A method for realizing fault early warning and management of electronic related equipment in railway signal system

Abstract

The present invention provides a method for realizing fault early warning and management of electronic related equipment of a railway signal system, which comprises: retrieving delayed passenger clearance data to determine the fault mode causing the delay of the passenger clearance operation; establishing a fault logic model, a fault assessment model, and constructing the relationship between the fault mode and the operating state, and the relationship between the maintenance measure and the fault mode in a monitoring and early warning system; extracting fault characteristic parameters according to the relationship between the fault logic model, the fault mode and the operating state, and judging whether the fault characteristic parameters are within a normal monitoring threshold; and / or obtaining the occurrence probability of the fault mode according to the fault assessment model; assigning different weights to the fault characteristic parameters and the occurrence probability corresponding to the fault mode in combination with key factors, and calculating the early warning level of the fault mode; selecting the elimination method of the fault early warning level according to the relationship between the maintenance measure and the fault mode, realizing early warning and management of the fault mode, and effectively reducing the failure rate.

Description

Technical Field

[0001] The present invention belongs to the field of operation and maintenance analysis of railway signal system electronic systems, and in particular relates to a method for realizing fault early warning and management of electronic related equipment of railway signal system. Background Art

[0002] At present, railway signal industry specifications such as "Provisional Technical Conditions for Onboard Equipment of New Train Control System", "Provisional Technical Conditions for Integrated Train Control and Interlocking Equipment of New Train Control System", "Technical Conditions for Onboard Equipment of CTCS-2 Level Train Control" and "Technical Conditions for Onboard Equipment of Autonomous CTCS-3 Level Train Control" have put forward requirements for RAM indicators of onboard or interlocking equipment such as failure rate, maintenance time, and maintenance guarantee. Although the signal system has been reducing the flow of faults to the site through the forward-focused design of the whole life cycle, it has been found through sorting that there are still faults in operation that cause train ATP downtime or loss of train integrity, which in turn cause line-level operation delays and reduce the operational service capabilities of the railway signal system.

[0003] First, for major faults that affect operations, such as ATP downtime, inability to release emergency brakes, inability to open doors, and unsuccessful restart of on-board equipment, most of the current strategies adopted are post-fault repairs, which have certain limitations and cannot avoid the chain reaction of lines or the occurrence of emergency accidents caused by sudden faults. Secondly, if there is no early warning for operational delays caused by clearing passengers or dropping cars, and only regular inspections are carried out, there are defects such as long time consumption, high inspection costs, high labor consumption, and low efficiency, which in turn leads to low economic benefits. Summary of the invention

[0004] According to the operational service capability requirements of the railway signal system and the random fault characteristics of the signal electronic equipment, the present invention proposes a fault warning and management implementation method applicable to the electronic related equipment of the railway signal system, which can warn in advance of operational delays such as clearing passengers or dropping trains, avoid the chain reaction of lines caused by sudden faults, or the occurrence of emergency accidents; and can give the life index of the consumable components according to the operational parameters of online diagnosis, and feedback to the design, so as to improve the efficiency of product selection and reduce the failure rate; at the same time, it can give the possible cause of the fault, maintenance measures and other maintenance information while giving the fault warning, carry out preventive maintenance, realize effective active fault handling, reduce the cost of regular inspection, make up for the limitations of the existing fault diagnosis-fault repair, give more time for maintenance preparation management, and avoid unnecessary cost. Finally, the fault warning and management implementation method can realize the adjustment and correction of the fault warning management framework and the fault warning model according to the specific application environment and data of different lines.

[0005] To achieve the above-mentioned purpose, the present invention provides a method for realizing fault warning and management of electronic related equipment of a railway signal system, which comprises: retrieving delayed passenger clearance data to determine the fault mode that causes the delay in passenger clearance operation; establishing a fault logic model, a fault assessment model, and constructing the relationship between the fault mode and the operating state, and the relationship between the maintenance measures and the fault mode in the monitoring and early warning system; extracting the fault characteristic parameters corresponding to the fault mode according to the fault logic model and the relationship between the fault mode and the operating state, monitoring the fault characteristic parameters, and judging whether the fault characteristic parameters are within the normal monitoring threshold; and / or obtaining the occurrence probability of the fault mode according to the fault assessment model; assigning different weights to the fault characteristic parameters and the occurrence probability corresponding to the fault mode in combination with key factors, and calculating the early warning level of the fault mode; selecting the method for eliminating the fault early warning level according to the relationship between the maintenance measures and the fault mode, so as to realize the early warning and management of the fault mode.

