CN119603131A - A MVB communication fault diagnosis system based on MVB online monitoring - Google Patents
A MVB communication fault diagnosis system based on MVB online monitoring Download PDFInfo
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- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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- H04L41/06—Management of faults, events, alarms or notifications
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- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
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Abstract
The invention discloses an MVB communication fault diagnosis system based on MVB on-line monitoring, which relates to the technical field of communication network fault diagnosis, wherein the MVB communication fault diagnosis system comprises an isolated partition module, a data acquisition module, a relationship analysis module, a fault diagnosis analysis module, a fault positioning module, a fault alarm recording module and a fault processing suggestion module, wherein the modules are connected by electric signals; and the isolation partition module is used for dividing the MVB network into a plurality of logic areas. The invention monitors the data flow, the signal quality and the communication state on the bus of the vehicle, discovers and locates the communication fault in real time, feeds back the communication state in real time, immediately gives an alarm once the abnormality is detected, and automatically starts the fault diagnosis flow, thereby effectively preventing the safety accident caused by the communication fault, ensuring the accuracy of fault diagnosis, reducing false alarm and missing alarm, providing reliable fault information for maintenance personnel and being convenient for taking measures rapidly.
Description
Technical Field
The invention relates to the technical field of communication network fault diagnosis, in particular to an MVB communication fault diagnosis system based on MVB on-line monitoring.
Background
The Multifunctional Vehicle Bus (MVB) bears the data interaction task among devices in the vehicle, is an important component of a train communication network, and comprises two stages of buses, namely a stranded Wire Train Bus (WTB) and a Multifunctional Vehicle Bus (MVB), along with the development of the rail transit industry, more and more train network systems adopt a train communication network standard, the MVB network is used as one of train communication network standard media, the market is greatly developed, and various devices and systems perform data transmission and control through the MVB bus due to the fact that control systems and devices in the train are more and more complex, so that the health condition of the MVB communication system must be monitored and diagnosed in real time in order to ensure the safe, stable and efficient operation of the train.
In the prior art, as the MVB communication system relates to a plurality of devices, nodes and connecting links, when a plurality of subsystems have faults at the same time, the specific fault source is difficult to accurately locate, and the situation of misjudgment or missed judgment is easy to occur.
Disclosure of Invention
The invention aims to provide an MVB communication fault diagnosis system based on MVB on-line monitoring so as to solve the problems in the background technology.
In order to solve the technical problems, the invention adopts the following technical scheme:
An MVB communication fault diagnosis system based on MVB on-line monitoring comprises an isolated partition module, a data acquisition module, a relation analysis module, a fault diagnosis analysis module, a fault positioning module, a fault alarm recording module and a fault processing suggestion module, wherein the modules are connected by electric signals;
the isolation partition module is used for dividing the MVB network into a plurality of logic areas so as to isolate each subsystem, so that the running state of each subsystem is analyzed independently, the mutual interference among the subsystems is reduced, and the accuracy of fault positioning is improved;
The data acquisition module is used for acquiring node data from each subsystem in the MVB network, including communication signals and state information of each subsystem, preprocessing the acquired node data, ensuring the integrity and instantaneity of the data, and providing a reliable data basis for subsequent fault analysis;
the relationship analysis module is used for analyzing the interrelationship among different subsystems, including a communication protocol, a data flow direction and a dependency relationship, and constructing a relationship map among the subsystems;
the fault diagnosis analysis module is used for analyzing an abnormal mode in the node data based on the preprocessed node data and the relation patterns among all subsystems, judging whether a fault exists or not and giving out a fault type;
The fault alarm recording module triggers an alarm mechanism after determining a fault node, sends out a fault alarm to an operator, records fault information including fault type, occurrence time, fault node and the like, and provides basis for subsequent fault analysis and processing;
The fault processing suggestion module provides fault processing suggestions according to the fault positioning result and the fault type, wherein the fault processing suggestions comprise fault repairing steps, required tools or spare parts, preventive measures and the like, and the specific processing suggestions are provided to help operators to quickly solve the faults and restore the normal operation of the system.
