CN113361858A - Vehicle state evaluation method and system based on rail transit vehicle fault data - Google Patents
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Abstract
The invention relates to a vehicle state evaluation method and a system based on rail transit vehicle fault data, wherein the method comprises the following steps: 1) constructing a basic information base and a vehicle function structure of all vehicle types of the whole network; 2) constructing a vehicle fault library covering all vehicle types of the whole network; 3) acquiring historical fault data of the electric train, preprocessing the historical fault data, and counting the number of faults; 4) and constructing an electric train state evaluation model, and calculating by combining the fault frequency and the fault quantitative grade to obtain the vehicle overall state score of the electric train. Compared with the prior art, the method has the advantages of grading, classified effective management, objective scientific evaluation, improvement of working efficiency, fault analysis and query and the like.
Description
Technical Field
The invention relates to the field of rail electric train state detection and evaluation, in particular to a vehicle state evaluation method and system based on rail transit vehicle fault data.
Background
Under the background of high-speed development of urban rail transit, the increasing of the rail transit vehicle base and the vehicle management present an unbalanced development situation. Particularly, for cities with earlier urban rail transit investment, network operation is comprehensively realized at present, a plurality of net attached vehicle types exist, and vehicles have differences in the aspects of service life, design and manufacturing level, equipment state, operation performance, maintenance requirements and the like. The vehicle is used as the most important device for urban rail transit operation, the vehicle is evaluated, the evaluation is not only one of means for guaranteeing the urban rail transit operation safety, but also the conditions of the reliability, the availability, the maintainability and the like of the wire-network vehicle can be reflected on the whole, and the vehicle evaluation method has important significance for the aspects of vehicle operation, maintenance and the like.
Currently, there are three more common methods for state assessment: firstly, establishing a failure physical model by using professional domain knowledge; secondly, analyzing and predicting based on data acquired by a sensor or a test; thirdly, the state is evaluated based on historical failure data, and the three methods are different in applicability. The urban rail transit vehicle is a complex mechanical system and an electric system, the vehicle state is influenced by a plurality of factors and is used as a complex dynamic system, and a failure physical model of the whole vehicle is difficult to obtain; therefore, the vehicle state is obtained mainly by monitoring or evaluating the state of a subsystem or a component in a vehicle system, but for the vehicle as a whole, the subsystem or the component cannot fully reflect the health state of the whole vehicle, and the evaluation of the whole vehicle state is still in an exploration stage at present.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a vehicle state evaluation method and system based on rail transit vehicle fault data.
The purpose of the invention can be realized by the following technical scheme:
a vehicle state evaluation method based on rail transit vehicle fault data comprises the following steps:
1) constructing a basic information base and a vehicle function structure of all vehicle types of the whole network;
2) constructing a fault library covering all vehicle types of the whole network;
3) acquiring historical fault data of the electric train, preprocessing the historical fault data, and counting the number of faults;
4) and constructing an electric train state evaluation model, and calculating by combining the fault frequency and the fault quantitative grade to obtain the vehicle overall state score of the electric train.
In the step 1), the basic information of the vehicle type included in the basic information base includes the vehicle type, the number of trains, the service life, the supplier, the overhaul history of the rack, the key technical parameters and the supplier information.
In the step 1), the vehicle functional structure is specifically a subsystem-secondary component-minimum replaceable unit three-level vehicle functional structure, and the subsystem, the secondary component and the minimum replaceable unit are respectively subjected to hierarchical coding for machine identification.
In the subsystem-secondary component-minimum replaceable unit three-level vehicle functional structure, an electric train is divided into 12 subsystems, namely a traction system, a brake system, a control system, a vehicle door, a bogie, an auxiliary power supply, a vehicle body, a vehicle coupler, an air conditioning system, an interface, passenger information and auxiliary functions.
And in the step 2), fault codes are compiled for each failure mode of each part based on a subsystem-secondary part-minimum replaceable unit three-level vehicle functional structure, and a fault library is constructed.
In the step 2), the fault types of different levels are quantized in the fault library, and the corresponding fault level quantization indexes are as follows:
first order fault F1: directly affect safety or cause system key function failure;
second order failure F2: the functional integrity of the system is influenced, the comfort is influenced, and redundancy or other emergency measures are provided to maintain operation for a period of time;
three-level fault F3: the fault has no safety influence and does not influence the operation;
four-stage fault F4: only affecting the beauty and not being urgent for immediate treatment.
