CN110309550A - A kind of bullet train systems reliability analysis method based on potential energy field and network efficiency - Google Patents
A kind of bullet train systems reliability analysis method based on potential energy field and network efficiency Download PDFInfo
- Publication number
- CN110309550A CN110309550A CN201910495102.8A CN201910495102A CN110309550A CN 110309550 A CN110309550 A CN 110309550A CN 201910495102 A CN201910495102 A CN 201910495102A CN 110309550 A CN110309550 A CN 110309550A
- Authority
- CN
- China
- Prior art keywords
- bullet train
- node
- train system
- failure
- component
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/13—Architectural design, e.g. computer-aided architectural design [CAAD] related to design of buildings, bridges, landscapes, production plants or roads
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Architecture (AREA)
- Civil Engineering (AREA)
- Structural Engineering (AREA)
- Test And Diagnosis Of Digital Computers (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
The bullet train systems reliability analysis method based on potential energy field and network efficiency that the present invention provides a kind of, specific step is as follows for this method: first, bullet train system topology feature is analyzed, and bullet train grid model is established based on Complex Networks Theory；Secondly, based on bullet train complex network model and potential energy field theory, the entire dynamic process that the analysis bullet train system failure is propagated obtains the every step of the system failure and propagates inoperative component；Finally, being based on network efficiency index of correlation dynamic analysis bullet train system reliability on the basis of the bullet train system failure is propagated.The indexs of correlation such as present invention combination train system fault propagation and grid efficiency analyze bullet train system reliability, can dynamic analysis bullet train system reliability changing rule gradually, provide theories integration for operation and maintenance personnel's emphasis maintenance task.
Description
Technical field
The present invention relates to bullet train systems reliability analysis fields, are imitated more particularly, to one kind based on potential energy field and network
The method of the bullet train systems reliability analysis of rate.
Background technique
High speed rail system, which comes up to China's socio-economic development, international community, plays irreplaceable branch of overall importance
Support effect, by the end of the end of the year 2017, China's high-speed rail operating mileage forms the high speed of maximum-norm in the world up to 2.5 ten thousand kilometers
The railway network, for EMU online operation up to 2522 groups, year sends 17.13 hundred million people of passenger, daily starts motor-car during summer transportation in 2017
Group is 4761 column；Chinese Industrial Standards (CIS) EMU " recovery number " realizes 350 kilometers of commercial operations of speed per hour, sets up world's high-speed rail construction fortune
The new mark post of battalion.External rail traffic developed country also payes attention to the development of high speed rail system energetically, wherein European high-speed railway
About 1.2 ten thousand kilometers of operating mileage, Japan has started to build speed per hour up to 500 kilometers of magnetic-suspension high-speed railway, and the U.S. even proposes
Develop the super high-speed railways that speed per hour is up to 1200 kilometers.
Along with the fast development of high-speed rail technology in world wide, the technological maheup complexity of bullet train is more and more
Height, different sub-systems, components are a up to more than 40,000 and have the stronger interactively that interdepends, and are typical complicated machines
The big system of tool electronic information.Bullet train complicated, electromechanical integration high-tech system as one, pedigree it is reliable
Journal of Sex Research work is very necessary.
The method of bullet train systems reliability analysis at present includes failure mode and impact analysis (Failure Mode and
EffectAnalysis, FMEA), Petri net model, fault tree (Fault TreeAnalysis, FTA) model, Bayesian network
Network (Bayesian network, BN) model etc., these methods in bullet train and its critical system fail-safe analysis
Using.But these above-mentioned methods largely combine historical failure data and expertise, and with a certain risk case or event
Fail-safe analysis is carried out based on barrier mode.Wherein artificial subjective factor is affected, and ignores system global feature, can lead
It causes certain error to generate, influences the correctness of result.Therefore, scholars begin trying using Complex Networks Theory analysis high speed
Train reliability.Wherein, based on complex network structures feature, relevant network topology characteristic index is established, it can be preferably
Bullet train system structure is analyzed to system reliability influence degree, and then carries out subsequent fail-safe analysis work.However, this
The key point of a little network-based analysis method for reliability concentrates on the final result of systems reliability analysis, and ignores reliable
Property analysis dynamic process, presentation is staticaanalysis results, is unfavorable for providing guidance for subsequent maintenance repair maintenance work
Thinking.