The technical scheme of the invention is further improved in that the isolated partition module specifically comprises:
Analyzing the whole topological structure of the MVB network according to the functional requirements of the train, subsystem distribution and fault isolation requirements, and identifying all equipment, nodes and connection relations thereof;
Presetting configuration files or user input, defining boundaries and parameters of each subsystem, dividing the MVB network into a plurality of logic areas according to network topology analysis results and combining actual application requirements, wherein each logic area comprises a group of related devices and nodes;
the sequestered partition module receives data frames from the MVB network, identifies their destination addresses and types, and determines forwarding processing decisions based on the destination addresses and types of the data frames.
The technical scheme of the invention is further improved in that the specific process for determining the forwarding processing decision comprises the following steps:
The partition module analyzes the data frame from the MVB network, and extracts a data frame structure comprising a target address, a source address, a frame type (a control frame, a data frame and the like) and a priority, wherein the target address points to a specific subsystem, equipment or a functional module;
Matching the target address with a predefined logic area mapping table, determining whether the data frame belongs to a specific logic area, outputting a forwarding decision according to a matching result and a preset rule, and determining whether the data frame is forwarded to a target subsystem or isolated;
If the target address and the type of the data frame accord with a preset forwarding rule, forwarding the data frame to a corresponding target subsystem or a next logic area by the isolation partition module;
If the target address or type of the data frame does not accord with the preset forwarding rule or the abnormal condition that the data frame is damaged and the target address is invalid exists, executing the forwarding processing decision of the data frame isolation, preventing the data frame isolation from entering other subsystems in the current logic area, recording isolation events, reducing the mutual interference among the subsystems and improving the stability and the safety of the system.
The technical scheme of the invention is further improved in that the data acquisition module specifically comprises:
The data acquisition module is initialized after being electrified, parameters of communication rate and node address are configured, and connection parameters of the data acquisition module and the MVB network are set according to a preset configuration file or user input, so that the module can be ensured to be correctly accessed into the network and identify each subsystem;
Starting an independent data acquisition task for each logic area, and identifying each node in the MVB network by a data acquisition module, wherein the data acquisition module comprises communication equipment and sensors of each subsystem, and periodically collecting node data of each subsystem, including communication signals and state information;
Temporarily storing the collected original node data in a buffer area for subsequent processing, and further preprocessing the node data, including data integrity checking, denoising, filtering and standardization operation, so as to improve the data quality;
A data warehouse is constructed and the preprocessed node data is stored in the data warehouse for subsequent analysis and processing.
The technical scheme of the invention is further improved in that the relation analysis module specifically comprises:
Initializing parameters and settings of a relation analysis module according to configuration files of the system or user input, acquiring node data of each subsystem from a data acquisition module, and importing basic information comprising subsystem names, function descriptions, interface definitions, node addresses and communication protocols;
analyzing communication protocols used among all subsystems, analyzing formats, message structures and verification modes of the communication protocols, defining a data exchange process, and determining a starting point subsystem, an intermediate link and an end point subsystem by analyzing communication protocol and data flow information among all subsystems and tracking data flow directions;
identifying direct dependency relationships among subsystems, and deducing indirect dependency relationships among the subsystems by analyzing data flow direction and communication protocol;
Generating a relation map according to the communication protocol, the data flow direction and the dependency relationship obtained by analysis, displaying the position, the mutual relationship and the data flow direction of each subsystem in the map, and simultaneously optimizing the generated relation map, including adjusting layout, adding notes, highlighting key nodes and the like, so as to ensure that the map is clear and easy to understand, facilitate the understanding and analysis of a user, storing the final relation map in a database, and updating periodically to reflect the change of the system.