In the step 4), the expression of the electric train state evaluation model is as follows:
Si＝(F1×n1+F2×n2+F3×n3+F4×n4)
wherein V is the score of the overall state of the vehicle, WkIs the normalized weight coefficient, w, of the subsystem k in the whole vehiclejIs the weight of subsystem j, wkIs the weight of the subsystem k, Sk(100)Scoring the status of subsystem k by percentage, SiIs the status score value, n, of subsystem i1-n4Respectively corresponding to four quantized fault levels F1-F4Millions of vehicle kilometers of faults within the evaluation period.
The weight of the subsystem is divided according to the importance degree of the subsystem, the importance degree of the subsystem comprises three levels of importance, importance and general importance, and different levels correspond to different weights.
The step 4) further comprises the following steps:
historical fault data and fault distribution of different lines, different vehicle types and different subsystems of the whole network are displayed, and state evaluation results of related electric trains and part information of abnormal fault frequency are displayed;
and for the abnormal frequency of the faults, if the fault-free working time or the fault-free operation mileage of the parts is obviously less than the average fault-free working time and the average fault-free operation mileage, alarming.
A vehicle condition assessment system based on rail transit vehicle fault data, the system comprising:
the vehicle basic information module is used for storing key basic information of the vehicle, including vehicle types, the number of attached trains, marshalling, a whole vehicle supplier, commissioning time, a shelf overhaul record, key technical parameters and key subsystem supplier information;
vehicle functional structure and fault library module: the system is used for establishing a subsystem-secondary component-minimum replaceable unit three-level vehicle functional structure and a fault library;
a data reading module: the method comprises the steps of reading information of vehicle parts with faults and fault types;
a data analysis module: the method is used for acquiring the fault distribution of the electric train and counting the fault frequency of the parts;
a vehicle state evaluation module: the system is used for evaluating the overall state of the vehicle according to the electric train state evaluation model;
an information display module: the device is used for displaying the vehicle type state evaluation result, the vehicle fault distribution condition and giving warning to the part with abnormal fault rate.
Compared with the prior art, the invention has the following advantages:
the vehicle fault database has important value on the operation and maintenance of the electric train, but the current database has huge information quantity and redundant information, so that the fault database is inconvenient to use and low in utilization rate, and vehicle faults can be classified and classified through the system, so that the effective management of vehicle fault historical data is realized.
The electric train state evaluation method established by the invention realizes objective scientific evaluation on each subsystem and each train type of the whole-line electric train, and provides support for operation and maintenance strategies of the electric train.
Thirdly, the system provides a convenient query function, and a user can quickly and effectively query the vehicle fault information through query conditions, so that the working efficiency of the electric train operation and maintenance personnel is improved.
The system provides a vehicle fault analysis function, and a user can not only inquire fault information, but also quickly obtain the fault distribution, the fault frequency of parts and key part information of abnormal fault rate and fault types of the electric train on different lines, different vehicle types and different subsystems.
Drawings
Fig. 1 is a functional block diagram of a system for evaluating a state of an electric train according to the present invention.
Fig. 2 is a flowchart of a method for evaluating a state of an electric train according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Examples
As shown in FIG. 1, the invention provides a vehicle state evaluation system based on rail transit vehicle fault data, which comprises a vehicle basic information module, a vehicle function structure and fault library module, a data reading module, a data analysis module, a vehicle state evaluation module and an information display module, wherein the main functions of the modules are as follows:
the data reading module reads fault data from an electric train historical fault database, the fault data, the vehicle basic information module, the vehicle function structure and the fault database module are used as input ends of the data analysis module, the vehicle state evaluation module uses data output by the data analysis module to grade vehicle states by using an electric train vehicle state evaluation method, and the information display module outputs various types of information of an electric train according to user query conditions.
As shown in fig. 2, the present invention provides a vehicle state evaluation method based on electric train fault data, comprising the steps of:
step 1, establishing a basic information base of the electric train. The ACCESS database management system is used for storing basic information of the full-wire-network electric train, wherein the basic information comprises information of vehicle types, the number of attached trains of different vehicle types, marshalling, vehicle suppliers, commissioning time, shelf overhaul histories, key technical parameters, key subsystem suppliers and the like.