The emphasis of bullet train systems reliability analysis should be based on thrashing, and thrashing is then by system
The failure of one component causes component function associated there to decline or fail, and then entire system is detached from physics or information
System, reduces the efficiency of whole system.Faults coupling between these components will form complicated cyberrelationship, give system band one's purpose in coming
The operation risk of unimaginable " dominoes ".Therefore, the dynamic process of High-speed Train systems reliability analysis needs
In conjunction with train system fault propagation, identification system fault propagation critical path and its propagation effect range, the description system failure are passed
The whole process broadcast, and then dynamic analysis train system reliability.
Summary of the invention
The object of the invention is to arrange for a kind of effective high speed for overcoming the problems, such as that above-mentioned technology exists and provides
The method of vehicle system reliability.
The purpose of the present invention is realized especially by following technical scheme:
The method of bullet train systems reliability analysis based on potential energy field and network efficiency, this method include following step
It is rapid:
(1) establishing using coupled relation of the bullet train component between node, component is the bullet train system for connecting side
Complex network model；
(2) on the basis of the bullet train system complex network model, in conjunction with potential energy field theory, bullet train is established
System failure propagation model obtains the every step of the system failure and propagates inoperative component；
(3) on the basis of the bullet train system failure propagation model, in conjunction with bullet train grid efficiency, divide
Analyse bullet train system reliability.
Preferably, step (1) high speed train system is made of n component, and there are m items to connect side between component, is established
Bullet train system complex network model
G=(V, E, R)
Wherein: V=(v1,v2,…,vj,…,vn) indicate n node of network set, attribute depending on component event
Barrier state；E=(e12,…,eij,…,ern) it is the set that network m item connects side, R=(r12,…,rij,…,rrn) indicate high speed
The degree to be influenced each other between train system component with coupled relation.
Preferably, bullet train system failure propagation model S is established in step (2)k
Sk=< V, E, R, Mk,Wk,Ik>
Wherein, IkIndicate the incidence matrix of grid model after kth step fault propagation occurs for bullet train system, WkTable
Show that the state that kth step all parts receive failure influence, M occur for bullet train systemkIndicate that kth step occurs for bullet train system
System mode after fault propagation；
MkIt is expressed as
M(l)kLabel is transmitted on the l articles fault propagation path after expression bullet train system generation kth step fault propagation
The system mode set of node, W (l)k-1Indicate that the l articles fault propagation road after -1 step fault propagation of kth occurs for bullet train system
The state set for receiving failure influence of flag node is transmitted on diameter,
Symbol " " is defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
SymbolIs defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
SymbolIs defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
Probability of spreading P in bullet train system failure propagation modelijFor
Wherein, PijIndicate virus from node viPropagate to node vjProbability；Indicate viral node viSection adjacent thereto
Point vjBetween average propagation rate；λiIndicate viral node viCourse of disease time, G is constant parameter；mi、mjRespectively object i
With the quality of j, rijFor the distance between object i and j；
When the probability of spreading of the l articles fault propagation chain road of bullet train systemWhen less than certain threshold value, initially
Node failure, which terminates, to be propagated, and chain road node state stops iterative process, obtains the l articles fault propagation path and its height at this time
The state of fast train system and component.
Preferably, bullet train grid efficiency described in step (3) is
Efk (G) indicates that entire bullet train grid efficiency after kth step fault propagation occurs for system；Expression system
Shortest time used in access after generation kth step fault propagation between any two node；
Calculating bullet train system reliability Rk (G) is
Detailed description of the invention
Fig. 1 the method for the present invention flow chart.
