combines data streams of the IMS interface and TIAS interface from different sources to quickly and accurately identify different board card fault points such as ATP faults, TAU faults, and monitoring board faults, so as to quickly give corresponding disposal suggestions according to the fault diagnosis results to assist maintenance personnel in quickly solving problems, improve the speed and accuracy of fault detection, and can provide strong technical support for the efficient, safe, reliable, and large-scale operation of the train system.

[0080] Figure 5 is a schematic structural diagram of the train fault diagnosis device provided by the present invention, as Figure 5 shown, the train fault diagnosis device includes but is not limited to a decision tree fault diagnosis module 501.

[0081] The decision tree fault diagnosis module 501 is used to perform train fault diagnosis and analysis based on a pre-constructed fault diagnosis decision tree step by step by using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, and obtain the fault diagnosis result of the train to be diagnosed.

[0082] It should be noted that the train fault diagnosis device provided by the present invention can execute the train fault diagnosis method described in any of the above embodiments during specific operation, and this embodiment will not be elaborated here.

[0083] The train fault diagnosis device provided by the present invention pre-constructs a fault diagnosis decision tree and combines different data of the train to be diagnosed actually obtained from different IMS interfaces and TIAS interfaces to perform step-by-step fault diagnosis analysis based on the fault diagnosis decision tree, and can quickly and accurately diagnose the fault conditions of train components indirectly or directly connected to the IMS interface and TIAS interface, which helps auxiliary maintenance personnel quickly solve train fault problems, greatly reduces the time for train fault troubleshooting, improves the efficiency, accuracy and reliability of train fault detection, and can provide strong technical support for the reliable operation of the train.

[0084] Figure 6 is a schematic structural diagram of the electronic device provided by the present invention, as Figure 6 shown, the electronic device may include: a processor (Processor) 610, a communication interface (Communications Interface) 620, a memory (Memory) 630, and a communication bus 640. Among them, the processor 610, the communication interface 620, and the memory 630 complete mutual communication through the communication bus 640. The processor 610 can call the logical instructions in the memory 630 to execute the train fault diagnosis method provided by any of the above embodiments. The train fault diagnosis method includes but is not limited to the following steps: using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing step-by-step train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree to obtain the fault diagnosis result of the train to be diagnosed.

[0085] In addition, when the logical instructions in the above-mentioned memory 630 are implemented in the form of software function units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk, or an optical disc that can store program codes.

[0086] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0087] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A train fault diagnosis method, characterized in that Including: Using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed.

2. The train fault diagnosis method according to claim 1, characterized in that, The fault diagnosis decision tree is pre-constructed based on the following method: Defining a status variable table according to the theoretically obtainable interface data of the intelligent operation and maintenance interface and the train information service interface; Defining a fault status table for each component of the train; Constructing a fault diagnosis truth table based on the operation status variables corresponding to each train operation status in the status variable table and the fault status variables corresponding to each fault status of each component of the train in the fault status table; Constructing a fault diagnosis decision tree based on the fault diagnosis truth table.

3. The train fault diagnosis method according to any one of claims 1-2, characterized in that The process of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed includes: Based on the first interface data, determining whether the train to be diagnosed is online; If the train to be diagnosed is online, obtaining the fault diagnosis result that the train to be diagnosed has no fault.

4. The train fault diagnosis method according to claim 3, wherein The process of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If the train to be diagnosed is not online, then based on the train access unit status data in the first interface data, determining whether there is a fault in the train access unit; If there is a fault in the train access unit, obtaining the fault diagnosis result that the train access unit of the train to be diagnosed is faulty.

5. The train fault diagnosis method according to claim 4, wherein, The process of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If there is no fault in the train access unit, then determining whether the first interface data includes the alarm information of the automatic train protection unit fed back by the monitoring board; If the alarm information is included, obtaining the fault diagnosis result that the automatic train protection unit of the train to be diagnosed is faulty.

6. The train fault diagnosis method according to claim 5, wherein The process of using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed further includes: If the alarm information is not included, then based on the second interface data, determining whether the train to be diagnosed is a communication vehicle; If the train to be diagnosed is a communication vehicle, obtaining the fault diagnosis result that the monitoring board of the train to be diagnosed is faulty.

7. The train fault diagnosis method according to claim 6, wherein Using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed, further includes: If the train to be diagnosed is not a communication vehicle, determining whether the reception of the second interface data is normal; If the reception of the second interface data is normal, and based on the second interface data, it is determined that the train to be diagnosed is on the main line, and the train to be diagnosed is not a communication control train, obtaining that the fault diagnosis result is that both the automatic train protection unit and the monitoring board of the train to be diagnosed have failed.

8. The train fault diagnosis method according to claim 7, characterized in that Using the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, performing train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed, further includes: If the reception of the second interface data is abnormal, based on the last received second interface data, obtaining the last position of the train to be diagnosed; If the last position is on the main line, obtaining that the fault diagnosis result is that both the automatic train protection unit and the monitoring board of the train to be diagnosed have failed.

9. A train fault diagnosis device, characterized in that, Includes: A decision tree fault diagnosis module, configured to use the first interface data obtained by the train to be diagnosed from the intelligent operation and maintenance interface and the second interface data obtained from the train information service interface, and perform train fault diagnosis analysis based on the pre-constructed fault diagnosis decision tree step by step to obtain the fault diagnosis result of the train to be diagnosed.

10. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the train fault diagnosis method according to any one of claims 1 to 8.

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