CN109978345A - A kind of bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity - Google Patents
A kind of bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity Download PDFInfo
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Abstract
The present invention provides a kind of bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity, this method is opened a way to bullet train traction invertor IGBT and is analyzed with the velocity sensor gain coefficient failure chain less than normal for leading to traction motor failure jointly, mathematical modeling is carried out using failure mechanism, the curve that traction motor failure rate changes with tan δ is obtained, the combined failure Risk Chain of the amount characterized by " IGBT junction temperature liter " and " motor stator temperature " is established.Simultaneously, the analysis of risk chain is extended into specific route scene, in risk schedule assessment, risk schedule is decomposed with fault tree analysis process, and establish the appraisement system to transport O&M as major consideration, grey cluster processing is carried out to indices value with whitened weight function, risk analysis has been carried out to the risk caused by combined failure and has respectively obtained its risk class, has provided theoretical foundation for the formulation and execution of emergency measure.
Description
Technical field
The invention belongs to bullet train risk analysis technical field, in particular to a kind of bullet train based on characteristic quantity
Trailer system combined failure dynamic risk analysis method.
Background technique
Chinese Rail Transit System has been achieved for huge progress and critical breakthrough by the development of many years.It is high
The development of fast railway and bullet train, also brings new safety problem and challenge, and these problems have caused great attention.According to
China Academy of Railways Sciences statistics, the total accident number of the accident Zhan as caused by bullet train trailer system risk or failure
20% or so, in occupation of higher specific gravity.Trailer system is the core that bullet train generated and transmitted power, if led
Draw system jam and will will lead to train and lose tractive force, driver must stop immediately.This can directly result in Train delay,
Delay, and then upset transport order and transport project, if long period or large area is caused to be delayed, transport capacity band can be given
Compare heavy losses, if reply is improper, it is also possible to cause serious safety accident, jeopardize the person and property safety.
The power core of bullet train is trailer system, and safety and reliability directly affects vehicle, personnel safety
And the capacity of entire road network.Zhu Lin arranges CRH2 type high speed in " research of CRH2 EMUs Electric Traction Drive System "
The structure of vehicle trailer system is systematically introduced with working mechanism.Cui Xiuguo is " CRH3 type EMU electrical system is reliable
Journal of Sex Research " in fail-safe analysis has been carried out to CRH3 type bullet train trailer system, obtain rapid wear device in trailer system and
Weak link.Wherein, power device insulated gate bipolar transistor (IGBT) has higher failure rate in three-level inverter,
This significantly improves the failure rate of trailer system.Jin Linqiang is in " diagnosis of bullet train trailer system inverter combined failure "
In using CRH2 EMUs trailer system three-level inverter as research object, describe the various faults type and mistake of IGBT
Imitate mechanism.When IGBT breaks down, risk will be propagated in trailer system, and whole system will be transported in " inferior health "
Row state.Furthermore the also failure frequent occurrence of the velocity sensor in trailer system, this will lead to train misoperation, or even hair
The burst accidents such as raw parking.The prior art, which also develops to the failure mechanism of velocity sensor and propagation, to be emulated.And IGBT
Be not easy to be found at failure initial stage with combined failure caused by velocity sensor, with failure in trailer system drilling gradually
Change and propagate, finally will lead to the adverse consequences such as motor is burnt, withdrawal of train even derails.
Weight of the velocity sensor of IGBT and traction electric machine in three-phase traction inverter as bullet train trailer system
Equipment is wanted, because its working environment is severe, failure frequent occurrence.The two once breaks down simultaneously, will cause entire traction system
The tractive force of system reduces, and speed reduces, and traction electric machine stator and rotor electric current increases, and long-play can make traction electric machine liter
Temperature will lead to traction electric machine and burn when serious, for this process also with the pulsation of stator and rotor electric current, it is acute that this will be such that motor occurs
Violent shock is dynamic, can also train be caused to derail when road conditions are severe.
Such combined failure has a complex characteristics such as coupling, ambiguity, transitivity, the risk being induced by it often wave
And entire train system, caused by consequence may be extremely serious and be not easy to quantify.