Fig. 2 train bogie couple system components interactively matrix diagram.
It influences each other between Fig. 3 train bogie system unit and coupled relation degree figure.
Fig. 4 train bogie system unit original state figure.
Fig. 5 train bogie system component failure probability of spreading matrix.
Fig. 6 train bogie system failure communication process figure.
Fig. 7 train bogie system reliability trend chart.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention
Premised on implemented, the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to
Following embodiments.
The method realization of the present embodiment specifically includes following steps (method flow is as shown in Figure 1):
(1) analysis and High-speed Train system physical topological structure feature are established using bullet train component as node, portion
Coupled relation between part is the bullet train system complex network model for connecting side.Pass through analysis and a certain model high speed of research
Train bogie system topology feature and fault propagation feature carry out analog simulation.Extract the high-speed train bogie system
It unites 35 components (as shown in table 1), coupling relationship carries out high-speed train bogie system complex net between analysis system component
Network modeling.
1 high-speed train bogie system unit inventory of table
Bullet train system is that a kind of Measurement And Control of The Jet Flotation Column for being made of numerous components and there is complicated interaction relationship is big
System.Complex Networks Theory is applied herein, and bogie system unit is node, and the interaction relationship between component is connection
Side constructs bullet train system complex network model.Assuming that bullet train system is made of n component, deposited between these components
Side is connected in m item, then bullet train system complex network model is represented by G=(V, E, R).
Wherein:
V=(v1,v2,…,vj,…,vn) indicate n node of network set, attribute depending on component failure shape
State；E=(e12,…,eij,…,ern) it is the set that network m item connects side, it indicates to whether there is machine between bogie system unit
Tool, electronics, information and control etc. influence each other and coupled relation, can define E=[eij], have
R=(r12,…,rij,…,rrn) indicate the degree to influence each other between bullet train system unit with coupled relation,
It can define R=[rij]。
There is three kinds of connections such as mechanical connection, electrical connection and information connection to close in the high-speed train bogie system
System, therefore in bogie grid GZIn=(V, E, R), we are by train bogie couple system components interactively matrix
Middle element " 1 " is converted into " * ", element " 0 " is converted into " Null ", and draw train bogie couple system components interactively
Matrix diagram, as shown in Figure 2；Because may be simultaneously present 2 kinds or 3 kinds of coupling relationships (connection relationship) between two adjacent components,
Therefore, it enables
Then influencing each other between high-speed train bogie system unit can be as shown in figure 3, because only with the degree of coupled relation
Have and exist simultaneously mechanical connection between component traction electric machine and velocity sensor 1 and connect with information, therefore we turn to train
Element " 1 " is converted into " * " in frame couple system components interactively matrix, and element " 2/3 " is converted into " o ", and element " 0 " is turned
Change " Null " into.
(2) it on the basis of bullet train system complex network model, in conjunction with potential energy field theory, studies between system unit
Probability of spreading, analysis the bullet train system failure propagate whole process, establish bullet train system failure propagation model.
S02: building high-speed train bogie system failure propagation model, it will be assumed that component 16 (traction electric machine) breaks down.Therefore,
By 35 component original state M of the train bogie system0System all parts when (as shown in Figure 4) and component 16 break down
Receive the state W of failure influence0It substitutes into probability of spreading model to be solved, obtains the probability of failure propagation between adjacent node
(first step probability of spreading between system node), and construct system relationship matrix I1, as shown in figure 5, indicating that failure starts to pass with x-axis
The component broadcast, y-axis indicate component of catching an illness, and z-axis indicates the probability of spreading between adjacent amount component.
