CN105740606A - High speed train reliability analysis method based on reliability GERT (Graphical Evaluation and Review Technique) model - Google Patents
High speed train reliability analysis method based on reliability GERT (Graphical Evaluation and Review Technique) model Download PDFInfo
- Publication number
- CN105740606A CN105740606A CN201610046387.3A CN201610046387A CN105740606A CN 105740606 A CN105740606 A CN 105740606A CN 201610046387 A CN201610046387 A CN 201610046387A CN 105740606 A CN105740606 A CN 105740606A
- Authority
- CN
- China
- Prior art keywords
- reliability
- bullet train
- parts
- high speed
- model
- 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.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Landscapes
- Complex Calculations (AREA)
Abstract
The invention belongs to the technical field of high speed train system reliability, and particularly relates to a high speed train reliability analysis method based on a reliability GERT (Graphical Evaluation and Review Technique) model. The high speed train reliability analysis method is characterized by comprising the following steps: analyzing the complex system structure of a high speed train, and constructing the reliability random network module of the high speed train system according to a component extraction method; according to high speed train fault data, calculating a component failure rate, and obtaining a reliability degree function through a fitting method, and combining with complex network reliability measure, analyzing influence relationship intensity among reliabilities; calculating a moment-generating function, and analyzing and calculating a pass parameter according to a random network model property and reliability network diagram to calculate the reliability degree of the system; and carrying out the sensitivity analysis of the high speed train system to evaluate the influence of a weak component on the system. The high speed train reliability analysis method can realize the computation of the reliability degree of the complex network system and obtain the influence degree of the component reliability on the system reliability. An experiment result indicates that the practicability of a model algorithm is high.
Description
Technical field
The invention belongs to bullet train system reliability technical field, be specifically related to a kind of bullet train systems reliability analysis method based on reliability GERT stochastic network model.
Background technology
Bullet train is with its high speed, low stain, the advantage such as quick, comfortable, safe and punctual, it has also become most one of bulk transport mode of sustainability.Bullet train is high-tech system complicated, electromechanical integration as one, and the reliability consideration work of its pedigree is very necessary.The current research method existing defects about bullet train system reliability, the incidence relation etc. that such as parts are mutually contradictory, ignore between parts, may result in system Reliability Research result and deviation occurs, and then cause being likely to based on system Reliability Research system that inaccuracy occurs.Existing Reliability Calculation Model and method, still come with some shortcomings and limitation: 1) most research method is based on static stability numerical value, fails the dynamic characteristic of descriptive system reliability；2) when solving system reliability, algorithm is many is completely independent this supposed premise each other based on parts, and therefore mostly solution procedure is simply being added or being multiplied of components reliability.But in systems in practice, due to mechanism or electronic interferences, the relation between parts and between parts and system reliability is sufficiently complex, simple being added or be multiplied can not analyze the reliability of system accurately.Limitation in view of the studies above, consider the dynamic characteristic of bullet train system reliability, the randomness of part reliability and the relation that influences each other, it is proposed to bullet train system dependability is analyzed and describes and system is carried out sensitive analysis by the available GERT reliability stochastic network model estimated in conjunction with reliability of complex networks.The reliability analysis of bullet train is had great practical value and dissemination by the method.
Summary of the invention
In order to solve the problems referred to above, the technical scheme that the present invention takes is as follows:
A kind of bullet train analysis method for reliability based on reliability GERT model, it is characterised in that described method comprises the steps:
Step 1 analyzes the relation that influences each other between internal part composition and each part reliability of bullet train complication system, the related reliability parameter information of collecting part reliability, builds the reliability stochastic network model of bullet train system；
Bullet train fault data is goed deep into Treatment Analysis by step 2, calculating unit crash rate, Reliability Function is drawn by approximating method, calculating the weighted mean of inefficacy degree, cluster coefficients and inefficacy this three of betweenness according to the reliability stochastic network model built, drawing affects relationship strength between each part reliability；
Step 3 calculates moment generating function, calculates Transfer Parameters and then computing system reliability according to stochastic network model character and reliability network map analysis；
Step 4 carries out bullet train system sensitivity analysis, assesses the weak element impact on system by sensitive analysis.