[0006] Preferably, the method of retrieving delayed passenger clearance data and determining the fault mode causing the delay in passenger clearance operation comprises the following steps: S101, retrieving the delayed passenger clearance documents of each year from each project management office; S102, screening the fault impact field in the delayed passenger clearance documents in step S101; S103, retrieving the "fault mode" according to the fault impact field; S104, establishing the fault mode causing delay of more than M minutes as the research object, where M≥5.

[0007] Preferably, the fault impact fields include "passenger clearance", "train drop", and "delay"; the fault modes include loss of ATP mode, inability to release emergency braking, inability to open doors, unsuccessful on-board restart, on-board freeze, and inability to establish train mode.

[0008] Preferably, the establishment of a fault logic model in the monitoring and early warning system includes the following steps: S201, retrieving functional design documents, wherein the design documents include system function requirement documents, system architecture design documents, hardware design documents, and software design documents related to the fault mode; S202, analyzing the fault cause of the fault mode, and selecting a fault tree or function-fault flow method for analysis; S203, determining the logical relationship between the fault cause and the fault mode, wherein the logical relationship includes OR logic and AND logic; S204, analyzing the fault mechanism of the fault mode, wherein this step specifically analyzes the module circuit or key chip; S205, retrieving design data, wherein the design data includes hardware schematics and software functions corresponding to the fault mode.

[0009] Preferably, the establishment of a fault logic model in the monitoring and early warning system also includes: S206, determining the monitored fault characteristic parameters; S207, judging whether the fault characteristic parameters in step S206 are monitored by the monitoring and early warning system; if the fault characteristic parameters are monitored, marking them as monitored; if the fault characteristic parameters are not monitored, executing step S208; S208, incorporating the unmonitored fault characteristic parameters into the monitoring range of the monitoring and early warning system.

[0010] Preferably, the determination of the monitored fault characteristic parameters described in step S206 includes the following steps: S261, extracting fault characteristic parameters, wherein the fault characteristic parameters include impedance, current, and voltage; S262, determining whether the fault characteristic parameters extracted in step S261 are analog signals, and if the fault characteristic parameters are analog signals, executing step S263; otherwise, determining the fault characteristic parameters of the fault mode according to the relationship between the fault mode and the operating state; S263, selecting an algorithm for extracting fault characteristic parameters; S264, embedding a normal monitoring threshold curve in the monitoring and early warning system for determining the fault characteristic parameters; S265, if the fault characteristic parameters are within the normal monitoring threshold curve, terminating the determination of the fault characteristic parameters and incorporating them into the monitoring range of the monitoring and early warning system; otherwise, if they exceed the normal monitoring threshold curve, executing step S266; S266, providing early warning and maintenance strategies; if the fault characteristic parameters exceed the normal range, providing early warnings or maintenance measures.

[0011] Preferably, if the fault characteristic parameters are irregular and the output is a discrete 0 / 1 signal, the ID3 algorithm or the Apriori algorithm is selected; if the fault characteristic parameters are current or voltage signals, the support vector machine algorithm is selected for extracting and monitoring the fault characteristic parameters.

[0012] Preferably, the establishment of a fault assessment model in the monitoring and early warning system includes the following steps: S301, retrieving relevant fault data; S302, cleaning and processing the relevant fault data retrieved in step S301; S303, creating a fault form based on the relevant fault data cleaned and processed in step S302; S304, initializing the parameter model; S305, fitting the parameter model selected in step S304 based on the relevant fault data after cleaning and processing; S306, comparing the result of the parameter model fitted in step S305 with the result of the RAM monitoring platform; if the result of step S305 is close to the result of the RAM monitoring platform, executing step S307; if the result of step S305 is significantly different from the result of the RAM monitoring platform, returning to step S304 and reselecting the initialized parameter model; S307, determining the parameter model fitted in step S305 as the fault assessment model; S308, embedding the fault assessment model determined in step S307 into the monitoring and early warning system to complete the construction of the fault assessment model in the monitoring and early warning system.

[0013] Preferably, the parameter model described in step S304 includes establishing a cumulative failure probability model using X-rank regression or maximum likelihood method.

[0014] Preferably, the parameter model includes a 2-parameter model of Weibull β is the shape parameter, η is the scale parameter, and t is the working time; Weibull's three-parameter model β is the shape parameter, η is the scale parameter, and γ is the location parameter; exponential distribution model F(t) = 1-e -λt , λ is the failure rate, and t is the working time.