W0=(01 L 116 L 035)
By high-speed train bogie system initial state M0, primary fault influence state W0And system relationship matrix I1Generation
Enter fault- traverse technique Sk, the state transfer for carrying out system unit changes with iteration, and carries out propagating termination condition judgement (herein
With 10-8As transmission threshold), the high-speed train bogie system failure for finally obtaining analog simulation propagates all possible road
Diameter, as shown in table 2 and Fig. 6.In Fig. 6, component 16 (traction electric machine) is broken down suddenly (labeled as green), is caused and its phase
The performance of associated component generates degeneration, is reached at first by simulation discovery component 1 (framework assembly) with component 13 (shaft coupling)
The state of failure, is marked as yellow；The probability of spreading of fault propagation chain road at this timeGreater than 10-8, propagate and continue.
The 2 high-speed train bogie system failure of table propagates analysis simulation result
Subsequent simulation is carried out with this, (height adjusts for discovery component 5 (pressurized cylinder), component 6 (spring composition), component 17
Device), component 19 (air spring), component 21 (drawing pull bar) and component 14 (gear-box composition) reach the shape of failure at first
State is marked as orange；The probability of spreading of fault propagation chain road at this timeGreater than 10-8, propagate and continue.Work as progress
When third portion propagates, component 2 (brake clamp), component 5 (pressurized cylinder), component 7 (axle box), (the vertical damping of level-one of component 8
Device), component 10 (wheel), component 11 (axle), component 15 (earthing or grounding means), component 25 (main air hose), 27 (velocity pick-up of component
Device 2) with component 32 (box bearing temperature sensor) reach malfunction, the probability of spreading of fault propagation chain road at this timeAlready less than 10-8, therefore the high-speed train bogie system failure is propagated and is terminated, bogie thrashing.
On the basis of bullet train system complex network model G=(V, E, R), the rule change of bonded block state, and
According to distribution diffusion principle, bullet train system failure propagation model S is establishedk。
Sk=< V, E, R, Mk,Wk,Ik> (2)
Wherein, IkThe incidence matrix for indicating grid model after kth step fault propagation occurs for bullet train system, can table
It is shown as
PijIndicate fault trend from node viPropagate to node vjProbability.
WkIndicate that all parts receive the state of failure influence.
MkIndicate bullet train system occur kth step fault propagation after system mode, by system all parts this
When state composition.According to distribution diffusion principle, and the state transfer alternative manner of component in system is combined, it is each in formulation system
The rule change of a unit status.Therefore, MkIt is represented by
W0Indicate that bullet train system system all parts in original state, a certain component malfunction receive failure shadow
Loud state composition, is represented by
W0=(01 L 1i L 0n) (5)
M0The original state for indicating bullet train system, is made of the original state of all parts in system, is represented by
M(l)kThe shape of flag node is transmitted after expression system generation kth step fault propagation on the l articles fault propagation path
State set.
Symbol " " is defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
SymbolIs defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
SymbolIs defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
When the probability of spreading of the l articles fault propagation chain road of bogie systemIt is initial to save when less than certain threshold value
Point failure, which terminates, to be propagated, and chain road node state stops iterative process, obtains the l articles fault propagation path and its steering at this time
The state of frame system and component.
Wherein, the probability of failure propagation between initial first step system unit is P (1), when the system failure propagates to kth step
When, obtain the probability of failure propagation P (1) on the paths between all components, P (2) ..., P (k) and its corresponding system
Fault propagation link { v1, v2..., vk}。
In bullet train system failure propagation model SkIn, crucial place how is characterized between system unit (node)
Probability of spreading Pij.Therefore, we are by viral transmission theory, definition
Wherein, PijIndicate virus from node viPropagate to node vjProbability；Indicate viral node viSection adjacent thereto
Point vjBetween average propagation rate；λiIndicate viral node viCourse of disease time, we can be by the course of disease time of node herein
It is defined as the mean repair time of bullet train system unit.
However, the definition and solution for the Mean Speed propagated between node are extremely difficult in the document of viral transmission, lead to
It is often to be obtained by experience and statistical data, is not related to the status attribute of each viral node itself.To understand
Certainly this problem, herein by the conversion and law of conservation of energy in the energy field theory in analogy physics, in viral transmission
A kind of bullet train system failure propagation model based on potential energy field is proposed on the basis of model.