The detailed process of described step 1 is that the functional structure feature to bullet train system is analyzed, and extracts principle according to parts and extracts bullet train parts；The parts of bullet train are considered as node, are considered as the interaction relationship between parts connecting limit；The fault rate of collecting part and MTBF, build the reliability stochastic network model of bullet train system；
Described parts extract principle: have mechanically or electrically or the independence of information function is overall；The parameter of parts is to calculate；Choosing with reference to its maintenance article or maintenance explanation of parts.
The detailed process of described step 2 is node in the reliability stochastic network model of described bullet train system and be connected the relation that influences each other that limit corresponds respectively between constituent system components and part reliability, and every connects limit and comprises two parameters: affect relationship strength p between part reliabilityijThe i.e. i-th node Reliability Function ln (R to the reliability effect degree of jth node and the start node through natural logrithm conversioni), the failure probability density function that f (t) is parts, the Reliability Function of partsCalculated the weighted mean of inefficacy degree, cluster coefficients and inefficacy betweenness by the reliability network model built, draw the relationship strength that affects between each part reliability, pijMeet ∑ pij=pi1+pi2+…pin=1.
The detailed process of described step 3 is described moment generating functionX is variable, is the moment generating function about variable S by what x integration was drawn, and wherein t is the time, the transmission function W between node i, jij(Si)=pij·Mij(Si),
If node Vi, VjThe respectively node at the whole story of reliability network model, according to model construction and model structure character, tries to achieve system carry-over factor of equal value reliably, then on components reliability basisAccording to the mathematical characteristic of moment generating function, according to the above-mentioned Transfer Parameters calculated, try to achieve the distribution characteristics of system dependabilitySeek derivative during s=0, carry out exponential transform on this basis, and then calculate the reliability of system.
The detailed process of described step 4 is:
Bullet train system is carried out sensitive analysis, assesses the weak element impact on system；Part reliability sensitivity is expectedE(rc) it is the reliability expected value of c subsystem, E (Rij) it is the expectation part reliability of whole system.Sensitivity variance isV(rc) it is the reliability variance of c subsystem, V (R) is the variance of whole system.Parts sensitivity expectation is more high, illustrates that part reliability promotes the lifting for system reliability and helps more big, and parts sensitivity variance is more high, illustrates that the reliability of parts promotes for system reliability fluctuation more big.
Beneficial effect
The present invention is for the bullet train system of structure and ruuning situation complexity, it is possible to the calculating of solution complex network sexual system reliability and part reliability are to system reliability influence degree.Test result indicate that the practicality of this model algorithm is good.
Accompanying drawing explanation
Fig. 1. for the bullet train systems reliability analysis flow chart of steps of the embodiment of the present invention
Fig. 2. bogie random network figure
Fig. 3. brake clamp fitting function figure
Fig. 4 .GERT stochastic network model figure
Fig. 5. parallel system figure
Fig. 6. from loop systems figure
Fig. 7. closed loop system figure
Fig. 8. bogie system dependability figure
Detailed description of the invention
Below in conjunction with accompanying drawing, the present invention is elaborated.Fig. 1 is the bullet train systems reliability analysis flow chart of steps of the embodiment of the present invention.
First the functional structure feature to high-speed train bogie system, extracts principle according to parts and extracts 35 parts in bogie system.Based on the physical arrangement relation of bogie system, take out the reliability relation between 35 parts.Build high-speed train bogie grid model, as shown in Figure 2.
The fault data of high-speed train bogie system is as shown in table 1.
Table 1. bogie system failure data
By the fault data of bullet train is goed deep into Treatment Analysis, calculating about the parts fault rate about the time, then simulate the Reliability Function of parts, the reliability fitted figure of brake clamp is as it is shown on figure 3, section components fitting parameter is as shown in table 1.
Table 2. components reliability function
The reliability GERT stochastic network model interior joint of bullet train system and limit correspond respectively to the relation that influences each other between constituent system components and part reliability.Each edge comprises two parameters: affect relationship strength p between part reliabilityijAs shown in table 3.
Table 3 bogie systematic influence relationship strength
Reliability Function ln (R through the start node of natural logrithm conversioni), model is as shown in Figure 4.
Drawn the transitive relation of transmission function by different theorems according to different relations.