And 2, establishing a subsystem-secondary component-minimum replaceable unit three-level vehicle functional structure of all vehicle types of the whole network based on the daily maintenance requirement of the electric train and by taking the minimum replaceable unit of the equipment as a principle, and coding the subsystem, the secondary component and the minimum replaceable unit so as to conveniently identify the machine.
For example, the whole electric train can be divided into 12 subsystems, namely a traction system (07), a brake system (06), a control system, a door (02), a bogie (04), an auxiliary power supply (08), a train body (01), a coupler (03), an air conditioning system (05), an interface (10), passenger information (14) and an auxiliary function (15). Taking a subsystem bogie (04) as an example, a second-stage part of the bogie comprises a framework (04-01), an elastic suspension device (04-02), a wheel-pair axle box device (04-03), a gear transmission device (04-04), a central traction device (04-05), a wheel rim lubricating device (04-06) and an obstacle detecting device (04-07), and a minimum replaceable unit of the elastic suspension device (04-02) of the second-stage part comprises a transverse shock absorber (04-020001), a first spring (04-020002), a first spring gasket (04-020003), a second spring (04-020004), an altitude valve (04-020005), a height compensating gasket (04-020006), an anti-side-rolling torsion bar (04-020007), an anti-side-rolling torsion bar joint bearing (04-020008), an anti-side-rolling torsion bar bearing positioning ring (04-020009), A vertical damper (04-020010).
And 3, establishing a fault library covering all vehicle types of the whole network according to the failure modes of the parts based on the functional structure of the electric train, wherein different failure modes of the same part correspond to different fault codes.
For example, for the smallest replaceable unit secondary spring of the bogie, the failure modes include air spring crack, air spring failure, air spring bulge, air spring leakage, emergency spring crack, emergency spring inclination, emergency spring failure and the like, and the fault codes corresponding to different failure modes are 191, 192, 636, 637, 352, 353 and 354 respectively.
And 4, reading the historical data of the vehicle faults from the historical fault database of the electric train, comparing the historical data with the minimum replaceable unit codes and the fault codes in the fault database established in the step 3, counting the data of different types of faults, and sending detailed information of the fault data to a fault analysis module.
Step 5, the fault analysis module carries out data preprocessing on historical fault data of the electric train, analyzes fault distribution conditions of the electric train on different lines, different vehicle types and different subsystems, counts fault frequency of parts, and determines key part information with high fault rate and fault types thereof, and the method mainly comprises the following steps:
step 5.1, data arrangement: the fault data of the electric train are sorted, and redundant and invalid data are removed;
step 5.2, normalization treatment: because the number of attached trains of different vehicle types is large in difference, and the operation mileage and the fault data amount have a direct relation, in order to objectively evaluate the state of the electric train, the number of trains and the operation mileage need to be considered, the fault data is normalized, the error of a data analysis result is reduced, and the objectivity of a vehicle state evaluation result is ensured.
The total number of faults is 'one', and the travel mileage unit is 'ten thousands of kilometers'.
And 5.3, counting the integral fault conditions of the whole network, each line, each vehicle type and each subsystem, analyzing the fault data of the electric trains of the whole network, different lines, different vehicle types and different subsystems, counting the fault data and fault trends of the electric trains of the whole network, different lines and different vehicle types, comparing the fault data of the electric trains of different lines and different vehicle types with the mean value of the whole network, and analyzing the state conditions of different lines, vehicle types and subsystems.
And 5.4, acquiring the fault distribution of the electric train according to the three-level vehicle function structure established in the step 2.
For example, according to the fault data of 2019 years, the fault number ratio of each vehicle subsystem is analyzed, Passenger Information (PIS) is the highest fault number ratio, and the fault number ratio is as high as 23.79%; the fault percentage of the air conditioner, the bogie and the vehicle door is more than 10 percent; traction, braking and control system faults are ratioed; the number of failures of the coupler and interface system is minimized. Further analysis is carried out on the fault distribution of the subsystem, and by taking the PIS as an example, the highest fault quantity of the video monitoring system, the second fault quantity of the broadcasting system and the minimum fault quantity of the media playing system in the PIS system in 2019 can be obtained.