The concept of field in the range of physics other than being widely used, in biology, mechanical engineering, material science
And it is also mentioned in behaviorist risk research.Field is a kind of citation form existing for substance, has the phases such as energy, momentum and quality
Attributive character is closed, the interaction between material object can be transmitted, physical quantity can be referred to as in space or temporal a part
?.
All there may be failures for all parts of bullet train system, this is objective reality, can be between the components
It is propagated and is developed according to certain relationship, there is certain space-time characterisation.Therefore, we will be in bullet train system unit
Failure diverging analogize to field.
According to potential energy field theory, we are defined in the potential energy field being made of two articles i and j, the potential energy E of object iiIt can table
It is shown as
Wherein, G is constant parameter；mi、mjThe respectively quality of object i and j；aiThe acceleration of movement is propagated for object i；
hiIt is displaced for the propagation of object i；rijFor the distance between object i and j.
We define object l and are located on the midpoint of object i and j composition line, then object l constitutes line in object i and j
On midpoint, by the gravitation of repulsion and object j from object i, then its speed at this time can be according to law of conservation of energy public affairs
Formula calculates:
Wherein, mlFor the quality of object l；For object l with static state motion to object i and object j at object i
The speed of midpoint on line；The half of x distance between object i and j, i.e.,
Therefore, object l speed at midpoint between object i and j, which can be calculated, is
Therefore, the probability of spreading P in bullet train system failure propagation modelijFor
To sum up, we obtain complete bullet train system failure propagation model Sk, to simulate and analysis bullet train
The whole process that the system failure is propagated, and pick out all paths of fault propagation.
(3) on the basis of bullet train system failure propagation model, refer in conjunction with bullet train system complex network characterization
Mark-network efficiency analyzes the situation of change of the index, and analyzes bullet train system reliability on this basis.S03: pass through
The high-speed train bogie system failure propagates whole process, analyzes bullet train grid efficiency in the communication process that breaks down
In each step situation of change, and then analyze bullet train system bogie system reliability, as shown in Figure 7.Y in Fig. 7
When the Initial travel state of axis, i.e. system, the Calculation of Reliability of system is when component 16 (traction electric machine) breaks down suddenly
The ratio of the efficiency of network in the presence of 35 nodes of network efficiency and network after removing node 16 are complete be at this time be
System reliability；35 nodes of network efficiency and network that the subsequent first step is propagated up to propagation termination (third step propagation) are completely deposited
When network efficiency be each step system reliability.By Fig. 7, it can be concluded that, component 16 (traction electric machine) occurs suddenly
The reliability of system is 0.899 when failure, is belonged within the scope of capable of guaranteeing that train operates normally；And when failure is propagated
After diffusion, trouble unit is gradually increased, until system shares 19 component malfunctions, and system is entirely ineffective when propagating termination.
In the step (3), scholars pass through the survivability index of quantitative description network system, and analysis is centainly being attacked
The reliability of complex network under policy breaks effect.Network efficiency refers to most short used in the access in network between any two points
The aisled ratio of institute between the inverse and nodes of time, i.e.,
Wherein, dijIndicate the shortest time used in the access in network between any two node.
And on the basis of bullet train system failure propagation model, defining bullet train grid efficiency is
Efk(G) indicate that entire bullet train grid efficiency after kth step fault propagation occurs for system；Expression system
Shortest time used in access after generation kth step fault propagation between any two node, hereinBullet train system can be passed through
It influences each other between component and is calculated with the degree of coupled relation.