The technical scheme of the invention is further improved in that the fault diagnosis and analysis module specifically comprises:
the preprocessed node data is imported into a fault diagnosis analysis module, and the connection relation and the communication path among the nodes are defined by utilizing the relation map among the subsystems;
According to the range and the path of the fault influence, positioning related nodes and connecting lines in a relation map, analyzing the flow path of data among the nodes, and determining a fault propagation path;
Extracting characteristics of communication signals and state information from the node data, wherein the characteristics of the communication signals are signal amplitude, signal phase and signal-to-noise ratio, and the characteristics of the state information are temperature, current, voltage and response time;
Based on the fault management requirement of the MVB network, presetting an abnormal threshold of the communication signal characteristic and the state information characteristic by combining historical data so as to distinguish the abnormal characteristic in the communication signal characteristic and the state information characteristic, wherein the abnormal communication signal characteristic is characterized by abnormal signal amplitude, signal phase distortion and signal noise ratio reduction, and the abnormal state information characteristic is characterized by abnormal temperature, current fluctuation, voltage fluctuation and abnormal response time;
comparing each feature with an abnormal threshold value according to the collected real-time communication signals and state information data to obtain an abnormal identification value of each feature;
the abnormal recognition value of the state information characteristic obtained by synthesis, the state abnormal recognition index is calculated, and the abnormal trend of the state information is analyzed;
And calculating a fault recognition coefficient by combining the signal abnormal recognition index and the state abnormal recognition index, analyzing an abnormal mode in the node data, and judging a specific fault type according to the abnormal mode recognition result and the relation map, wherein the fault type comprises a hardware fault, a software fault and a communication fault.
The technical scheme of the invention is further improved in that the calculation formula of the signal abnormality identification index is as follows:
;
In the formula, As an index for identifying the signal abnormality,For the current signal amplitude value,Is an abnormal threshold value of the signal amplitude,As the value of the phase of the current signal,Is an abnormal threshold value of the phase of the signal,AndConstants of signal amplitude and signal phase adjustment sensitivity, respectively, take positive values for controlling the steepness of the exponential function,For the current signal-to-noise ratio value,As an outlier threshold for the signal-to-noise ratio,The value range of (2) is between 0 and 1;
the calculation formula of the state anomaly identification index is as follows:
;
In the formula, As the state abnormality identification index,As a value of the current temperature of the water,Is an abnormal threshold value of the temperature,Is the maximum allowable value of the temperature and,As the current value of the current is present,Is an abnormal threshold value of the current,Taking positive value for constant of current adjustment sensitivity, for controlling steepness of exponential function,As the value of the current voltage is the value of the current voltage,Is an abnormal threshold value of the voltage,Is the maximum allowable value of the voltage,As a value of the current response time,In order to respond to the abnormal threshold of time,In order to respond to the constant of the time adjustment sensitivity, take a positive value for controlling the steepness of the exponential function,The value range of (2) is between 0 and 1;
The calculation formula of the fault identification coefficient is as follows:
;
In the formula, As a result of the failure recognition factor,As an index for identifying the signal abnormality,As the state abnormality identification index,The constant of the sensitivity is adjusted for the state abnormality identification index, a positive value is taken for controlling the steepness of the exponential function,And has a value ranging from 0 to 1, when all features are within normal ranges,Close to 0.
The technical scheme of the invention is further improved in that the judging process of the fault type comprises the following steps:
setting a distinguishing threshold K of the fault recognition coefficient according to the historical data so as to distinguish normal conditions from abnormal conditions, and when the value of the fault recognition coefficient is smaller than K, indicating that the abnormal conditions exist;
according to the size of the fault identification coefficient and the distinguishing threshold value, comparing to identify the node with higher abnormality degree, further carrying out deep analysis on the characteristics of the identified abnormal node, and judging whether an abnormal mode exists;
for the abnormal mode, further analyzing the signal abnormal identification index and the state abnormal identification index to determine specific abnormal characteristics, finding the position of an abnormal node in the relation map, and marking the position;
Based on the connection relation between the abnormal node and other nodes, analyzing the propagation path and the influence range of the abnormal mode in the MVB network, and judging the specific fault type according to the abnormal mode, the fault propagation path and the node characteristics.