1) influence each other V during in series relationship between the reliability of constituent system componentsi→Vj→Vk→…→Vz.The carry-over factor of equal value of system dependability is: Wiz(s)=Wij(si)·Wjk(sj)·Wkl(sk)…Wyz(sy)。
2), when influencing each other between the reliability of constituent system components in parallel relationship, the carry-over factor of equal value of system dependability is: Wij(s)=Wi1(s1)+Wi2(s2)+…+Win(sn), as shown in Figure 5.
3) in reliability network model containing from ring structure time, its reliability carry-over factor of equal value is: As shown in Figure 6.
4) closed loop system for closing, has following relation between the carry-over factor of equal value of reliability: As shown in Figure 7.
According to above-mentioned theorem, the Transfer Parameters of the bogie system calculated is
0.03e-0.0531s+0.09e-0.0404s+0.015e-0.0888s+0.015e-0.0929s+0.3e-0.0213s+0.11e-0.034s+0.03e-0.029s+0.41e-0.0332s。
According to the mathematical characteristic of moment generating function, according to the above-mentioned Transfer Parameters calculated, the distribution characteristics of bogie system dependability can be tried to achieve, and then calculate the reliability of system, obtain the reliability of bogie system as shown in Figure 8.Finding by contrasting, system dependability and existing bullet train maintenance cycle that the method analysis draws substantially conform to, it was demonstrated that the reasonability of method.
On the basis of the above, bullet train system is carried out sensitive analysis, calculate parts sensitivity as shown in table 4.
Table 4. parts sensitivity
The IE of axle box parts is found by Calculation of Sensitivity result table 4cIt is 0.0115, in all parts the highest, illustrate that bogie system reliability is improved by lift shaft casing reliability to have the greatest impact, axle box material is cast steel, bearing is installed in casing, its top is used for installing journal box spring, and the other end of axle box swivel arm is connected by gland and caoutchouc elasticity location node, composition take turns to positioner.Bearing outer ring in axle box is positioned by axle box front and rear cover.The IV of gearbox partscIt is 2.1223, the highest in all parts, illustrate that the reliability fluctuation range to bogie system is maximum, geared system is the critical component of transmission driving torque or braking torque, and it had both belonged to motor car wheel pair, was again the important component part of driving device.
Claims (5)
1. the bullet train analysis method for reliability based on reliability GERT model, it is characterised in that described method comprises the steps:
Step 1 analyzes the relation that influences each other between internal part composition and each part reliability of bullet train complication system, the related reliability parameter information of collecting part reliability, builds the reliability stochastic network model of bullet train system；
Bullet train fault data is goed deep into Treatment Analysis by step 2, calculating unit crash rate, Reliability Function is drawn by approximating method, calculating the weighted mean of inefficacy degree, cluster coefficients and inefficacy this three of betweenness according to the reliability stochastic network model built, drawing affects relationship strength between each part reliability；
Step 3 calculates moment generating function, calculates Transfer Parameters and then computing system reliability according to stochastic network model character and reliability network map analysis；
Step 4 carries out bullet train system sensitivity analysis, assesses the weak element impact on system by sensitive analysis.
2. a kind of bullet train analysis method for reliability based on reliability GERT model according to claim 1, it is characterized in that, the detailed process of described step 1 is that the functional structure feature to bullet train system is analyzed, and extracts principle according to parts and extracts bullet train parts；The parts of bullet train are considered as node, are considered as the interaction relationship between parts connecting limit；The fault rate of collecting part and MTBF, build the reliability stochastic network model of bullet train system；
Described parts extract principle: have mechanically or electrically or the independence of information function is overall；The parameter of parts is to calculate；Choosing with reference to its maintenance article or maintenance explanation of parts.
3. a kind of bullet train analysis method for reliability based on reliability GERT model according to claim 1, it is characterized in that, the detailed process of described step 2 is node in the reliability stochastic network model of described bullet train system and be connected the relation that influences each other that limit corresponds respectively between constituent system components and part reliability, and every connects limit and comprises two parameters: affect relationship strength p between part reliabilityijThe i.e. i-th node Reliability Function ln (R to the reliability effect degree of jth node and the start node through natural logrithm conversioni), the failure probability density function that f (t) is parts, the Reliability Function of partsWherein t is the time；Calculated the weighted mean of inefficacy degree, cluster coefficients and inefficacy betweenness by the reliability network model built, draw the relationship strength that affects between each part reliability, pijMeet ∑ pij=pi1+pi2+…pin=1.