Step 5.5, fault abnormity alarming: and calculating the fault-free working time or fault-free operation mileage of the key components, and alarming the components which are obviously less than the average fault-free working time and the average fault-free operation mileage.
Step 6, establishing an electric train state evaluation model, evaluating the overall states of different vehicle types and subsystems, and mainly comprising the following steps of:
step 6.1, dividing the electric train fault grade into four grades according to the fault influence degree, wherein the four grades are respectively as follows:
one type of failure: directly affect safety or cause system key function failure; for example: cab windshield breakage, bolster cracking, speedometer damage, cut-out device malfunction, door leaf damage, gearbox cracking, unit brake damage, brake control unit EPAC brake force loss, brake unrelaxed, and the like.
Two types of faults: the functional integrity of the system is influenced, the comfort is influenced, and redundancy or other emergency measures are provided to maintain operation for a period of time; for example: the automobile interior equipment cabinet is damaged, a side wall protection plate is worn, mechanical parts of the window wiper are aged, a door closing button is damaged, oil leakage of a transverse shock absorber is caused, axle box cracks are caused, a torsion bar knuckle bearing ball hinge is damaged, contact failure of an air compressor contactor is caused, and the like.
Three types of faults: the fault has no safety influence and does not influence the operation; for example: the floor is damaged, the upright post and the handrail are damaged, accessories of equipment cabinets in the car are damaged, sealing brushes on door leaves are deformed, wheels are scratched and the like.
Four types of faults: only affecting the beauty and not being urgent for immediate treatment. For example: various marks are lost, water enters the laminated glass, the illuminating lamp is damaged, paint falls off, the seat cover is damaged, the parallelism of the door leaf is out of tolerance, and the like.
And 6.2, dividing the electric train into 12 subsystems, namely a traction system, a braking system, a control system, a vehicle door, a bogie, auxiliary power supply, a vehicle body, a vehicle coupler, an air conditioning system, an interface, passenger information and auxiliary functions.
And 6.3, quantizing the subsystem weight. Defining the vehicle state of the electric train as S, and defining the state scores of 12 subsystems of the electric train as S1-S12. Because the importance degrees of different subsystems of the vehicle are different, the subsystems are divided into three levels of very important, important and general, and the three levels are endowed with different weight values w, namely the subsystem S1-S12The corresponding weights are w1-w12。
And 6.4, normalizing the weight of the subsystem. Normalization weight coefficient W of kth subsystem in whole vehiclekObtained according to the following formula:
wherein, wkTaking the weight value of the subsystem k, WkAnd the weight coefficient is the normalized weight coefficient of the subsystem k in the whole vehicle.
Step 6.5, fault grade quantification: quantifying the fault types of different levels according to the fault types defined in the step 6.1, wherein the quantitative indexes corresponding to the four fault types are defined as F1-F4。
Step 6.6, subsystem state scoring: state score value S of subsystemiObtained by the following formula:
Si＝(Fi×n1+F2×n2+F3×n3+F4×n4)
wherein n is1-n4To a fault class F1-F4"million car kilometer failures" within an evaluation period.
In order to facilitate overall evaluation of the vehicle model, a percentile system is used for evaluation of the subsystem. State score value S at subsystemiOn the basis ofObtaining the kth subsystem state percentile score S by using a linear difference methodk(100)。
Step 6.7, scoring S in the subsystem by the vehicle overall state score Vk(100)Sum subsystem normalization weight WkObtained according to the following formula:
and 7, a user can check historical fault data and fault distribution of different lines, different vehicle types and different subsystems of the whole network through the information display module, and call the state evaluation result of the relevant electric train and the information of the parts with abnormal fault frequency.
The above description is only a preferred embodiment of the present invention and should not be taken as limiting the invention, and any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A vehicle state evaluation method based on rail transit vehicle fault data is characterized by comprising the following steps:
1) constructing a basic information base and a vehicle function structure of all vehicle types of the whole network;
2) constructing a fault library covering all vehicle types of the whole network;
3) acquiring historical fault data of the electric train, preprocessing the historical fault data, and counting the number of faults;
4) and constructing an electric train state evaluation model, and calculating by combining the fault frequency and the fault quantitative grade to obtain the vehicle overall state score of the electric train.