[0015] Preferably, the establishment of a fault assessment model in the monitoring and early warning system further includes step S309: creating a repair return form according to the maintainability data; the maintainability data includes delay time and repair time.

[0016] Preferably, a flow chart of the relationship between fault events and operating status is constructed in the monitoring and early warning system, which includes the following steps: S401, determining the alarm fault mode; S402, retrieving log data to obtain the state quantity field related to the alarm fault mode; S403, sorting out the link relationship between the fault mode and the operating status in the log data; finding the operating status and characteristic parameter changes N minutes before the alarm fault mode, and assisting in the selection of fault characteristic parameters, where N≥10.

[0017] Preferably, it also includes establishing a life assessment model for consumable components in the monitoring and early warning system, which specifically includes the following steps: S501, screening consumable failure mechanism components; S502, determining design parameters by querying the design manual; S503, determining actual application parameters; S504, determining application environment factors; S505, determining the life assessment model for consumable components, and establishing the model by combining the specifications with actual online operation data; S506, embedding the life assessment model for consumable components determined in step S505 into the monitoring and early warning system.

[0018] Preferably, constructing the relationship between maintenance measures and failure modes in the monitoring and early warning system includes the following steps: S601, determining a list of failure modes for failure warning; S602, retrieving the field "measures taken on site" in the on-site failure data statistics system and the frequent failure recording system; S603, retrieving the field "measures taken on site" in the on-site failure event reporting platform; S604, retrieving the field "maintenance suggestions" in the existing alarm system; S605, generating a failure mode and maintenance measures form for failure warning; S606, determining whether the relationship between the failure and the maintenance measures already exists in the monitoring and early warning system; if so, it will not be repeatedly added to the monitoring and early warning system; if not, executing step S607; S607, embedding the generated failure mode and maintenance measures form into the monitoring and early warning system.

[0019] Preferably, the key factors include environmental factors, elapsed time or frequency, fault characteristic values, and alarm quantity.

[0020] Preferably, the environmental factors include temperature, humidity, salt spray, and dust. The excellent to good level of the environmental factors is determined based on whether the equipment has dustproof and heat dissipation design data, and weights are assigned to different environmental factors.

[0021] Preferably, the weights of each key factor are determined using expert experience and historical data. i , combined with the actual warning data of the monitoring and early warning system, correct and adjust the weights of each key influencing factor in the monitoring and early warning system i value.

[0022] In summary, compared with the prior art, the present invention provides a method for realizing fault warning and management of electronic related equipment of railway signal system, which can warn in advance of operational delay faults such as passenger clearance or train drop, avoid line chain reactions caused by sudden faults, or the occurrence of emergency accidents, reduce the failure rate of passenger clearance or delay of more than 5 minutes, and improve passenger satisfaction.

[0023] Furthermore, the present invention provides an evaluation model based on field fault data, which is used to reflect the actual availability of products on site, and overcomes the problem that existing purely theoretical calculations are not very consistent with actual applications;

[0024] Furthermore, the present invention can view the available life results of consumable components through the consumable component life assessment model, and generate different statistical charts, effectively improving the efficiency of product selection during design;

[0025] Furthermore, the present invention can provide suggested maintenance measures and possible causes of early warning faults, reduce maintenance support costs, and reduce the intensity of maintenance personnel; at the same time, it provides ideas for the merger and integration of fault warning and management of electronic related equipment of railway signal systems in the monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of the method for realizing fault early warning and management of electronic related equipment of railway signal system of the present invention;

[0027] Figure 2 The flow chart of the research object such as the determination of the present invention leading to the delay of clearing passengers or dropping vehicles;

[0028] Figure 3 A flow chart of constructing a fault logic model of the present invention;

[0029] Figure 4 is a flow chart for extracting fault characteristic parameters of the present invention;

[0030] Figure 5 Partial input and output of fault data information of the present invention;

[0031] Figure 6 A flow chart of constructing a fault assessment model of the present invention;

[0032] Figure 7 A flow chart showing the relationship between a fault event and an operating state of the present invention;

[0033] Figure 8 Constructing a flow chart for the wear-out component life assessment model of the present invention;

[0034] Fig. 9 A maintenance measure and fault relationship flow chart for the present invention;

[0035] Fig.10 It is a framework diagram of the key factors of fault warning and management in the monitoring and early warning system of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the attached embodiment of the present invention Figure 1 ~Attached Fig.10 , the technical solutions, structural features, objectives achieved and effects in the embodiments of the present invention are described in detail.