4. a kind of bullet train analysis method for reliability based on reliability GERT model according to claim 3, it is characterised in that the detailed process of described step 3 is
Described moment generating functionX is variable, is the moment generating function about variable S by what x integration was drawn, the transmission function W between node i, jij(Si)=pij·Mij(Si),
If node Vi, VjThe respectively node at the whole story of reliability network model, according to model construction and model structure character, tries to achieve system carry-over factor of equal value reliably, then on components reliability basisAccording to the mathematical characteristic of moment generating function, according to the above-mentioned Transfer Parameters calculated, try to achieve the distribution characteristics of system dependability Seek derivative during s=0, carry out exponential transform on this basis, and then calculate the reliability of system.
5. a kind of bullet train analysis method for reliability based on reliability GERT model according to claim 4, it is characterised in that the detailed process of described step 4 is:
Bullet train system is carried out sensitive analysis, assesses the weak element impact on system；Part reliability sensitivity is expectedE(rc) it is the reliability expected value of c subsystem, E (Rij) it is the expectation part reliability of whole system, sensitivity variance isV(rc) it is the reliability variance of c subsystem, V (R) is the variance of whole system, parts sensitivity expectation is more high, illustrate that part reliability promotes the lifting for system reliability and helps more big, parts sensitivity variance is more high, illustrates that the reliability of parts promotes for system reliability fluctuation more big.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610046387.3A CN105740606A (en) | 2016-01-22 | 2016-01-22 | High speed train reliability analysis method based on reliability GERT (Graphical Evaluation and Review Technique) model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610046387.3A CN105740606A (en) | 2016-01-22 | 2016-01-22 | High speed train reliability analysis method based on reliability GERT (Graphical Evaluation and Review Technique) model |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105740606A true CN105740606A (en) | 2016-07-06 |
Family
ID=56246438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610046387.3A Pending CN105740606A (en) | 2016-01-22 | 2016-01-22 | High speed train reliability analysis method based on reliability GERT (Graphical Evaluation and Review Technique) model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105740606A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106254090A (en) * | 2016-07-11 | 2016-12-21 | 西南大学 | Complex Networks Feature computational methods |
| CN107133469A (en) * | 2017-04-27 | 2017-09-05 | 上海喆之信息科技有限公司 | One kind assesses accurate vehicle reliability assessment system |
| CN108536965A (en) * | 2018-04-11 | 2018-09-14 | 北京交通大学 | City rail traffic route operating service reliability calculation method |
| CN108596371A (en) * | 2018-04-03 | 2018-09-28 | 广西大学 | A kind of train critical component chance preventative maintenance Optimized model based on reliability |
| CN111104296A (en) * | 2019-11-14 | 2020-05-05 | 北京航空航天大学 | Carrier-based aircraft carrier landing task risk control method based on GERT |
| CN113515810A (en) * | 2021-05-17 | 2021-10-19 | 中车长春轨道客车股份有限公司 | Motor train unit bogie design and development method based on reliability and safety analysis |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102902875A (en) * | 2012-07-31 | 2013-01-30 | 中国兵器科学研究院 | Network-based method for evaluating reliability degree of failure-relevant system |
| CN104392072A (en) * | 2014-12-12 | 2015-03-04 | 北京交通大学 | Equipment integration system reliability analysis method based on dynamic fault tree |
| CN104537134A (en) * | 2014-06-16 | 2015-04-22 | 北京空间飞行器总体设计部 | Method for reliability modeling and evaluation of dynamic cascade coupling electromechanical system |
-
2016
- 2016-01-22 CN CN201610046387.3A patent/CN105740606A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102902875A (en) * | 2012-07-31 | 2013-01-30 | 中国兵器科学研究院 | Network-based method for evaluating reliability degree of failure-relevant system |