The definition of reliability be finger element, product, system within a certain period of time, under certain condition trouble-freely execute or
Person is kept for a possibility that a certain specified function.The validity of network is one of measurement index of reliability of reaction network, network
Validity network efficiency and the ratio between initial network efficiency after attack can be then received by network.Therefore in bullet train system
In, we define train system reliability: when a certain component malfunction of train system, leading to the associated component that is coupled with it
Functional deterioration occurs, generates the effect of fault propagation, until in this period of entire bullet train system function failure, it is high
Health is celebrated in the variation of fast train system network efficiency.Therefore, we can calculate bullet train system reliability and are
In this way by system failure communication process, it is straight since component small fault can gradually to analyze bullet train system
Reliability situation of change into whole system failure procedure.
Claims (4)
1. the method for the bullet train systems reliability analysis based on potential energy field and network efficiency, which is characterized in that this method packet
Include following steps:
(1) establishing using coupled relation of the bullet train component between node, component is the bullet train system complex for connecting side
Network model；
(2) on the basis of the bullet train system complex network model, in conjunction with potential energy field theory, bullet train system is established
Fault- traverse technique obtains the every step of the system failure and propagates inoperative component；
(3) on the basis of the bullet train system failure propagation model, in conjunction with bullet train grid efficiency, analysis is high
Fast train system reliability.
2. the method for the bullet train systems reliability analysis as described in claim 1 based on potential energy field and network efficiency,
It is characterized in that, in step (1)
Bullet train system is made of n component, and there are m items to connect side between component, establishes bullet train system complex network
Model
G=(V, E, R)
Wherein: V=(v1,v2,…,vj,…,vn) indicate n node of network set, attribute depending on component failure shape
State；E=(e12,…,eij,…,ern) it is the set that network m item connects side, R=(r12,…,rij,…,rrn) indicate bullet train
The degree to be influenced each other between system unit with coupled relation.
3. the method for the bullet train systems reliability analysis as described in claim 1 based on potential energy field and network efficiency,
It is characterized in that, in step (2)
Establish bullet train system failure propagation model Sk
Sk=< V, E, R, Mk,Wk,Ik>
Wherein, IkIndicate the incidence matrix of grid model after kth step fault propagation occurs for bullet train system, WkIndicate high
The state that kth step all parts receive failure influence, M occur for fast train systemkIndicate that bullet train system occurs kth and walks failure
System mode after propagation；
MkIt is expressed as
M(l)kFlag node is transmitted on the l articles fault propagation path after expression bullet train system generation kth step fault propagation
System mode set, W (l)k-1After expression bullet train system generation -1 step fault propagation of kth on the l articles fault propagation path
It is transmitted the state set for receiving failure influence of flag node,
Symbol " " is defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
SymbolIs defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
Symbol " ⊕ " is defined as:
If A ∈ Rm×n, and B ∈ R1×n, then have:
Probability of spreading P in bullet train system failure propagation modelijFor
Wherein, PijIndicate virus from node viPropagate to node vjProbability；Indicate viral node viNode v adjacent theretoj
Between average propagation rate；λiIndicate viral node viCourse of disease time, G is constant parameter；mi、mjRespectively object i and j
Quality, rijFor the distance between object i and j；
When the probability of spreading of the l articles fault propagation chain road of bullet train systemWhen less than certain threshold value, start node event
Barrier, which terminates, to be propagated, and chain road node state stops iterative process, obtains the l articles fault propagation path and its bullet train at this time
The state of system and component.