[0037] It should be noted that the drawings are in a very simplified form and use non-precise proportions. They are only used to conveniently and clearly assist in explaining the embodiments of the present invention, and are not used to limit the conditions for the implementation of the present invention. Therefore, they have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical content disclosed by the present invention.

[0038] It should be noted that, in the present invention, the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or equipment including a series of elements includes not only the elements explicitly listed, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment.

[0039] The present invention provides a method for realizing fault early warning and management of electronic related equipment of railway signal system, such as Figure 1As shown, the fault warning and management implementation method includes: retrieving delayed passenger clearance data to determine the fault mode that causes the delay in passenger clearance operation; establishing a fault logic model, a fault assessment model, and constructing the relationship between the fault mode and the operating state, and the relationship between the maintenance measures and the fault mode in the monitoring and early warning system; extracting the fault characteristic parameters corresponding to the fault mode according to the fault logic model, the relationship between the fault mode and the operating state, monitoring the fault characteristic parameters, and judging whether the fault characteristic parameters are within the normal monitoring threshold; and / or obtaining the occurrence probability of the fault mode according to the fault assessment model; assigning different weights to the fault characteristic parameters and the occurrence probability corresponding to the fault mode in combination with key factors, and calculating the warning level of the fault mode; selecting the elimination method of the fault warning level according to the relationship between the maintenance measures and the fault mode, to realize the early warning and management of the fault mode.

[0040] Among them, Fig.10 As shown, the key factors include environmental factors, elapsed time or frequency, fault characteristic values, number of alarms, etc. Further, the environmental factors are determined based on field data and design data to participate in the fault early warning management environment; the environmental factors include temperature, humidity, salt spray, dust, etc., and the environmental factors are determined to be good or excellent based on whether the equipment has dustproof, heat dissipation and other design data, and the weights of different environmental factors are assigned. Further, the weights of each key factor are determined using expert experience and historical data. i , combined with the actual warning data of the monitoring and early warning system, correct and adjust the weights of each key influencing factor in the monitoring and early warning system i value, thereby improving the accuracy and effectiveness of fault warning.

[0041] Among them, Figure 2 As shown, the method of retrieving delayed passenger clearance data and determining the fault mode causing the delay in passenger clearance operation includes the following steps: S101, retrieving the delayed passenger clearance documents of each year from each project management office; S102, screening the fault impact fields in the delayed passenger clearance documents in S101, such as "passenger clearance", "car drop", "delay", etc.; S103, retrieving "fault mode" according to the fault impact field; S104, establishing the fault mode causing delay of more than 5 minutes as the research object; further, the fault modes include: ATP mode loss, emergency brake failure, door failure, vehicle restart failure, vehicle crash, train mode failure, etc.

[0042] Among them, Figure 3As shown, the establishment of a fault logic model in the monitoring and early warning system includes the following steps: S201, calling the functional design document, that is, calling each functional design document corresponding to the fault mode, such as the system functional requirement document, system architecture design document, hardware design document and software design document related to the fault mode; S202, analyzing the fault cause of the fault mode, and selecting a fault tree or function-fault flow method for analysis; S203, determining the logical relationship between the fault cause and the fault mode, the logical relationship includes OR logic, AND logic, etc.; S204, analyzing the fault mechanism of the fault mode, that is, a deeper analysis of the root cause of the fault and the failure mechanism, this step specifically analyzes the module circuit or key chip; S205, calling the design data, the design data includes the hardware schematic diagram and software function corresponding to the fault mode; the fault logic model is constructed through steps S201 to S205, and the fault logic model corresponds each fault mode to the functional design document, logical relationship, fault mechanism and design data corresponding to each fault mode, so as to facilitate the subsequent extraction of fault feature parameters.

[0043] Specifically, taking the emergency brake failure mode that cannot be released as an example, the cause and failure mechanism of the failure are found through the fault tree method. Based on the design document of the emergency brake, it is obtained that the emergency brake function is related to the speed sensor, the backplane of the cabinet, the board PSB that controls the emergency brake, the safety input and output control board, the channel interface, the relay, etc. Therefore, its fault logic model is established according to the functional association relationship.

[0044] Furthermore, the establishment of a fault logic model in the monitoring and early warning system also includes: step S206, determining the monitored fault characteristic parameters, such as impedance, current, voltage, etc.; step S207, judging whether the fault characteristic parameters in step S206 are monitored by the monitoring and early warning system; if the fault characteristic parameters have been monitored, marking them as monitored; if the fault characteristic parameters have not been monitored, executing step S208; step S208, including the unmonitored fault characteristic parameters in the monitoring range of the monitoring and early warning system.