It is each to people's lives, life, property etc. after risk analysis assessment refers to that preceding or generation occurs for consequential event
The work that influence and loss caused by aspect are quantified.Liu Yanqiong etc. is " theory of risk assessment method and both at home and abroad research are existing
Shape commentary " in summarize most common nine kinds of theoretical methods in domestic and international risk assessment, and application field to method and excellent
It is bad to be summarized.Qin Yong etc. is High Speed Train in China in " research of bullet train system security reliability analyzing evaluation method "
Propose the system security reliability analysis method system and estimation flow of complete set.Bullet train trailer system is very multiple
Miscellaneous, failure is often associated with the variation of many intermediate features amounts (such as electric current, voltage and temperature) during propagation, existing
Some is unable to satisfy the requirement of " quick " and " real-time " based on the static risk analysis assessment of historical data, thus needs to grind
Study carefully the dynamic risk analysis appraisal procedure based on real-time characteristic amount.Zhou Donghua etc. " assessment of the reliability in time of engineering system with
Predicting Technique " in review engineering system reliability in time assessment and prediction technique.Li Hui etc. " is being based on temperature profile amount
Wind turbines critical component deteriorate gradual change probability analysis " in using Wind turbines as research object, propose based on temperature profile
The Wind turbines critical component of amount deteriorates gradual change probability analysis method.Sun Yuanzhang etc. is in " the power train based on real-time running state
Unite operation reliability evaluation " in by taking electric system as an example, analyze the real-time characteristics such as Line Flow amount to element outage probability
Influence, establish the reliability model of unit of the real-time operating condition based on characteristic quantity.
Existing literature is more for the mechanism study of bullet train trailer system ordinary failures, but draws in bullet train
Combined failure happens occasionally in the actual motion of system, and the research propagated of developing for combined failure mechanism and risk is less,
In addition, bullet train trailer system as one of subsystem important in bullet train, real time security is required it is very high,
Existing static risk analysis assessment cannot achieve real-time risk analysis assessment.Combined failure once occurs, just must be to event
Barrier train and repairs and safeguards, this will directly affect the transport and capacity of the railway system, but the wind of existing static state
Danger analysis assessment, few researchs will transport the factors such as O&M and are included in risk analysis chain.
Summary of the invention
In order to solve the problems in the existing technology, the present invention provides a kind of bullet trains based on characteristic quantity to lead
Draw system combined failure dynamic risk analysis method, this method set up in contact net system critical component probability of malfunction about
The function of characteristic quantity obtains the real-time risk level of system by the failure mechanism during Risk of Communication, so as to basis
The variation of characteristic quantity compares to take appropriate measures suitably to propagate when the dependent thresholds and actual motion of setting
Risk of Communication chain is blocked in link, and major accident caused by being influenced by contact net by weather is avoided to occur.
Specific technical solution of the present invention is as follows:
The present invention provides a kind of bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity,
This method comprises the following steps:
S1: the combined failure Risk Chain of building bullet train trailer system, based on the characteristic quantity in combined failure Risk Chain
Seek combined failure rate P；
S2: i-th consequential event in the n consequential event as caused by combined failure is calculated according to combined failure rate and is occurred
Probability Fi, form consequential event probability of happening vector shown in formula (1)
F=(F1,F2,…,Fi,…,Fn) (1)
S3: consequence of i-th of consequential event under grey cluster in the n consequential event as caused by combined failure is calculated
Severity Si, form sequence severity vector shown in formula (2)
S=(S1,S2,…,Si,…,Sn) (2)
S4: total sequence severity R of combined failure Risk Chain is calculated according to formula (3)
S5: bullet train trailer system combined failure dynamic risk is analyzed according to total sequence severity R.
Further to improve, combined failure rate P described in step S1 is calculated by formula (4) and is obtained:
P=λ (tan δ) * λIt is compound(ΔT) (4)
In formula, Δ T indicates IGBT junction temperature liter, λIt is compound(Δ T) indicates the raised failure rate of traction electric machine temperature anomaly, λ
(tan δ) indicates traction motor failure rate.
It is further to improve, λIt is compound(Δ T) is calculated by formula (5) and is obtained:
λIt is compound(Δ T)=λIGBT(ΔT)·λSensor (5)
In formula, λSensorIndicate that failure rate less than normal, λ occur for sensor gain coefficientIGBT(Δ T) indicates IGBT crash rate.