The technical scheme of the invention is further improved in that the fault alarm recording module specifically comprises:
determining a node with a fault through means of fault identification coefficient analysis, abnormal mode detection and relation map analysis, determining the specific position of the fault, and providing an accurate target for subsequent alarm and processing;
after the fault node is determined, the fault alarm recording module automatically triggers an alarm mechanism which comprises a plurality of modes including sound and light alarm, short message notification and mail reminding, and further sends an alarm containing fault information to an operator through a preset alarm mode, so that the operator can quickly know the fault condition and make a correct coping decision;
And when the fault alarms, fault information including fault type, occurrence time, fault node and detailed information of fault description is automatically recorded, a detailed fault report is generated according to the recorded fault information and is used for subsequent fault analysis and processing, after the fault processing is finished, an operator feeds back a processing result to a fault alarm recording module, and the fault alarm recording module automatically updates the fault state and records the processing result and the processing time.
The technical scheme of the invention is further improved in that the fault processing suggestion module specifically comprises:
Matching corresponding fault handling suggestions from a fault handling knowledge base containing various known fault handling suggestions according to the determined fault type;
Generating specific fault handling suggestions including fault repair steps, required tools or spare parts and precautions according to the matched relevant fault entries, and providing the generated handling suggestions to an operator, wherein the steps required for repairing the fault including necessary operation sequences and precautions are detailed, specific tools, spare parts or test equipment required for completing the repair work are pointed out, and suggestions for preventing similar faults from happening again are provided;
the fault processing progress is tracked, so that an operator is allowed to record the completion condition of each step, any problems encountered and additional measures taken, and after the operator processes the fault, the operator feeds back the processing result and newly discovered information to update the fault processing knowledge base.
By adopting the technical scheme, compared with the prior art, the invention has the following technical progress:
1. the invention provides an MVB communication fault diagnosis system based on MVB on-line monitoring, which is used for immediately finding and positioning a communication fault by monitoring data flow, signal quality and communication state on a vehicle bus, feeding back the communication state in real time, immediately giving out an alarm once abnormality is detected, and automatically starting a fault diagnosis process, thereby effectively preventing safety accidents caused by the communication fault, ensuring the accuracy of fault diagnosis, reducing false alarm and missing report, providing reliable fault information for maintenance personnel, and facilitating rapid taking of measures.
2. The invention provides an MVB communication fault diagnosis system based on MVB on-line monitoring, which accurately locates fault nodes and the influence range thereof through relation map analysis, greatly improves the accuracy and efficiency of fault diagnosis, reduces the possibility of false alarm and missing alarm, and can accurately judge specific fault types and positions through combining fault identification coefficients, abnormal mode detection and relation map analysis, thereby providing a definite target for subsequent processing.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a schematic diagram of the functional modules of the system of the present invention;
FIG. 2 is a schematic diagram of the workflow of the fault diagnosis and analysis module of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment 1, as shown in fig. 1, provides an MVB communication fault diagnosis system based on MVB online monitoring, wherein the MVB communication fault diagnosis system comprises an isolated partition module, a data acquisition module, a relationship analysis module, a fault diagnosis analysis module, a fault positioning module, a fault alarm recording module and a fault processing suggestion module, wherein the modules are connected by electric signals;