[0045] Further, if Figure 4 As shown, the step S206 of determining the monitored fault characteristic parameters includes the following steps:

[0046] S261, extracting fault characteristic parameters, including impedance, current, voltage, etc. as described in step S206;

[0047] S262, determining whether the fault characteristic parameter extracted in step S261 is an analog signal, if the fault characteristic parameter is an analog signal, executing step S263; otherwise, determining the fault characteristic parameter of the fault mode according to the relationship between the fault mode and the operating state; wherein the information represented by the continuously changing physical quantity is determined to be an analog quantity; and the output signal is 0 / 1, and is determined to be a digital signal;

[0048] S263, select an algorithm for extracting fault characteristic parameters; in the embodiment, if the fault characteristic parameters are irregular and the output is a discrete 0 / 1 signal, the ID3 algorithm or the Apriori algorithm may be selected; if the fault characteristic parameters are current or voltage signals, the support vector machine algorithm may be selected for extracting and monitoring the fault characteristic parameters;

[0049] S264. Embed a normal monitoring threshold curve in the monitoring and early warning system for determining fault characteristic parameters;

[0050] S265, if the fault characteristic parameter is within the normal monitoring threshold curve, then the determination of the fault characteristic parameter is terminated and included in the monitoring range of the monitoring and early warning system; otherwise, if it exceeds the normal monitoring threshold curve, then execute step S266;

[0051] S266, provide early warning and maintenance strategies; if the fault characteristic parameters exceed the normal range, give early warning or maintenance measures. The correction of the fault characteristic parameters is based on the field application, and the algorithm selected in step S263 is continuously learned to achieve the purpose of correcting the fault characteristic parameter model, which is to improve the accuracy of early warning.

[0052] Further, if Figure 6 As shown, the establishment of a fault assessment model in the monitoring and early warning system includes the following steps:

[0053] S301, retrieve relevant fault data; the relevant fault data includes field fault data obtained from CRM (field fault data statistics system), K2 (frequent fault recording system), field fault event reporting platform, monitoring data retrieved from MSS (operation and maintenance system), alarm data and maintenance data;

[0054] Specifically, Figure 5It is the partial input and output of the relevant fault data information in the present invention, wherein the on-site fault data includes fields such as fault component, fault phenomenon, fault date, fault quantity, emergency braking amount, whether it causes train ATP downtime, operation delay duration (minutes), environmental conditions, etc.; the maintenance data includes fault component, maintenance duration (minutes), and maintenance measures; the monitoring data includes the object monitored on the existing maintenance platform, fault code, fault description, etc., which is used to distinguish whether the monitored object is an analog signal or a digital signal; the alarm data includes the alarmed object on the maintenance platform, fault alarm content, alarm cause, etc.

[0055] S302, cleaning and processing the relevant fault data retrieved in step S301; the specific steps of data cleaning and processing include: S321, formulating the data format required for making a form; S322, eliminating missing values ​​or invalid values ​​in the field fault data; S323, completing the data to form cleaned field fault data;

[0056] S303, creating a fault form according to the relevant fault data after cleaning in step S302; the fault form includes information such as fault time, fault sample volume, environmental conditions, and whether the fault state is failure or success;

[0057] S304, initializing the parameter model; X-rank regression (RRX) or maximum likelihood method can be used to establish a cumulative failure probability model, such as Weibull's two-parameter model ( β is the shape parameter, η is the scale parameter, t is the working time), Weibull's 3-parameter model ( β is the shape parameter, η is the scale parameter, γ is the location parameter), exponential distribution model (F(t) = 1-e -λt , λ is the failure rate, t is the working time);

[0058] S305, fitting the parameter model selected in step S304 according to the field fault data after cleaning; in one embodiment, 78 samples of a certain line collected by the fault assessment model of key equipment, running 45048 hours of fault data analysis to obtain The probability of failure of this key equipment at time t can be predicted based on the time t of operation. A threshold probability of failure can also be set as an active maintenance condition. When the probability is lower than the threshold, the monitoring and early warning system sends an alarm signal to prompt the operation and maintenance staff to prevent the failure from occurring.

[0059] S306, compare the result of the parameter model after fitting in step S305 with the result of the RAM monitoring platform (reliability, availability, and maintainability platform); since the RAM monitoring platform is sample data obtained by monitoring actual data, if the result of step S305 is close to the result of the RAM monitoring platform, execute step S307; if the result of step S305 is significantly different from the result of the RAM monitoring platform, return to step S304 and reselect the initialization parameter model;

[0060] S307, determining the parameter model fitted in step S305 as a fault assessment model;

[0061] S308: Embed the fault assessment model determined in step S307 into the monitoring and early warning system to complete the construction of the fault assessment model in the monitoring and early warning system.