Further to improve, λ (tan δ) is calculated by formula (6):
It is further to improve, probability F in step S2iIt is calculated according to formula (7):
Fi=Gi×P (7)
In formula, GiIndicate the product for each probability of happening for causing i-th of consequential event to occur.
It is further to improve, step S3 method particularly includes:
S31: building bullet train trailer system combined failure risk schedule evaluation index system
S32: m first class index value x of i-th of consequential event is calculatedimAnd establish commenting for bullet train risk analysis assessment
Valence matrix Xi, as shown in formula (8)
Xi=(xi1 xi2 … xim) (8)；
S33: the whitened weight function f of each first class index is constructedq(x), as follows:
fqIt (x) is power that x belongs to q class evaluation criteria, A, B, C, D representative function threshold value；
S34: the q class Grey System for calculating p-th of index of i-th of consequential event counts pi,pqAnd its grey weight
ri,pq, as shown in formula (9) and (10)
pi,pq=fq(xip) (9)
In formula, k is to assess grey class number；
S35: building is by i-th of consequential event, the grey weight r of m first class indexi,pqThe assessment weight matrix of composition, such as
Shown in formula (11):
S36: risk assessment of i-th of consequential event under grey cluster is obtained according to evaluation vector K and assessment weight matrix
Value, as shown in formula (12):
Bi=KRi(12)；
S37: sequence severity S of i-th of consequential event under grey cluster is calculated according to formula (13)i,
Si=WiBi (13)
In formula, WiIndicate i-th of first class index for the weight of overall risk degree；
S38: sequence severity vector shown in formula (2) is formed
S=(S1,S2,…,Si,…,Sn) (2)。
Bullet train trailer system combined failure dynamic risk analysis method provided by the invention based on characteristic quantity is to height
Fast train traction inverter IGBT open circuit and this event less than normal for leading to traction motor failure jointly of velocity sensor gain coefficient
Barrier chain is analyzed, and carries out mathematical modeling to it using failure mechanism, has obtained " IGBT knot with reference to existing experimental result
Temperature rise-combined failure incidence " relation curve and " stator temperature and stator electromagnet line dielectric loss angle tangent tan δ " are closed
It is curve, finally obtains the curve that traction motor failure rate changes with tan δ, establishes with " IGBT junction temperature liter " and " motor is fixed
The failure rate model of the combined failure of the sub- temperature " amount of being characterized.Meanwhile the analysis of risk chain is extended into specific route field
Scape decomposes risk schedule with fault tree analysis process, and establish to transport O&M in risk schedule assessment
For the appraisement system of major consideration, grey cluster processing is carried out to indices value with whitened weight function, to by compound
The risk that failure causes has carried out risk analysis and has respectively obtained its risk class, mentions for the formulation and execution of emergency measure
Theoretical foundation is supplied.
Detailed description of the invention
Fig. 1 is the flow chart of the bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity；
Fig. 2 is bullet train traction invertor systematic functional structrue figure；
Fig. 3 is three level traction invertor main circuit diagram of CRH380D bullet train；
Fig. 4 is bullet train trailer system combined failure Risk Chain schematic diagram；
Fig. 5 is the extremely raised failure rate of motor stator temperature under the conditions of IGBT difference junction temperature rises；
Fig. 6 is traction electric machine electromagnetic wire tan δ TEMPERATURE SPECTROSCOPY under different ageing times；
Fig. 7 is temperature-time of measuring-tan δ relationship surface chart；
Fig. 8 is the curve graph that traction motor failure rate changes with tan δ；
Fig. 9 amount of being characterized and traction motor failure rate relational graph；
Figure 10 is that event tree structural schematic diagram occurs for bullet train trailer system combined failure；
Figure 11 is bullet train trailer system combined failure risk schedule evaluation index system schematic diagram.
The step of process of attached drawing illustrates can hold in a computer system such as a set of computer executable instructions
Row.It, in some cases, can be to be different from sequence execution herein although logical order is shown in flow charts
Described step.