The isolated partition module is used for dividing the MVB network into a plurality of logic areas, isolating each subsystem so as to independently analyze the running state of each subsystem, help reduce the mutual interference among the subsystems, improve the accuracy of fault location, analyze the overall topology structure of the MVB network according to the functional requirement of a train, subsystem distribution and the requirement of fault isolation, identify all devices, nodes and connection relations thereof, wherein all devices in the network are identified, the system comprises a central control unit, various sensors, an executor, a display, a door controller, a brake system and the like, identify the unique node address of each device on the MVB network, the nodes are master nodes (such as CCU, responsible for managing and coordinating network communication) or slave nodes (such as sensors and executors, respond to the command of the master nodes), determine the physical and logical connection among the devices, all devices are connected through a shared communication line in a bus topology, each device is connected to a central switch through a single line, a preset configuration file or a user input, define the topology of each subsystem and the boundary and parameters, the system is convenient for the system to realize the analysis of the type of the system according to the different physical and the physical and logical nodes, the information of the control frame, the type of the system is different from the target area, the system is realized by the system, the system is a control system is not divided by the relative logic area, the system is a control system, the type of the system is convenient to realize the analysis of the system is a target-independent control area, and the type of the system is different from the target area, and the system is convenient to realize the system, and the system is a system is different in the type of the system has the analysis of the system has different type and has different analysis conditions and different physical conditions, and can be different from the system and can be different. Determining a forwarding processing decision;
Further, the specific process of determining a forwarding processing decision includes:
The isolation partition module analyzes a data frame from the MVB network, extracts a data frame structure comprising a target address, a source address, a frame type (a control frame, a data frame and the like) and a priority, wherein the target address points to a specific subsystem, equipment or a functional module, matches the target address with a predefined logic area mapping table, determines whether the data frame belongs to a specific logic area or not, outputs a forwarding processing decision according to a matching result and a preset rule, determines whether the data frame is forwarded to the target subsystem or performs isolation processing, forwards the data frame to a corresponding target subsystem or the next logic area if the target address and the type of the data frame meet the preset forwarding rule, or performs the forwarding processing decision of the data frame isolation if the target address or the type of the data frame does not meet the preset forwarding rule or the abnormal condition that the data frame is damaged or the target address is invalid, prevents the data frame from entering the current logic area and records isolation events, thereby being beneficial to reducing the mutual interference among the subsystems and improving the stability and the safety of the system;
The data acquisition module is used for acquiring node data from each subsystem in the MVB network, including communication signals and state information of each subsystem, preprocessing the acquired node data, ensuring the integrity and instantaneity of the data, providing a reliable data base for subsequent fault analysis, initializing the data acquisition module after power-on, configuring parameters of communication rate and node address, setting connection parameters of the data acquisition module and the MVB network according to a preset configuration file or user input, ensuring that the module can correctly access the network and identify each subsystem, starting an independent data acquisition task for each logic area, identifying each node in the MVB network, including communication equipment and sensors of each subsystem, periodically collecting the node data of each subsystem, the method comprises the steps of temporarily storing collected original node data in a buffer area for subsequent processing, further preprocessing the node data, including data integrity checking, denoising, filtering and standardization operation to improve data quality, wherein the integrity checking is carried out to ensure that the data is not lost or damaged, if the data is found to be incomplete, the error log is tried to be collected again or recorded, the collected data is filtered and cleaned to remove invalid data, noise data and abnormal data, the data format is unified, the fact that all the collected data have uniform time stamps is ensured, so that the data from different sources can be accurately aligned during subsequent analysis is constructed, a data warehouse is constructed, and the preprocessed node data is stored in the data warehouse for subsequent analysis and processing;