[0062] Furthermore, the establishment of a fault assessment model in the monitoring and early warning system also includes step S309: creating a repair form based on the maintainability data; the maintainability data includes delay time, repair time, etc.; based on the repair form, the corresponding delay time and the time required for repair can be directly obtained according to the fault mode, so that the operation and maintenance personnel can make maintenance plans in advance and improve maintenance efficiency.

[0063] Figure 7 The present invention is a flow chart of building a relationship between a fault event and an operating state in a monitoring and early warning system, which includes the following steps:

[0064] S401, determining alarm failure mode A;

[0065] S402, retrieve the log data, and obtain the relevant state quantity fields of the alarm fault mode A; since the log data contains the relevant state quantity fields of the possible fault information, the relevant state quantity fields can describe the train operation status at the time of the fault and some action status information related to the train protection; for example, the occurrence of a fault event must be an abnormality in a certain characteristic parameter, but the fault event at this time is not enough to trigger an alarm, and then at a certain time later, this fault event triggers the occurrence of another fault event, thereby causing an alarm and possibly causing the train ATP to shut down, affecting the train operation; for example, when the alarm fault mode is that the emergency brake cannot be released, the relevant state quantity fields related to the emergency brake cannot be released include the operating status of the speed sensor in the system, the operating status of the board controlling the emergency brake, the status of the safety input and output control board, the status of the backplane, etc.;

[0066] S403. Sort out the link relationship between the fault mode and the operating status in the log data; specifically, find the operating status and characteristic parameter changes of the alarm fault mode A N minutes (N≥10) before the alarm fault mode A, the purpose of which is to find out what characteristic parameter changes lead to the occurrence of the alarm fault mode A, and then assist in the selection of fault characteristic parameters.

[0067] In order to evaluate and warn the available life of online equipment with a failure mechanism of wear and tear, the present invention provides a method for implementing fault warning and management of electronic related equipment in a railway signal system, which also includes: establishing a wear and tear component life evaluation model in the monitoring and warning system. Specifically, Figure 8 As shown in the figure, establishing a life assessment model for depletion-type components includes the following steps:

[0068] S501. Screen components with wear-out failure mechanisms, such as switches, relays, LEDs, liquid aluminum electrolyte capacitors, optocouplers, flash, connectors, batteries, etc.

[0069] S502, determining design parameters by consulting a design manual, such as a durability index of the liquid aluminum electrolyte, a rated number of erase and write times of the flash, etc.;

[0070] S503, determining actual application parameters, such as the number of plug-in and pull-out times in actual application, the input current of the optocoupler, the input current of the LED, the designed erase and write cycle of the flash, etc.;

[0071] S504, determining application environment factors, such as temperature, etc.;

[0072] S505. Determine the life assessment model of the consumable component, and establish the model by combining the specification with the actual online operation data. Table 1 shows the available life assessment model of some consumable components:

[0073]

[0074]

[0075] Table 1. Available life assessment model for some depletion-type components

[0076] S506: embed the consumable component life assessment model determined in step S505 into the monitoring and early warning system. By evaluating the life of the consumable component through the consumable component life assessment model, early warning management of the consumable component can be performed in advance, effectively avoiding the failure of the consumable component during use, greatly reducing the failure rate, and avoiding operational delays.

[0077] Further, if Fig. 9 As shown in the figure, building the relationship between maintenance measures and failure modes in the monitoring and early warning system includes the following steps:

[0078] S601, determining a fault mode list of fault warning; that is, obtaining the fault mode list through steps S101 to S104;

[0079] S602, retrieve the field "Measures taken on site" in CRM and K2;

[0080] S603, retrieve the field "measures taken on site" in the on-site fault event reporting platform, that is, the on-site maintenance measures taken recorded in the current historical fault data;

[0081] S604, retrieve the field "maintenance suggestion" in the existing alarm system, that is, some maintenance suggestions given for the warning failure mode, including but not limited to the "measures taken on site" mentioned in step S602 and step S603;

[0082] S605, generating a failure mode and maintenance measure form for failure warning;

[0083] S606, determine whether the relationship between the fault and the maintenance measure already exists in the monitoring and early warning system. If so, do not add it to the monitoring and early warning system again. If not, execute step S607;

[0084] S607, embed the generated fault mode and maintenance measure form into the monitoring and early warning system. By querying the fault mode and maintenance measure form in the monitoring and early warning system, maintenance measures can be quickly obtained when a fault is warned or occurs, thereby improving the speed of handling faults, shortening maintenance time, and avoiding the impact of excessive maintenance time on operational delays.