Specific embodiment
Since method description of the invention realizes that the computer system, which can be set, to be taken in computer systems
In business device or the processor of client.Such as method described herein can be implemented as that software can be performed with control logic,
It is executed by the CPU in server.Function as described herein can be implemented as being stored in non-transitory tangible computer readable
Program instruction set in medium.When implemented in this fashion, which includes one group of instruction, when the group instructs
It promotes computer to execute the method that can implement above-mentioned function when being run by computer.Programmable logic can be temporarily or permanently
Ground is mounted in non-transitory visible computer readable medium, for example, ROM chip, computer storage, disk or
Other storage mediums.In addition to software come other than realizing, logic as described herein can use a point sharp component, integrated circuit, with
The programmable logic that programmable logic device (such as, field programmable gate array (FPGA) or microprocessor) is used in combination, or
Person includes any other equipment of their any combination to embody.All such implementations are each fallen within the scope of the present invention.
Embodiment 1
The embodiment of the present invention 1 provides a kind of bullet train trailer system combined failure dynamic risk based on characteristic quantity point
Analysis method, as shown in Figure 1, this method comprises the following steps:
S1: the combined failure Risk Chain of building bullet train trailer system, based on the characteristic quantity in combined failure Risk Chain
Seek combined failure rate P；
In step S1, when constructing combined failure Risk Chain, by taking CRH2 bullet train trailer system as an example, inversion is drawn
The functional structure chart of system is as shown in Fig. 2, the main circuit diagram of three level traction invertors passes through as shown in figure 3, by taking U phase as an example
Control T11, T12, T13, T14's cut-offs, and U phase output terminal is availableO andThe voltage of three kinds of level, wherein Ud
For DC voltage.U, V, W three-phase output can be with frequency synthesis, the adjustable AC sine wave of amplitude.
Based on combined failure risk chain structure constructed by the above bullet train trailer system as shown in figure 4, mechanism such as
Under:
By taking U phase as an example, when T12 IGBT junction temperature rise it is excessively high, will lead to IGBT open-circuit fault, inverter U phase is exported and will be lacked
Positive distribution channel is lost, the voltage positive half period of the phase is caused to lack, and IGBT and its corresponding afterflow two to T12 with bridge arm
Pole pipe does not break down, and the negative half-cycle distribution channel that inverter U phase exports is unaffected.Since U phase forward current is
Zero, it is distorted the electric current of remaining two-phase, harmonic wave increases, and causes the electromagnetic torque of traction electric machine to decline, and the period occur
Property pulsation, motor speed decline, so that traction electric machine is operated in abnormal state.And traction electric machine velocity sensor once occurs
Gain coefficient failure less than normal, measurement revolving speed will be less than actual speed, control system caused to generate accelerating torque, be added to traction electricity
Stator terminal voltage will increase on machine, and the operating condition amplificationization for running three-phase imbalance, stator and rotor electric current will be further increased, this
It will lead to traction electric machine stator and rotor temperature substantial increase, traction electric machine stator dielectric loss angle sine value increases, and may burn
Ruin motor.
Combined failure rate P is calculated by formula (4) and is obtained in step S1:
P=λ (tan δ) * λIt is compound(ΔT) (4)
Meaning represented by each parameter is as follows in formula (1):
1) in formula (1), Δ T indicates IGBT junction temperature liter.
2) in formula (1), λIt is compound(Δ T) indicates to be caused by IGBT open circuit and velocity sensor gain coefficient combined failure less than normal
The raised failure rate of traction electric machine temperature anomaly, by formula (5) calculate and obtain:
λIt is compound(Δ T)=λIGBT(ΔT)·λSensor (5)
In formula (2), λSensorIt indicating that failure rate less than normal occurs for sensor gain coefficient, is a constant, value is 7.66 ×
10-8。
In formula (2), λIGBT(Δ T) indicates IGBT crash rate, rises the functional relation such as formula between Δ T with IGBT junction temperature
(14) shown in:
λIGBT(Δ T)=2.995 × 10-7e0.09033ΔT (14)
In formula (14), IGBT junction temperature, which rises the functional relation between IGBT crash rate, to be obtained by the data fitting of table 1
's.