The relation analysis module is used for analyzing the interrelationship among different subsystems, including communication protocols, data flow directions and dependency relations, constructing a relation graph among the subsystems, initializing parameters and settings of the relation analysis module according to configuration files of the system or user input, acquiring node data of each subsystem from the data acquisition module, importing basic information including subsystem names, function descriptions, interface definitions, node addresses and communication protocols, analyzing the communication protocols used among the subsystems, analyzing the format, message structures and verification modes of the communication protocols, defining the process of data exchange, analyzing the communication protocols and data flow information among the subsystems, tracking the flow directions of data, determining the direct dependency relations among the starting subsystem, the intermediate link and the end subsystem, identifying the direct dependency relations among the subsystems, and deducing the indirect dependency relations among the subsystems through analyzing the data flow directions and the communication protocols, wherein if the A subsystem directly calls interfaces or functions of the B subsystem, judging that the two subsystems are in direct dependency relations among the A subsystem, if the A subsystem is communicated with the C subsystem, analyzing the communication protocols, analyzing the format of the communication protocols, the message structures and verification modes of the communication protocols, defining the indirect dependency relations among the A subsystem and the C subsystem, analyzing the data flow directions, optimizing the relation among the communication protocols, generating the relation, and the relation between the communication protocols, and the key graph, and the map is conveniently and clearly understood, and the relation is generated, and the relation is improved by the relation is obtained, and is clearly displayed when the relation is displayed, and is conveniently and improved by the relation is displayed, and is clearly and improved to the relation is displayed and changed to the relation between the relation graph is conveniently and is clearly and changed by the relation between the data flow and has the relation is obtained;
The fault diagnosis analysis module is used for analyzing an abnormal mode in the node data based on the preprocessed node data and the relation patterns among all the subsystems, judging whether a fault exists or not and giving out a fault type;
the fault alarm recording module triggers an alarm mechanism after determining the fault node, sends out a fault alarm to an operator, records fault information including fault type, occurrence time, fault node and the like, and provides basis for subsequent fault analysis and processing;
The fault processing suggestion module provides fault processing suggestions according to the fault positioning result and the fault type, comprises a fault repairing step, required tools or spare parts, preventive measures and the like, and helps operators to quickly solve the faults and restore the normal operation of the system by providing specific processing suggestions.
In embodiment 2, as shown in fig. 2, on the basis of embodiment 1, the present invention provides a technical solution, wherein preferably, the fault diagnosis analysis module specifically includes:
The method comprises the steps of importing preprocessed node data into a fault diagnosis analysis module, utilizing a relation graph among all subsystems to determine connection relations and communication paths among all nodes, positioning related nodes and connecting lines in the relation graph according to the range and paths affected by faults, analyzing the flow paths among the nodes of the data, determining fault propagation paths, carrying out feature extraction on the node data, extracting features of communication signals and state information, wherein the features of the communication signals are signal amplitude, signal phase and signal noise ratio, the features of the state information are temperature, current, voltage and response time, presetting abnormal thresholds of the features of the communication signals and the features of the state information based on fault management requirements of an MVB network, combining historical data to distinguish abnormal features in the features of the communication signals and the features of the state information, wherein the features of the abnormal communication signals are signal amplitude abnormality, signal phase distortion and signal noise ratio reduction, the features of the abnormal state information are temperature abnormality, current fluctuation, voltage fluctuation and abnormal response time, comparing the features with the abnormal thresholds of the features according to collected real-time communication signals and state information data, obtaining abnormal identification values of the features, comprehensively obtaining abnormal identification values of the communication signals, calculating abnormal signal identification values, and abnormal signal trend analysis indexes; comprehensively obtaining abnormal recognition values of state information features, calculating state abnormal recognition indexes, analyzing abnormal trend of the state information, combining the signal abnormal recognition indexes and the state abnormal recognition indexes, calculating fault recognition coefficients, analyzing abnormal modes in node data, and judging specific fault types according to the abnormal mode recognition results and the relation patterns, wherein the fault types comprise hardware faults, hardware faults and the like, software failure and communication failure;