[0085] In summary, the present invention provides a method and process for constructing fault warning and management of electronic related equipment of railway signal system, which can warn in advance of operational delay faults such as passenger clearance or train drop, avoid line chain reactions caused by sudden faults, or the occurrence of emergency accidents, reduce the failure rate of passenger clearance or delays of more than 5 minutes, and improve passenger satisfaction.

[0086] Furthermore, the present invention provides an evaluation model based on field fault data, which is used to reflect the actual availability of products on site, and overcomes the problem that existing purely theoretical calculations are not very consistent with actual applications;

[0087] Furthermore, the present invention can view the available life results of consumable components through the consumable component life assessment model, and generate different statistical charts, effectively improving the efficiency of product selection during design;

[0088] Furthermore, the present invention can provide suggested maintenance measures and possible causes of early warning faults, reduce maintenance support costs, and reduce the intensity of maintenance personnel; at the same time, it provides ideas for the merger and integration of fault warning and management of electronic related equipment of railway signal systems in the monitoring system.

[0089] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A method for realizing fault warning and management of electronic related equipment in railway signal system, characterized in that: include: Retrieve delayed clearance data to identify the failure mode that caused the delay in clearance operations; Establish fault logic model and fault assessment model in monitoring and early warning system, and build the relationship between fault mode and operation status, and the relationship between maintenance measures and fault mode; Extracting fault characteristic parameters corresponding to the fault mode according to the fault logic model and the relationship between the fault mode and the operating state, monitoring the fault characteristic parameters, and determining whether the fault characteristic parameters are within a normal monitoring threshold; and / or obtaining the occurrence probability of the failure mode according to the failure assessment model; The fault characteristic parameters and occurrence probability corresponding to the fault mode are combined with key factors to assign different weights, and the warning level of the fault mode is calculated; According to the relationship between maintenance measures and failure modes, a method for eliminating the failure warning level is selected to achieve early warning and management of the failure mode; The establishment of a fault assessment model in the monitoring and early warning system comprises the following steps: S301, retrieve relevant fault data; S302, cleaning and processing the relevant fault data retrieved in step S301; S303, creating a fault form according to the relevant fault data cleaned in step S302; S304, initializing a parameter model; the parameter model includes establishing a cumulative failure probability model using X-rank regression or maximum likelihood method; S305, fitting the parameter model selected in step S304 according to the relevant fault data after cleaning; S306, compare the result of the parameter model after fitting in step S305 with the result of the RAM monitoring platform; if the result of step S305 is close to the result of the RAM monitoring platform, execute step S307; if the result of step S305 is significantly different from the result of the RAM monitoring platform, return to step S304 and reselect the initialization parameter model; S307, determining the parameter model fitted in step S305 as a fault assessment model; S308, embedding the fault assessment model determined in step S307 into the monitoring and early warning system, completing the construction of the fault assessment model in the monitoring and early warning system; Wherein, the parameter model includes the 2-parameter model of Weibull β is the shape parameter, η is the scale parameter, and t is the working time; Weibull's three-parameter model β is the shape parameter, η is the scale parameter, and γ is the location parameter; exponential distribution model F(t) = 1-e -λt , λ is the failure rate, t is the working time; The establishment of a fault assessment model in the monitoring and early warning system further includes step S309: creating a repair return form according to the maintainability data; the maintainability data includes delay time and repair time.

2. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: The method of retrieving delayed passenger removal data and determining the failure mode causing the delayed passenger removal operation includes the following steps: S101. Obtain the annual delayed clearance documents from each project management office; S102, filtering the fault impact field in the delayed customer clearance document in step S101; S103, retrieve "fault mode" according to the fault impact field; S104. Establish the failure mode that causes delay of more than M minutes as the research object, where M≥5.

3. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 2, characterized in that: The fault impact fields include "passenger clearance", "car drop", and "delay"; The failure modes include loss of ATP mode, inability to release the emergency brake, inability to open the door, unsuccessful vehicle restart, vehicle freeze, and inability to establish the train mode.

4. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: The establishment of a fault logic model in the monitoring and early warning system comprises the following steps: S201, retrieve functional design documents, wherein the design documents include system functional requirement documents, system architecture design documents, hardware design documents, and software design documents related to failure modes; S202, analyzing the fault cause of the fault mode, and selecting a fault tree or function-fault flow method for analysis; S203, determining a logical relationship between the fault cause and the fault mode, wherein the logical relationship includes an OR logic and an AND logic; S204, analyzing the failure mechanism of the failure mode, this step specifically analyzes the module circuit or key chip; S205 , retrieving design data, where the design data includes a hardware schematic diagram and software functions corresponding to the failure mode.

5. The method for realizing fault early warning and management of electronic related equipment of railway signal system as claimed in claim 4, characterized in that: The establishment of a fault logic model in the monitoring and early warning system also includes: S206, determining the monitored fault characteristic parameters; S207, determining whether the fault characteristic parameters in step S206 are monitored by the monitoring and early warning system; if the fault characteristic parameters are monitored, marking them as monitored; if the fault characteristic parameters are not monitored, executing step S208; S208. Include the unmonitored fault characteristic parameters into the monitoring scope of the monitoring and early warning system.

6. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 5, characterized in that: The step S206 of determining the monitored fault characteristic parameters includes the following steps: S261, extracting fault characteristic parameters, wherein the fault characteristic parameters include impedance, current, and voltage; S262, determining whether the fault characteristic parameter extracted in step S261 is an analog signal, if the fault characteristic parameter is an analog signal, executing step S263; otherwise, determining the fault characteristic parameter of the fault mode according to the relationship between the fault mode and the operating state; S263, selecting an algorithm for extracting fault characteristic parameters; S264. Embed a normal monitoring threshold curve in the monitoring and early warning system for judging fault characteristic parameters; S265, if the fault characteristic parameter is within the normal monitoring threshold curve, then the determination of the fault characteristic parameter is terminated and included in the monitoring range of the monitoring and early warning system; otherwise, if it exceeds the normal monitoring threshold curve, then execute step S266; S266. Provide early warning and maintenance strategies; if the fault characteristic parameters exceed the normal range, give early warning or maintenance measures.

7. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 6, characterized in that: If the fault characteristic parameters are irregular and the output is a discrete 0 / 1 signal, the ID3 algorithm or the Apriori algorithm is selected; if the fault characteristic parameters are current or voltage signals, the support vector machine algorithm is selected for extracting and monitoring the fault characteristic parameters.

8. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: A flow chart of the relationship between fault events and operating status is constructed in the monitoring and early warning system, which includes the following steps: S401, determining an alarm failure mode; S402, retrieve log data to obtain the state quantity fields related to the alarm fault mode; S403, sorting out the link relationship between the fault mode and the operating status in the log data; finding the operating status and characteristic parameter changes N minutes before the alarm fault mode, and assisting in the selection of fault characteristic parameters, where N≥10.

9. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: It also includes establishing a life assessment model for depletion-type components in the monitoring and early warning system, which specifically includes the following steps: S501, screening of components with wear-out failure mechanisms; S502, determining design parameters by querying a design manual; S503, determining actual application parameters; S504, determining application environment factors; S505, determining a life assessment model for a consumable component, and establishing the model by combining specifications with actual online operation data; S506: embed the life assessment model of the depletion-type component determined in step S505 into the monitoring and early warning system.

10. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: Building the relationship between maintenance measures and failure modes in the monitoring and early warning system includes the following steps: S601, determine a list of failure modes for failure warning; S602, retrieve the field "measures taken on site" in the on-site fault data statistics system and the frequent fault recording system; S603, retrieve the field "measures taken on site" in the on-site fault event reporting platform; S604, retrieve the field "Maintenance Suggestion" in the existing alarm system; S605, generating a failure mode and maintenance measure form for failure warning; S606, determine whether the relationship between the fault and the maintenance measure already exists in the monitoring and early warning system. If so, do not add it to the monitoring and early warning system again. If not, execute step S607; S607: embed the generated failure mode and maintenance measure form into the monitoring and early warning system.

11. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: The key factors include environmental factors, elapsed time or frequency, fault characteristic values, and alarm quantity.

12. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 11, characterized in that: The environmental factors include temperature, humidity, salt spray, and dust. The excellent, medium, and good levels of the environmental factors are determined based on whether the equipment has dustproof and heat dissipation design data, and different environmental factors are assigned weights.

13. The method for realizing fault early warning and management of electronic related equipment of railway signal system according to claim 1, characterized in that: Use expert experience and historical data to determine the weight of each key factor i , combined with the actual warning data of the monitoring and early warning system, correct and adjust the weights of each key influencing factor in the monitoring and early warning system i value.

Images