| CN104537134A (en) * | 2014-06-16 | 2015-04-22 | 北京空间飞行器总体设计部 | Method for reliability modeling and evaluation of dynamic cascade coupling electromechanical system |
| CN104392072A (en) * | 2014-12-12 | 2015-03-04 | 北京交通大学 | Equipment integration system reliability analysis method based on dynamic fault tree |
Non-Patent Citations (2)
| Title |
|---|
| 李翀 等: ""多元件复杂系统可靠性的GERT随机网络模型研究及其应用"", 《系统工程》 * |
| 秦勇 等: ""高速列车系统安全可靠性分析评估方法研究"", 《机动车传动》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106254090A (en) * | 2016-07-11 | 2016-12-21 | 西南大学 | Complex Networks Feature computational methods |
| CN107133469A (en) * | 2017-04-27 | 2017-09-05 | 上海喆之信息科技有限公司 | One kind assesses accurate vehicle reliability assessment system |
| CN108596371A (en) * | 2018-04-03 | 2018-09-28 | 广西大学 | A kind of train critical component chance preventative maintenance Optimized model based on reliability |
| CN108536965A (en) * | 2018-04-11 | 2018-09-14 | 北京交通大学 | City rail traffic route operating service reliability calculation method |
| CN108536965B (en) * | 2018-04-11 | 2020-12-01 | 北京交通大学 | Urban rail transit line operation service reliability calculation method |
| CN111104296A (en) * | 2019-11-14 | 2020-05-05 | 北京航空航天大学 | Carrier-based aircraft carrier landing task risk control method based on GERT |
| CN113515810A (en) * | 2021-05-17 | 2021-10-19 | 中车长春轨道客车股份有限公司 | Motor train unit bogie design and development method based on reliability and safety analysis |
| CN113515810B (en) * | 2021-05-17 | 2022-08-26 | 中车长春轨道客车股份有限公司 | Motor train unit bogie design and development method based on reliability and safety analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105740606A (en) | High speed train reliability analysis method based on reliability GERT (Graphical Evaluation and Review Technique) model | |
| CN107941537B (en) | A kind of mechanical equipment health state evaluation method | |
| Quinn | Axiomatic approach to radiation reaction of scalar point particles in curved spacetime | |
| Hong et al. | Vehicle energy system active defense: a health assessment of lithium‐ion batteries | |
| Jha et al. | Particle filter based hybrid prognostics for health monitoring of uncertain systems in bond graph framework | |
| Paramo et al. | Research trends and applications of PMUs | |
| CN108664673A (en) | A kind of wheel rail force load identification feature-based data model method for building up and device | |
| CN103680063A (en) | Old person abnormal condition judging method based on mobile phone accelerometer and gyroscope | |
| CN104808653A (en) | Motor servo system additivity fault detection and fault tolerant control method based on slip form | |
| Wu et al. | Incipient fault diagnosis for T–S fuzzy systems with application to high‐speed railway traction devices | |
| Jia et al. | Design of a PD‐type learning observer for reconstruction of actuator faults in descriptor systems | |
| Zhu et al. | An integrated approach for structural damage identification using wavelet neuro-fuzzy model | |
| Bonfè et al. | Active fault tolerant control of nonlinear systems: The cart-pole example | |
| Harish et al. | Fault detection and classification for wide area backup protection of power transmission lines using weighted extreme learning machine | |
| CN102521651A (en) | Bow net contact force prediction method based on NARX neural networks | |
| Li et al. | Fault diagnosis of motor bearing based on the Bayesian network | |
| CN105976021A (en) | Fault diagnosis method for roller assembly of belt conveyor | |
| Hao et al. | Gear fault detection in a planetary gearbox using deep belief network | |
| CN104036118B (en) | A kind of power system parallelization trace sensitivity acquisition methods | |
| CN110262447A (en) | A kind of ACS closed-loop system Fault Locating Method based on ANN | |
| Kou et al. | A random forest and current fault texture feature–based method for current sensor fault diagnosis in three-phase pwm vsr | |
| Avvenuti et al. | Using gait symmetry to virtually align a triaxial accelerometer during running and walking | |
| Liu et al. | Preimpact fall detection for elderly based on fractional domain | |
| CN104980442A (en) | Network intrusion detection method based on element sample sparse representation | |
| ShangGuan et al. | Fault diagnosis method of the on-board equipment of train control system based on rough set theory |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160706 |