further, the calculation formula of the signal anomaly identification index is as follows:
;
In the formula, As an index for identifying the signal abnormality,For the current signal amplitude value,Is an abnormal threshold value of the signal amplitude,As the value of the phase of the current signal,Is an abnormal threshold value of the phase of the signal,AndConstants of signal amplitude and signal phase adjustment sensitivity, respectively, take positive values for controlling the steepness of the exponential function,For the current signal-to-noise ratio value,As an outlier threshold for the signal-to-noise ratio,And has a value ranging from 0 to 1, when all features are within normal ranges,Near 0, when one or more features exceeds its anomaly threshold,Close to 1, ifThenNear 0, ifThenClose to 1, asThe value of the part is gradually increased, and the change rate is increased byControl ofThenNear 0, ifThenClose to 1, asThe value of the part is gradually increased, and the change rate is increased byControl ofThenNear 0, ifThenClose to 1, asIncreasing, the value of the portion gradually increases;
the calculation formula of the state anomaly identification index is as follows:
;
In the formula, As the state abnormality identification index,As a value of the current temperature of the water,Is an abnormal threshold value of the temperature,Is the maximum allowable value of the temperature and,As the current value of the current is present,Is an abnormal threshold value of the current,Taking positive value for constant of current adjustment sensitivity, for controlling steepness of exponential function,As the value of the current voltage is the value of the current voltage,Is an abnormal threshold value of the voltage,Is the maximum allowable value of the voltage,As a value of the current response time,In order to respond to the abnormal threshold of time,In order to respond to the constant of the time adjustment sensitivity, take a positive value for controlling the steepness of the exponential function,And has a value ranging from 0 to 1, when all features are within normal ranges,Near 0, when one or more features exceeds its anomaly threshold,Close to 1, ifThenNear 0, ifThenAlong withThe increase gradually increases and the rate of change is controlled by the root function ifThenNear 0, ifThenClose to 1, asThe value of the part is gradually increased, and the change rate is increased byControl ofThenNear 0, ifThenAlong withThe increase gradually increases and the rate of change is controlled by a linear function ifThenNear 0, ifThenClose to 1, asThe value of the part is gradually increased, and the change rate is increased byControlling;
The calculation formula of the fault recognition coefficient is as follows:
;
In the formula, As a result of the failure recognition factor,As an index for identifying the signal abnormality,As the state abnormality identification index,The constant of the sensitivity is adjusted for the state abnormality identification index, a positive value is taken for controlling the steepness of the exponential function,And has a value ranging from 0 to 1, when all features are within normal ranges,Near 0, ifClose to 0, thenNear 0, ifClose to 1, thenAlong withThe increase gradually increases and the rate of change is controlled by the root function ifThenNear 0, ifThenClose to 1, asThe value of the part is gradually increased, and the change rate is increased byControlling;
Further, the fault type judging process includes:
Setting a distinguishing threshold K of a fault recognition coefficient according to historical data to distinguish normal and abnormal conditions, when the value of the fault recognition coefficient is smaller than K, indicating that abnormal conditions exist, comparing according to the size of the fault recognition coefficient and the distinguishing threshold, identifying a node with higher degree of abnormality, further carrying out deep analysis on the characteristics of the identified abnormal node to judge whether an abnormal mode exists, further analyzing a signal abnormal recognition index and a state abnormal recognition index for the abnormal mode to determine specific abnormal characteristics, finding the position of the abnormal node in a relation graph, marking the abnormal node, and based on the connection relation between the abnormal node and other nodes, analyzing the propagation path and the influence range of the abnormal mode in the MVB network, and judging specific fault types according to the abnormal mode, the fault propagation path and the node characteristics, wherein the hardware faults are represented by damage or performance degradation of physical components, such as circuit board aging, interface poor contact and the like, in a relation map, the hardware faults are related to specific hardware nodes, the software faults are represented by program errors, improper configuration or virus infection and the like, in the relation map, the software faults are related to the software nodes or related configuration nodes, the communication faults are represented by signal interference, communication protocol errors or network faults and the like, and in the relation map, the communication faults are generally related to the communication nodes or the network nodes;