Cycle-index and IGBT crash rate of 1 IGBT of table under different junction temperatures liter
IGBT crash rate is calculated by formula (15) and is obtained:
λ (t)=Δ Nf(t)/Ns(t)·Δt (15)
In formula (15), λ (t) indicates crash rate；ΔNf(t) failure number (a) in the unit time is indicated； Ns(t) indicate single
Product number (a) is run in the time of position；Δ t indicates runing time (h).
It follows that formula (5) can be write as:
λIt is compound(Δ T)=λIGBT(ΔT)·λSensor=2.294 × 10-14e0.09033ΔT。
Relationship based on formula (5), between IGBT difference knot temperature condition and the extremely raised failure rate of motor stator temperature
As shown in Figure 5.
3) in formula (1), λ (tan δ) indicates traction motor failure rate.
Combined failure occurs the constant temperature that caused direct result is exactly traction electric machine stator winding insulation and rises,
The loss of these thermal energy is the dielectric dielectric loss often said.Dielectric dielectric loss and dielectric loss angle tangent
Direct proportionality between tan δ can study the overall performance of insulating materials by the changing rule of tan δ, such as insulate
Air blister defect in the ageing state of material, surface wetting or filthy situation, material, and these insulation defects can directly be led
It sends a telegraph machine burning and the adverse consequences such as ruins.Dielectric loss angle tangent can be used in power equipment preventive experiment to assess electricity
Solve the quality of matter insulation performance.According to rail traffic traction electric machine " temperature-dielectric loss " experimental result, as shown in table 2.
Traction electric machine electromagnetic wire tan δ value under the different ageing times of table 2, different temperatures
It can be fitted to obtain Fig. 6 and curve shown in Fig. 7 according to above-mentioned data.
According to standard " JB/T50132-1999 medium-sized high-pressure electrical machinery stator coil finished product product quality point etc. " electrical-coil
Dielectric loss Index grading is as shown in table 3.
3 motor stator coil dielectric loss Index grading of table
It follows that being unqualified, the traction electricity under normal operating condition when stator coil failure rate reaches 0.667
The failure rate of machine stator coil is 3.578 × 10-7, but in actual traction electric machine reliability data statistical work, do not press
According to the failure rate of the magnitude classification statistics traction electric machine of dielectric loss angle tangent, probability of malfunction and dielectric loss can not be obtained
The relational expression of angle tangent value.In order to improve the accuracy of traction motor failure rate calculating, traction motor failure of the invention
Rate λ (tan δ) is obtained by formula (6):
Traction motor failure rate is with the tan δ curve changed as shown in figure 8, as can be seen from the figure:
When tan δ is in " excellent ", " first-class " section, traction motor failure rate rises slower；
When tan δ is in " qualification " section, the failure rate of traction electric machine rises rapidly with dielectric loss angle tangent；
When tan δ is in " unqualified " section, it is considered as traction electric machine and has occurred and that failure.
The characteristic quantity constructed as a result, and traction motor failure rate relational graph are as shown in Figure 9.
S2: i-th consequential event in the n consequential event as caused by combined failure is calculated according to combined failure rate and is occurred
Probability Fi, form consequential event probability of happening vector shown in formula (1)
F=(F1,F2,…,Fi,…,Fn) (1)
In step S2, method particularly includes:
S21: decomposing risk schedule with Event Tree Analysis, is based on combined failure Risk Chain, and motor burns conduct
The combined failure of the primary event of event tree, probability of happening P, as the combined failure rate of step S1 meaning, building occurs
The structure chart of event tree is as shown in Figure 10.
In figure, the consequential event description of each branch of event tree is shown in Table 4.
The description of event tree consequence occurs for 4 bullet train trailer system combined failure of table
S22: by each probability of happening be calculated in n consequential event of generation i-th of consequential event occur it is general
Rate Fi, it is calculated by formula (7) and is obtained:
Fi=Gi×P (7)
In formula, GiIndicate the product for each probability of happening for causing i-th of consequential event to occur.
S23: forming the vector being made of the probability that n consequential event occurs, as shown in formula (1):
F=(F1,F2,…,Fi,…,Fn) (1)
And ∑ Fi=P.
S3: consequence of i-th of consequential event under grey cluster in the n consequential event as caused by combined failure is calculated
Severity Si, form sequence severity vector shown in formula (2)
S=(S1,S2,…,Si,…,Sn) (2)
Step S3 method particularly includes:
S31: building bullet train trailer system combined failure risk schedule evaluation index system, the evaluation index system
As shown in figure 11；
S32: m first class index value x of i-th of consequential event is calculatedimAnd establish commenting for bullet train risk analysis assessment
Valence matrix Xi, as shown in formula (8):
Xi=(xi1 xi2 … xim) (8)
In step S32, the calculation of each first class index value is as follows:
(1) capacity loss=parking vehicle transport power × idle time
(2) maintenance cost=car inspection and repair expense+line maintenance expense
(3) casualties=slight wound number × slight wound grading+severe injury number × severe injury grading+death toll × death is commented
Grade
(4) social influence=influence number × duration.
S33: the whitened weight function f of each first class index is constructedq(x), as shown in table 5:
5 four quasi-representative whitened weight function of table
In step S33, using whitened weight function data are converted with the influence for mainly eliminating subjective factor.Foundation
The practical problem of bullet train risk assessment is equipped with the grey class of k assessment, and since its higher loss of risk is bigger, and it increases
Gesture is exponential, therefore successively indicates degree of risk corresponding to index value size from light to heavy with 1,10,20,50,100, is formed
Evaluation vector K=[1,10,20,50,100] determines the k whitened weight function f for assessing grey classq(x), fqIt (x) is that x belongs to q
The power of class evaluation criteria, function threshold A, B, C, D are by four quasi-representative whitened weight functions corresponding grey number and mathematical expression and press
It is obtained according to bullet train operation experience.
S34: the q class Grey System for calculating p-th of index of i-th of consequential event counts pi,pqAnd its grey weight
ri,pq, as shown in formula (9) and (10)
pi,pq=fq(xip) (9)
In formula, k is to assess grey class number；
S35: building is by i-th of consequential event, the grey weight r of m first class indexi,pqThe assessment weight matrix of composition, such as
Shown in formula (11):
S36: risk assessment of i-th of consequential event under grey cluster is obtained according to evaluation vector K and assessment weight matrix
Value, as shown in formula (12):
Bi=KRi (12)
S37: sequence severity S of i-th of consequential event under grey cluster is calculated according to formula (13)i
Si=WiBi (13)
In formula, WiIndicate i-th of first class index for the weight of overall risk degree；
In step S37, the calculation method of weight is as follows:
Indexs at different levels obtained shown in formula (16) two-by-two relatively and using 1-9 scale based on expertise
Evaluations matrix:
It is calculated again by the analytic hierarchy process (AHP) software Yaahp of profession, to obtain each index for overall risk degree
Weight Wi。
S38: sequence severity vector shown in formula (2) is formed
S=(S1,S2,…,Si,…,Sn) (2)；
S4: total sequence severity R of combined failure Risk Chain is calculated according to formula (3)
S5: bullet train trailer system combined failure dynamic risk is analyzed according to total sequence severity R, the General Logistics Department
Fruit severity and combined failure dynamic risk grade are as shown in table 6:
The total sequence severity of table 6 and combined failure dynamic risk grade corresponding relationship
Embodiment 2
Risk analysis of cases, operation column are carried out using in November, 2017 " Chengdu-Chongqing Line for Passenger Transportation " actual motion route as background
Vehicle model CRH380D, 556 people of train seating capacity, by the marshalling of every train number 16, totally 1000 people are appraised and decided.
Risk case concrete condition is as follows: 14:59 is left for the G8713 train at Chongqing northern station, Yu Zizhong by Chengdu eastern station
Northern station to inland river northern station section measures IGBT junction temperature and is upgraded to 100 DEG C, the corresponding raised failure rate λ of traction electric machine temperature anomalyIt is compound(Δ
T)=2.294 × 10-14e0.09033*100=1.9212 × 10-10, traction electric machine stator temperature is about 120 DEG C, the duration 90
Minute, δ=2.3 corresponding dielectric loss angle tangent tan, traction motor failure rate λ (tan δ)=1.919 × 10- 13e9.626*2.3=7.9117 × 10-4, so far, combined failure rate is P=λ (tan δ) * λIt is compound(Δ T)=1.9212 × 10-10×
7.9117×10-4=1.5215 × 10-13。
According to the event tree that Fig. 9 is established, according to expertise, motor probability on fire is set as 30%, is found in time
The probability of fire is 60%, and the probability of bearing breaking is 20%, finds that the probability of bearing breaking is 80% in time, derailing thing occurs
Therefore probability be 60%, compared with the probability having some casualties in small fire be 30%, be compared with the probability having some casualties in conflagration
80%, the probability having some casualties in derailment accident is 99%, is thus calculated
F1=G1× P=30% × 60% × 30% × 1.5215 × 10-13=8.21 × 10-15
F2=G2× P=30% × 60% × 70% × 1.5215 × 10-13=1.92 × 10-14
F3=G3× P=30% × 40% × 80% × 1.5215 × 10-13=1.46 × 10-14
F4=G4× P=30% × 40% × 20% × 1.5215 × 10-13=3.65 × 10-15
F5=G5× P=70% × 20% × 80% × 1.5215 × 10-13=1.704 × 10-14
F6=G6× P=70% × 20% × 20% × 60% × 99% × 1.5215 × 10-13=2.53 × 10-15
F7=G7× P=70% × 20% × 20% × 60% × 1% × 1.5215 × 10-13=2.556 × 10-17
F8=G8× P=70% × 20% × 20% × 40% × 1.5215 × 10-13=1.7 × 10-15
F9=G9× P=70% × 80%1.5215 × 10-13=8.52 × 10-14
Obtain consequential event probability of happening vector
F=(8.21 × 10-15, 1.92 × 10-14, 1.46 × 10-14, 3.65 × 10-15, 1.704 × 10-14, 2.53 ×
10-15, 2.556 × 10-17, 1.7 × 10-15, 8.52 × 10-14)
According to the risk analysis evaluation system established in Figure 10, the case is determined in conjunction with the above failure scenario and empirical data
Each two-level index value of example, as shown in table 7.
Each consequential event of table 7 corresponds to two-level index value
According to the calculation of each first class index, each first class index shown in table 8 is calculated in data substitution in table 7
Value.
Each consequential event of table 8 corresponds to first class index value
The whitened weight function (indicating with grey number) of each first class index is constructed by expertise statistics, wherein k=5, such as
Shown in table 9.
Each index whitened weight function of table 9
According to each consequential event in table 8, following sample matrix can be obtained:
X1=[36 80 55 21], X2=[36 80 0 2.5], X3=[48 120 120 50] X4=[48 120 0
21], X5=[24 60 0 1.5], X6=[72 150 350 600], X7=[72 150 0 300], X8=[24 60 0
1.5], X9=[24 60 0 1.5]
X is obtained by the whitened weight function of table 9ijBelong to the power f of q class evaluation criteriaq(xij), and counted by formula (9), (10)
Grey System counting and grey weight are calculated, and then obtains assessment weight matrix are as follows:
Above data is substituted into formula (12), can be obtained:
B1=(20 20 35 5.95), B2=(20 20 1 1), B3=(50 50 100 100), B4=(50 50 1
5.95),B5=(50 50 1 1), B6=(100 75 100 100), B7=(100 75 1 100), B8=(10 10 1
1),B9=(10 10 1 1).
Sequence severity of each consequential event under risk grey cluster is obtained by formula (13) are as follows:
S1=22.966, S2=5.94, S3=87,
S4=15.126, S5=3.34, S6=97.5,
S7=51.96, S8=3.34, S9=3.34
Write as matrix form are as follows: S=[22.966,5.94,87,15.126,3.34,97.5,51.96.3.34,3.34]
Calculate the risk schedule of each consequential event:
R1=F1×S1=8.21 × 10-15× 22.966=1.89 × 10-13
R2=F2×S2=1.92 × 10-14× 5.94=1.14 × 10-13
R3=F3×S3=1.46 × 10-14× 87=12.7 × 10-13
R4=F4×S4=3.65 × 10-15× 15.126=0.55 × 10-13
R5=F5×S5=1.704 × 10-14× 3.34=1.56 × 10-13
R6=F6×S6=2.53 × 10-15× 97.5=2.47 × 10-13
R7=F7×S7=2.556 × 10-17× 51.96=0.013 × 10-13
R8=F28×S8=1.7 × 10-15× 3.34=0.057 × 10-13
R9=F9×S9=8.52 × 10-14× 3.34=2.8 × 10-13
Overall risk consequence R=R1+R2+R3+R4+R5+R6+R7+R8+R9=2.22 × 10-12
According to table 6, thus risk caused by combined failure belongs to III level risk.
In risk assessment, the risk situation which occurs for different periods, road conditions and train number is different,
The corresponding risk class of different consequential events is also different, should take at emergency measure corresponding with its risk class
It sets, the manpower and material resources in emergency disposal can be saved.
Claims (6)
1. a kind of bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity, which is characterized in that institute
The method of stating includes the following steps:
S1: the combined failure Risk Chain of building bullet train trailer system is sought based on the characteristic quantity in combined failure Risk Chain
Combined failure rate P；
S2: the probability that i-th of consequential event occurs in the n consequential event as caused by combined failure is calculated according to combined failure rate
Fi, form consequential event probability of happening vector shown in formula (1)
F=(F1, F2..., Fi..., Fn) (1)
S3: sequence severity of i-th of consequential event under grey cluster in the n consequential event as caused by combined failure is calculated
Si, form sequence severity vector shown in formula (2)
S=(S1, S2..., Si..., Sn) (2)
S4: total sequence severity R of combined failure Risk Chain is calculated according to formula (3)
S5: bullet train trailer system combined failure dynamic risk is analyzed according to total sequence severity R.
2. the bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity as described in claim 1,
It is characterized in that, combined failure rate P described in step S1 is calculated by formula (4) and is obtained:
P=λ (tan δ) * λIt is compound(ΔT) (4)
In formula, Δ T indicates IGBT junction temperature liter, λIt is compound(Δ T) indicates the raised failure rate of traction electric machine temperature anomaly, λ (tan δ)
Indicate traction motor failure rate.
3. the bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity as claimed in claim 2,
It is characterized in that, λIt is compound(Δ T) is calculated by formula (5) and is obtained:
λIt is compound(Δ T)=λIGBT(ΔT)·λSensor (5)
In formula, λSensorIndicate that failure rate less than normal, λ occur for sensor gain coefficientIGBT(Δ T) indicates IGBT crash rate.
4. the bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity as claimed in claim 2,
It is characterized in that, λ (tan δ) is calculated by formula (6):
。
5. the bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity as claimed in claim 3,
It is characterized in that, probability F in step S2iIt is calculated according to formula (7):
Fi=Gi×P (7)
In formula, GiIndicate the product for each probability of happening for causing i-th of consequential event to occur.
6. the bullet train trailer system combined failure dynamic risk analysis method based on characteristic quantity as described in claim 1,
It is characterized in that, step S3 method particularly includes:
S31: building bullet train trailer system combined failure risk schedule evaluation index system；
S32: m first class index value x of i-th of consequential event is calculatedimAnd establish the evaluation square of bullet train risk analysis assessment
Battle array Xi, as shown in formula (8)
Xi=(xi1 xi2 ... xim) (8)；
S33: the whitened weight function f of each first class index is constructedq(x), as follows:
fqIt (x) is power that x belongs to q class evaluation criteria, A, B, C, D representative function threshold value；
S34: the q class Grey System for calculating p-th of index of i-th of consequential event counts PI, pqAnd its grey weight rI, pq, such as formula
(9) and shown in (10)
PI, pq=fq(xip) (9)
In formula, k is to assess grey class number；
S35: building is by i-th of consequential event, the grey weight r of m first class indexI, pqThe assessment weight matrix of composition, such as formula (11)
It is shown:
S36: risk assessment value of i-th of consequential event under grey cluster is obtained according to evaluation vector K and assessment weight matrix, such as
Shown in formula (12):
Bi=KRi(12)；
S37: sequence severity S of i-th of consequential event under grey cluster is calculated according to formula (13)i,
Si=WiBi (13)
In formula, WiIndicate i-th of first class index for the weight of overall risk degree；
S38: sequence severity vector shown in formula (2) is formed
S=(S1, S2..., Si..., Sn) (2)。
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