4. the method for the bullet train systems reliability analysis as described in claim 1 based on potential energy field and network efficiency,
It is characterized in that, in step (3)
The bullet train grid efficiency is
Efk(G) indicate that entire bullet train grid efficiency after kth step fault propagation occurs for system；Expression system occurs the
Shortest time used in access after k step fault propagation between any two node；
Calculate bullet train system reliability Rk(G) it is
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910495102.8A CN110309550B (en) | 2019-06-10 | 2019-06-10 | High-speed train system reliability analysis method based on potential energy field and network efficiency |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910495102.8A CN110309550B (en) | 2019-06-10 | 2019-06-10 | High-speed train system reliability analysis method based on potential energy field and network efficiency |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110309550A true CN110309550A (en) | 2019-10-08 |
| CN110309550B CN110309550B (en) | 2021-06-22 |
Family
ID=68075876
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910495102.8A Active CN110309550B (en) | 2019-06-10 | 2019-06-10 | High-speed train system reliability analysis method based on potential energy field and network efficiency |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110309550B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112345276A (en) * | 2020-11-10 | 2021-02-09 | 北京交通大学 | State evaluation and prediction system for key components of medium-speed maglev train |
| CN112560188A (en) * | 2020-12-24 | 2021-03-26 | 北京交通大学 | Method for judging association relation between high-speed train components |
| CN112766509A (en) * | 2021-01-18 | 2021-05-07 | 合肥工业大学 | Method for analyzing fault propagation path of electronic information system |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8700958B2 (en) * | 2006-08-11 | 2014-04-15 | Riverbed Technology, Inc. | Multi-variate network survivability analysis |
| CN104392071A (en) * | 2014-12-12 | 2015-03-04 | 北京交通大学 | High-speed train system security evaluation method based on complex network |
| CN104992011A (en) * | 2015-06-24 | 2015-10-21 | 东北大学 | FMEA analysis based comprehensive reliability allocation method for numerical control machine tool |
| CN105760589A (en) * | 2016-02-03 | 2016-07-13 | 北京交通大学 | Reliability analyzing method based on high-speed train system action relation network |
| CN107846307A (en) * | 2017-10-13 | 2018-03-27 | 天津大学 | A kind of control method being used for information physical system fault propagation |
| US20180189662A1 (en) * | 2006-02-14 | 2018-07-05 | Power Analytics Corporation | Systems and Methods for Automatic Real-Time Capacity Assessment for Use in Real-Time Power Analytics of an Electrical Power Distribution System |
| CN108269211A (en) * | 2016-12-30 | 2018-07-10 | 北京金风科创风电设备有限公司 | The determining method and apparatus of the reliability index of wind power generating set system |
| CN109104328A (en) * | 2018-06-14 | 2018-12-28 | 北京航空航天大学 | A kind of group system reliability assessment method based on complex network |
| CN109544011A (en) * | 2018-11-26 | 2019-03-29 | 北京交通大学 | Bullet train system reliability estimation method based on inside and outside covariant |
| CN109543248A (en) * | 2018-11-02 | 2019-03-29 | 北京交通大学 | The generation method in the train system fault propagation path based on failure potential energy field |
-
2019
- 2019-06-10 CN CN201910495102.8A patent/CN110309550B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180189662A1 (en) * | 2006-02-14 | 2018-07-05 | Power Analytics Corporation | Systems and Methods for Automatic Real-Time Capacity Assessment for Use in Real-Time Power Analytics of an Electrical Power Distribution System |
| US8700958B2 (en) * | 2006-08-11 | 2014-04-15 | Riverbed Technology, Inc. | Multi-variate network survivability analysis |
| CN104392071A (en) * | 2014-12-12 | 2015-03-04 | 北京交通大学 | High-speed train system security evaluation method based on complex network |
| CN104992011A (en) * | 2015-06-24 | 2015-10-21 | 东北大学 | FMEA analysis based comprehensive reliability allocation method for numerical control machine tool |
| CN105760589A (en) * | 2016-02-03 | 2016-07-13 | 北京交通大学 | Reliability analyzing method based on high-speed train system action relation network |
| CN108269211A (en) * | 2016-12-30 | 2018-07-10 | 北京金风科创风电设备有限公司 | The determining method and apparatus of the reliability index of wind power generating set system |
| CN107846307A (en) * | 2017-10-13 | 2018-03-27 | 天津大学 | A kind of control method being used for information physical system fault propagation |