the fault alarm recording module specifically comprises:
Determining a node with a fault through fault identification coefficient analysis, abnormal mode detection and relation map analysis, determining the specific position of the fault, providing an accurate target for subsequent fault analysis and processing, automatically triggering an alarm mechanism by a fault alarm recording module after the fault node is determined, and automatically updating the fault state by the fault alarm recording module and recording the processing result and the processing time by the fault alarm recording module after the fault processing is completed, wherein the alarm comprises a plurality of modes of sound-light-electric alarm, short message notification and mail reminding, and further, the fault information is sent to an operator through a preset alarm mode, so that the operator can quickly know the fault condition and make an accurate coping decision, the fault information, including the fault type, the occurrence time, the fault node and detailed information of fault description, is automatically recorded according to the recorded fault information, and the detailed fault report is generated for subsequent fault analysis and processing;
the fault handling suggestion module specifically includes:
According to the determined fault type, matching corresponding fault handling advice from a fault handling knowledge base containing various known fault handling advice, generating specific fault handling advice including fault repair steps, required tools or spare parts and precautions according to the matched relevant fault items, and providing the generated handling advice to an operator, wherein the steps required for repairing the fault, including necessary operation sequences and precautions, are specified, the specific tools, spare parts or test equipment required for completing the repair work are pointed out, advice for preventing similar faults from happening again is provided, the fault handling progress is tracked, the operator is allowed to record the completion of each step, any problems encountered and additional measures taken, and after handling the fault, the operator feeds back the handling results and newly discovered information to update the fault handling knowledge base.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN120018089A (en) * | 2025-04-15 | 2025-05-16 | 沈阳安普合科技有限公司 | Vehicle Data Wireless Interaction System |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220200844A1 (en) * | 2019-09-11 | 2022-06-23 | Huawei Technologies Co., Ltd. | Data processing method and apparatus, and computer storage medium |
| CN114818353A (en) * | 2022-05-09 | 2022-07-29 | 北京交通大学 | A fault prediction method for train control on-board equipment based on fault feature relationship graph |
| CN115529229A (en) * | 2022-11-09 | 2022-12-27 | 中国农业银行股份有限公司 | Fault positioning method, device and equipment |
| CN116489000A (en) * | 2023-04-14 | 2023-07-25 | 中车青岛四方车辆研究所有限公司 | Train MVB communication network fault diagnosis and positioning method and system |
| CN116976043A (en) * | 2023-05-26 | 2023-10-31 | 南京航空航天大学 | An intelligent auxiliary decision-making method for SDSS power grid based on knowledge graph |
| CN118249504A (en) * | 2024-03-15 | 2024-06-25 | 浙江万胜智能科技股份有限公司 | Microgrid equipment status intelligent diagnosis and alarm notification system |
-
2025
- 2025-02-11 CN CN202510147986.3A patent/CN119603131B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220200844A1 (en) * | 2019-09-11 | 2022-06-23 | Huawei Technologies Co., Ltd. | Data processing method and apparatus, and computer storage medium |
| CN114818353A (en) * | 2022-05-09 | 2022-07-29 | 北京交通大学 | A fault prediction method for train control on-board equipment based on fault feature relationship graph |
| CN115529229A (en) * | 2022-11-09 | 2022-12-27 | 中国农业银行股份有限公司 | Fault positioning method, device and equipment |
| CN116489000A (en) * | 2023-04-14 | 2023-07-25 | 中车青岛四方车辆研究所有限公司 | Train MVB communication network fault diagnosis and positioning method and system |
| CN116976043A (en) * | 2023-05-26 | 2023-10-31 | 南京航空航天大学 | An intelligent auxiliary decision-making method for SDSS power grid based on knowledge graph |
| CN118249504A (en) * | 2024-03-15 | 2024-06-25 | 浙江万胜智能科技股份有限公司 | Microgrid equipment status intelligent diagnosis and alarm notification system |
Non-Patent Citations (2)
| Title |
|---|
| 刘斌;王立德;丁国君;王苏敬;: "基于DSP和MVB的机车瞬间故障检测记录仪", 铁道机车车辆, no. 04, 25 August 2010 (2010-08-25) * |
| 蔡龙龙 等: ""轨道交通车辆专家诊断系统的分析与应用"", 《机电工程技术》, vol. 52, no. 02, 9 March 2023 (2023-03-09), pages 284 - 287 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN120018089A (en) * | 2025-04-15 | 2025-05-16 | 沈阳安普合科技有限公司 | Vehicle Data Wireless Interaction System |
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