2. The method as claimed in claim 1, wherein the basic information base includes basic information of vehicle type including vehicle type, train number, service life, supplier, overhaul history, key technical parameters and supplier information in step 1).
3. The method for evaluating the vehicle state based on the rail transit vehicle fault data as claimed in claim 1, wherein in the step 1), the vehicle function structure is a subsystem-secondary component-minimum replaceable unit three-level vehicle function structure, and the subsystem, the secondary component and the minimum replaceable unit are respectively encoded in a hierarchical manner for machine identification.
4. The method for evaluating the vehicle state based on the fault data of the rail transit vehicle as claimed in claim 3, wherein in the subsystem-secondary component-minimum replaceable unit three-level vehicle function structure, the electric train is divided into 12 subsystems, which are respectively a traction system, a brake system, a control system, a door, a bogie, an auxiliary power supply, a vehicle body, a coupler, an air conditioning system, an interface, passenger information and auxiliary functions.
5. The method for evaluating the vehicle state based on the rail transit vehicle fault data as claimed in claim 3, wherein in the step 2), fault codes are compiled for each failure mode of each part based on a subsystem-secondary part-minimum replaceable unit three-level vehicle functional structure, so as to construct a fault library.
6. The rail transit vehicle fault data-based vehicle state evaluation method according to claim 5, wherein in the step 2), fault types of different levels are quantified in a fault library, and corresponding fault level quantification indexes are as follows:
first order fault F1: directly affect safety or cause system key function failure;
second order failure F2: the functional integrity of the system is influenced, the comfort is influenced, and redundancy or other emergency measures are provided to maintain operation for a period of time;
three-level fault F3: the fault has no safety influence and does not influence the operation;
four-stage fault F4: only affecting the beauty and not being urgent for immediate treatment.
7. The method for evaluating the vehicle state based on the rail transit vehicle fault data as claimed in claim 1, wherein in the step 4), the expression of the electric train state evaluation model is as follows:
Si＝(F1×n1+F2×n2+F3×n3+F4×n4)
wherein V is the score of the overall state of the vehicle, WkIs the normalized weight coefficient, w, of the subsystem k in the whole vehiclejIs the weight of subsystem j, wkIs the weight of the subsystem k, Sk(100)Scoring the status of subsystem k by percentage, SiIs the status score value, n, of subsystem i1-n4Respectively corresponding to four quantized fault levels F1-F4Millions of vehicle kilometers of faults within the evaluation period.
8. The method as claimed in claim 7, wherein the weight of the subsystem is divided according to the importance degree of the subsystem, the importance degree of the subsystem includes three levels of importance, importance and general importance, and different levels correspond to different weights.
9. The method for evaluating the vehicle state based on the rail transit vehicle fault data as claimed in claim 1, wherein the step 4) further comprises:
historical fault data and fault distribution of different lines, different vehicle types and different subsystems of the whole network are displayed, and state evaluation results of related electric trains and part information of abnormal fault frequency are displayed;
and for the abnormal frequency of the faults, if the fault-free working time or the fault-free operation mileage of the parts is obviously less than the average fault-free working time and the average fault-free operation mileage, alarming.
10. A vehicle condition assessment system based on rail transit vehicle fault data, the system comprising:
the vehicle basic information module is used for storing key basic information of the vehicle, including vehicle types, the number of attached trains, marshalling, a whole vehicle supplier, commissioning time, a shelf overhaul record, key technical parameters and key subsystem supplier information;
vehicle functional structure and fault library module: the system is used for establishing a subsystem-secondary component-minimum replaceable unit three-level vehicle functional structure and a fault library;
a data reading module: the method comprises the steps of reading information of vehicle parts with faults and fault types;
a data analysis module: the method is used for acquiring the fault distribution of the electric train and counting the fault frequency of the parts;
a vehicle state evaluation module: the system is used for evaluating the overall state of the vehicle according to the electric train state evaluation model;
an information display module: the device is used for displaying the vehicle type state evaluation result, the vehicle fault distribution condition and giving warning to the part with abnormal fault rate.
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