| CN109104328A (en) * | 2018-06-14 | 2018-12-28 | 北京航空航天大学 | A kind of group system reliability assessment method based on complex network |
| CN109543248A (en) * | 2018-11-02 | 2019-03-29 | 北京交通大学 | The generation method in the train system fault propagation path based on failure potential energy field |
| CN109544011A (en) * | 2018-11-26 | 2019-03-29 | 北京交通大学 | Bullet train system reliability estimation method based on inside and outside covariant |
Non-Patent Citations (3)
| Title |
|---|
| LUYI LI等: "A systematic modeling approach for failure indicators of complex software-intensive systems", 《IEEE XPLORE》 * |
| 刘文波: "非自然灾害下基础设施系统关联可靠性分析", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 王健等: "Internet 级联动力学分析与建模", 《JOURNAL OF SOFTWARE》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112345276A (en) * | 2020-11-10 | 2021-02-09 | 北京交通大学 | State evaluation and prediction system for key components of medium-speed maglev train |
| CN112560188A (en) * | 2020-12-24 | 2021-03-26 | 北京交通大学 | Method for judging association relation between high-speed train components |
| CN112560188B (en) * | 2020-12-24 | 2023-09-15 | 北京交通大学 | Method for judging association relation between high-speed train components |
| CN112766509A (en) * | 2021-01-18 | 2021-05-07 | 合肥工业大学 | Method for analyzing fault propagation path of electronic information system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110309550B (en) | 2021-06-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110309550A (en) | A kind of bullet train systems reliability analysis method based on potential energy field and network efficiency | |
| CN103955556B (en) | High Speed Train Operation Control onboard system fault logic modeling method | |
| CN109543248A (en) | The generation method in the train system fault propagation path based on failure potential energy field | |
| CN105676842B (en) | A kind of high-speed rail train control on board equipment method for diagnosing faults | |
| CN106533759B (en) | A kind of link prediction method based on path entropy in multitiered network | |
| CN106444719A (en) | Multi-fighter cooperative fault diagnosis method under switching topology | |
| CN105760589A (en) | Reliability analyzing method based on high-speed train system action relation network | |
| CN108427401A (en) | A kind of flight control system collaborative fault diagnosis method with joint connection topology | |
| CN102684902B (en) | Based on the network failure locating method of probe prediction | |
| CN110216680A (en) | A kind of service robot cloud ground collaborative fault diagnosis system and method | |
| Lin et al. | System reliability assessment based on failure propagation processes | |
| CN108494594A (en) | A kind of analysis method and system of EIGRP route networks failure | |
| CN104458297A (en) | Fault detection method for train suspension system sensor based on nonlinearity random model | |
| CN106528970A (en) | CPS modeling and property verification method based on possibility space-time hybrid automaton | |
| CN101901317B (en) | Growing hierarchical self-organizing maps (GHSOM)-based intrusion detection method for neural network | |
| CN104965506A (en) | Adjustable parameter-based distributed flight control system real-time fault diagnosis method | |
| CN109544011A (en) | Bullet train system reliability estimation method based on inside and outside covariant | |
| CN102739527A (en) | Network packet loss rate detection method | |
| Zhang et al. | Traffic fluctuations on weighted networks | |
| CN109522633B (en) | High-speed railway system key link set identification method based on topology comprehensive importance | |
| CN106656797B (en) | A method of considering the AFDX network path optimization of risk balance | |
| CN110213741A (en) | A kind of vehicle based on width study sends the real-time detection method of information true or false | |
| Zhang et al. | Tensor-based spectral analysis of cascading failures over multilayer complex systems | |
| CN104468196B (en) | Virtual network method for diagnosing faults and device based on evidence screening | |
| Zeng et al. | Railway train device fault causality model based on knowledge graph |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20201023 Address after: No. 3, Yuen Yuan village, West Straight outside Beijing, Beijing Applicant after: Beijing Jiaotong University Applicant after: CRRC QINGDAO SIFANG Co.,Ltd. Address before: 100044 Beijing city Haidian District Shangyuan Village No. 3 Applicant before: Beijing Jiaotong University |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |