CN106951648A - A kind of interacted system reliability estimation method for considering equipment life cycle management - Google Patents
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Abstract
The present invention relates to power system asset management field, more particularly to a kind of interacted system reliability estimation method for considering equipment life cycle management.Methods described comprises the following steps：(S1) founding mathematical models：Consider the factors such as fault mode feature and reparation that the equipment of different runtimes undergone, the fault rate of each runtime can respectively be modeled；(S2) system emulation：In the sequential Monte Carlo emulation of system reliability, when considering the characteristic of equipment life cycle management fault rate, initial time and the difference at putting equipment in service moment according to the period to be assessed is needed to determine the runtime residing for each equipment, so as to determine the failure rate model of life cycle management.The present invention is capable of the influence that the change of the full longevity cycle fault rate of quantitative appraisal equipment has for Reliability evaluation.
Description
Technical field
The present invention relates to power system asset management field, more particularly to a kind of mutual contact for considering equipment life cycle management
System reliability estimation method.
Background technology
Two classes can be divided into by being presently used for the method for fail-safe analysis：Analytic method and emulation mode.Analytics evaluation method
Although with time-consuming short advantage is assessed, once meeting with system scale and expanding and operating condition complicated and changeable, it is modeled
Often run into and compare bigger difficulty.By contrast, Simulation Evaluation method can start with from the discrete component of composition system, handle
More complicated element state characteristic and influence each other, thus can more easily simulate whole complication system with
Machine behavior.
In emulation mode, sequential Monte Carlo method possesses complication system behavior of the simulation with temporal correlation
Ability, thus it is also the most accurate to the reliability evaluation of system.From the prior art it can be seen that with setting that weather condition changes
There is considerable influence to system reliability in standby failure/repair rate, the aging characteristics and repairing condition of element are to system reliability
Influence, and made comparative analysis with 3 kinds of Sequential Simulation methods respectively.Some documents are then in the aging degree of unavailability concept of foundation
On the basis of derived a kind of Analytical Solution method of aging degree of unavailability, while also illustrate that component ageing reliably shows to system
Write influence.Some literature reviews running environment and influence of the service recovery strategy to distribution system power supply reliability after failure.
As can be seen here, in it is different run time under element failure rate different degrees of influence can be caused to system reliability, enter
And influence the final programmed decision-making of system.
At present, traditional interacted system reliability estimation method is general using annual failure/repair rate as known parameters, this
Although kind consider simplify analysis process, while also have ignored the service condition of element, environmental aspect and self deterioration etc. because
The rule that is continually changing in its cycle of operation life-cycle of element, thus caused system reliability estimated bias can not ignore.
The content of the invention
The problem of in background technology, the invention provides a kind of interacted system for considering equipment life cycle management is reliable
Property appraisal procedure.
To achieve these goals, the present invention proposes following technical scheme：
A kind of interacted system reliability estimation method for considering equipment life cycle management, it is characterised in that methods described bag
Include following steps：
(S1) founding mathematical models：Consider fault mode feature and reparation that the equipment of different runtimes undergone etc. because
Element, can respectively be modeled to the fault rate of each runtime；
(S2) system emulation：In the sequential Monte Carlo emulation of system reliability, when consideration equipment life cycle management event
, it is necessary to determine each equipment according to the initial time and the difference at putting equipment in service moment of period to be assessed during the characteristic of barrier rate
The residing runtime, so as to determine the failure rate model of life cycle management；
The fault mode include repairable elements fault mode, chance failure pattern and random failure rate and certain outside
The interdependent continuous mode of portion's condition；
The different runtimes include put into operation early stage, normality runtime, aging maintenance phase and accelerated ageing phase.
Further, the mathematical definition of the fault rate of the repairable elements fault mode is：
Wherein,Repairable elements are represented respectively to follow under the fault mode c of Poisson process in a certain kind,
Fault rate and the number of stoppages in [0, the t] period, c represent random failure pattern (rm) or initial failure pattern (in), E
() represents mathematical expectation；
The fault rate of the chance failure pattern is constant, can be passed through based on formula (1) under conditions of t → ∞ and pushed away
Lead and obtain：
In formula, x represents the random fault time of adjacent failure twice；
The random failure rate is also also considered as the function of time, i.e. λrm(t), wherein 0≤t≤TL, TLFor the longevity of element
Life；
The formula of the fault rate of the random failure rate continuous mode interdependent with certain external condition is：
λrm=F (Ω) (18)
In formula, Ω is external environment condition variable vector.
Further, the fault rate of the early stage of putting into operation：
The element fault of early stage of putting into operation follows early stage and accidental two kinds of fault modes, and two kinds of fault modes are made in [0, t]
Total expectation number of stoppages under can be decomposed into two parts sum, i.e.,：
E[Nel(t)]=E [Nrm(t)]+E[Nin(t)] (19)
Understood according to formula (1), element infant mortality can also be obtained by superposition：
λel(t)=λin(t)+λrm(t) (20)
For λin(t), a kind of typical model is exponential model, and its expression formula is：
λin(t)=α e-βt, 0≤t<Tin (21)
α in formula>0 is the primary fault rate of early stage of putting into operation, TinFor the end time threshold values for early stage of putting into operation, λin(t≥Tin)≈
0；
Bring formula (6) into formula (5) and obtain equipment infant mortality model and be：
λel(t)=λin(t)+λrm(t), 0≤t<Tin (22)
The fault rate of the normality runtime：
The chife failure models that the equipment of normality runtime is undergone are random failure pattern, therefore its fault rate is：
λno(t)=λrm(t), Tin≤t<Tno (23)
In formula, TnoFor the finish time of normality runtime；
The fault rate of phase is safeguarded in the aging：
Equipment fault in the aging maintenance phase is based on random failure, and its failure is recoverable, specific modeling process
It is as follows：
First from the point of view of element repairing effect, repair can be grown from weak to strong and be in turn divided into minimum reparation, not complete
It is complete to repair, repair completely；
If do not consider periodic maintenance effect or think to repair only with minimum, the failure rate characteristic before and after repairing is not
Become, typical failure rate model is described using Power-law Process：
In formula, η>0, σ>1, η and σ represents that the scope scale parameters and shape shape parameters of phase, T are safeguarded in aging respectivelyno
Carved at the beginning of for the aging maintenance phase, TomThe finish time of phase, λ are safeguarded for agingom(t<Trm)=0；
If considering the repair of periodic maintenance, service age reduction factor q can be introduced to set up and repair front and rear element event
Barrier rate relation, is expressed as follows：
If element breaks down at the t ' moment, by trTime is repaired, then element is in t=t '+trThe event of+Δ t
Barrier rate can be expressed as：
λ′om(t)=λom[q(t′+tr)+Δt] (25)
Aging safeguards that the fault rate of phase can be taken and be obtained by (3) (10) two parts：
λma(t)=λ 'o′m(t)+λrm(t), Trm≤t<Tom (26)
The fault rate of the accelerated ageing phase：
With respect to the definition of formula (1) repairable elements fault rate, unrepairable element failure rate is replaced with the concept of level of significance
In generation, its mathematical definition is：
In formula, had(t) it is ageing equipment failure level of significance, Fad(t)、fad(t) be respectively the degradation failure time accumulation it is general
Rate and probability density function；
There is one-to-one pass according to the definition of formula (12), between aging level of significance and the probability distribution of fault time
System：
The final fault rate of accelerated ageing phase can be obtained by (3) (12) superposition：
λaa(t)=had(t)+λrm(t)Tom≤t≤TL (29)
Further, the specific method of the step (S2) is：
If the initial time of period to be assessed is Ts, period span is Φ, and putting into operation for equipment be T constantly0, then equipment
The simulation model of life cycle management fault rate can obtain formula (15) by four period operation troubles rate (5) (8) (11) (14) superpositions：
λc(t)=λel(t)+λno(t)+λma(t)+λaa(t), Ts-T0≤t≤Ts-T0+Φ (30)
Further, when handling ageing failure time simulation problems, using sparse emulation mode, it is specially：
Two independent (0,1) interval uniform random number a, b is produced respectively, from moment TsSet out, first with λmax=
max[λad(t):Ts-T0≤t≤Ts-T0+ Φ] and a be known parameters, randomly generated using inverse transformation method under corresponding exponential distribution
Degradation failure time TTF；
If λad(TTF+T)/λmax>=b, then receive TTF；Otherwise, a is regenerated, b repeats said process.
Beneficial effects of the present invention are：
The invention provides a kind of meter and the interconnected electric power system reliability estimation method of equipment life cycle management fault rate,
It is capable of the influence that the change of the full longevity cycle fault rate of quantitative appraisal equipment has for Reliability evaluation.Meanwhile, for
In the evaluation procedure of whole-life cycle fee, in the case that equipment failure rate is fluctuated, the effective discriminating device full cycle in longevity
The change of fault rate.
Brief description of the drawings
Fig. 1 is life cycle management bathtub curve schematic diagram.
Embodiment
With reference to the accompanying drawings and detailed description, specific embodiments of the present invention are made with detailed elaboration.These tools
Body embodiment is not used for limiting the scope of the present invention or implementation principle only for narration, and protection scope of the present invention is still with power
Profit requires to be defined, including obvious change made on this basis or variation etc..
The invention provides a kind of interacted system reliability estimation method for considering equipment life cycle management, methods described bag
Include following steps：
(S1) founding mathematical models：Consider fault mode feature and reparation that the equipment of different runtimes undergone etc. because
Element, can respectively be modeled to the fault rate of each runtime.
According to the equipment runtime of division, it is considered to fault mode feature and reparation that the equipment of different runtimes is undergone
Etc. factor, the fault rate of each runtime can respectively be modeled.When carrying out simulation analysis, it is necessary to according to emulation initial time
The runtime residing for each equipment is determined, and then chooses the corresponding failure rate model of each equipment respectively.
According to theory of random processes, the mathematical definition of repairable elements fault rate is：
Wherein,Repairable elements are represented respectively to follow under the fault mode c of Poisson process in a certain kind,
Fault rate and the number of stoppages in [0, the t] period, c can be random failure pattern rm) or initial failure pattern (in), E
() represents mathematical expectation.
For chance failure pattern, due to adjacent fault time twice and equipment history run time in itself and reparation
Characteristic is unrelated, and the random process is then the when neat Poisson process being familiar with, and its fault rate is constant, can based on (1) t →
By being derived by under conditions of ∞：
In formula, x represents the random fault time of adjacent failure twice.
In the case that random failure data message is more complete, desirably random failure is set up according to formula (2)
Rate and the interdependent continuous model of certain external condition, as shown in formula (3).
λrm=F (Ω) (33)
In formula, Ω is external environment condition variable vector.Because external environment condition is with time consecutive variations, random failure rate can also be seen
Into the function for being the time, i.e. λrm(t), as it was previously stated, it is considered herein that random failure is present in the whole life cycle of equipment, because
This, 0≤t≤TL, TLFor the life-span of element.If data collection time is shorter or shortage of data, can by data pool merger,
The methods such as fuzzy and artificial intelligence merge the fault data of multiple external conditions the average value for obtaining random failure.
1) put into operation infant mortality：
Put into operation early stage element fault follow early stage and accidental two kinds of fault modes.Thus, two kinds of failure moulds in [0, t]
Total expectation number of stoppages under formula effect can be decomposed into two parts sum, i.e.,：
E[Nel(t)]=E [Nrm(t)]+E[Nin(t)] (34)
Understood according to (1), element infant mortality can also be obtained by superposition：
λel(t)=λin(t)+λrm(t) (35)
For λin(t), a kind of typical model is exponential model.Its expression formula is：
λin(t)=α e-βt, 0≤t<Tin (36)
α in formula>0 is the primary fault rate of early stage of putting into operation, TinFor the end time threshold values for early stage of putting into operation, λin(t≥Tin)≈
0.(6) are brought into (5) obtain equipment infant mortality model and be：
λel(t)=λin(t)+λrm(t), 0≤t<Tin (37)
2) fault rate of normality runtime：
The chife failure models that the equipment of normality runtime is undergone are random failure pattern, therefore its fault rate is：
λno(t)=λrm(t), Tin≤t<Tno (38)
In formula, TnoFor the finish time of normality runtime.
3) fault rate of phase is safeguarded in aging：
The equipment fault for safeguarding the phase in aging follows two kinds of fault modes：Random failure and degradation failure, based on this hair
Bright is foregoing it is assumed that the component failure model in the runtime is still based on random failure, therefore its failure is still to repair
's.But different from early stage and normality runtime, due to there is a certain degree of senile abrasion, it can repair fault rate before reparation
More substantially, specific modeling process is as follows for operation characteristic change afterwards：
First from the point of view of element repairing effect, repair can be grown from weak to strong and be in turn divided into minimum reparation, not complete
It is complete to repair, repair completely.If do not consider periodic maintenance effect or think to repair only with minimum, the fault rate before and after repairing
Characteristic is constant, and typical failure rate model can be also described using Power-law Process；
In formula, η>0, σ>1, η and σ represents that the scope scale parameters and shape shape parameters of phase, T are safeguarded in aging respectivelyno
Carved at the beginning of for the aging maintenance phase, TomThe finish time of phase, λ are safeguarded for agingom(t<Trm)=0；
If considering the repair of periodic maintenance, service age reduction factor q can be introduced to set up and repair front and rear element event
Barrier rate relation, is expressed as follows：
If element breaks down at the t ' moment, by trTime is repaired, then element is in t=t '+trThe event of+Δ t
Barrier rate can be expressed as：
λ′o′m(t)=λom[q(t′+tr)+Δt] (40)
The physical meaning of formula (10) is the element after failure, under a certain correcting strategy, and the amplitude of its fault rate reduction can
It is achieved with the actual enlistment age by " reduction " element, age reduction is then relevant with reparative factor q, 0≤q≤1, q
It is worth smaller repairing effect more obvious.In the case of the missing of data, the estimation for q values is relatively difficult, but can be by special
Family's experience is given, and also has document to think that random quantity can be taken as, i.e. after each repair, and q is that (0,1) is interval uniform
The random number of distribution.Finally, aging safeguards that the fault rate of phase can be taken and be obtained by (3) (10) two parts：
λma(t)=λo′m(t)+λrm(t), Trm≤t<Tom (41)
4) the accelerated ageing phase：
For the consideration of the factor such as maintenance cost and new equipment manufacture, transport, set-up time, into the accelerated ageing phase
Element stills need continuous service to a certain stipulated time or until occurs primary fault (accidentally, aging).Therefore, into the stage
Equipment once breaking down replacing of just mean, therefore can regard as unrepairable element.
The definition of relative (1) repairable elements fault rate, unrepairable element failure rate is typically replaced with the concept of level of significance
In generation, its mathematical definition is：
In formula, had(t) it is ageing equipment failure level of significance, Fad(t)、fad(t) be respectively the degradation failure time accumulation it is general
Rate and probability density function.According to the definition of formula (12), have one by one between aging level of significance and the probability distribution of fault time
Corresponding relation：
Be typically used in description ageing failure fault time two kinds of typical probability distribution functions for Wei Buer be distributed and just
State is distributed.The final fault rate of accelerated ageing phase can be obtained by (3) (12) superposition：
λaa(t)=had(t)+λrm(t)Tom≤t≤TL (44)
In the failure rate model that the above-mentioned timesharing phase sets up, the fault rate of each period separation is according to front and rear two neighboring
The runtime result of statistics can be deviated, for simplicity, and approximating assumption life cycle management fault rate of the present invention is with having
The right continuous function of limit jump.
(S2) system emulation：
In the sequential Monte Carlo emulation of system reliability, when considering the characteristic of equipment life cycle management fault rate,
Initial time and the difference at putting equipment in service moment according to the period to be assessed is needed to determine the runtime residing for each equipment,
So as to determine its failure rate model, specific method is：
If the initial time of period to be assessed is Ts, period span is Φ, and putting into operation for equipment be T constantly0, then equipment
The simulation model of life cycle management fault rate can obtain formula (15) by four period operation troubles rate (5) (8) (11) (14) superpositions.
λc(t)=λel(t)+λno(t)+λma(t)+λaa(t), Ts-T0≤t≤Ts-T0+Φ (45)
In view of fault time and replacing construction to the importance of systems reliability analysis, being can be in unified Sequential Simulation
Complete to consider that the system reliability of equipment life-cycle fault rate is emulated under framework, the present invention demonstrates two kinds and can be used for directly simulation
The emulation mode of system aging out-of-service time.
Compared to analytic method and inverse transform method, sparse method directly can be simulated random according to the display expression formula of fault rate
Fault time, without calculating Fad(t) and its inverse function, emulated in the ageing failure time of the increasingly complex situation of handling failure rate
There is stronger applicability, its emulation mode is during problem：Two independent (0,1) intervals are produced respectively to be uniformly distributed at random
Number a, b, from moment TsSet out, first with λmax=max [λad(t):Ts-T0≤t≤Ts-T0+ Φ] and a be known parameters, use
Inverse transformation method randomly generates the degradation failure time TTF under corresponding exponential distribution, if λad(TTF+T)/λmax>=b, then receive TTF,
Otherwise, a is regenerated, b repeats said process.
Claims (5)
1. a kind of interacted system reliability estimation method for considering equipment life cycle management, it is characterised in that methods described includes
Following steps：
(S1) founding mathematical models：Consider the factors such as fault mode feature and reparation that the equipment of different runtimes undergone,
The fault rate of each runtime can respectively be modeled；
(S2) system emulation：In the sequential Monte Carlo emulation of system reliability, when consideration equipment life cycle management fault rate
Characteristic when, it is necessary to be determined according to the initial time and the difference at putting equipment in service moment of period to be assessed residing for each equipment
Runtime, so as to determine the failure rate model of life cycle management；
The fault mode includes repairable elements fault mode, chance failure pattern and random failure rate and certain outer strip
The interdependent continuous mode of part；
The different runtimes include put into operation early stage, normality runtime, aging maintenance phase and accelerated ageing phase.
2. a kind of interacted system reliability estimation method for considering equipment life cycle management according to claim 1, it is special
Levy and be：
The mathematical definition of the fault rate of the repairable elements fault mode is：
Wherein,Represent repairable elements respectively to follow under the fault mode c of Poisson process in a certain kind, [0, t]
Fault rate and the number of stoppages in period, c represent random failure pattern (rm) or initial failure pattern (in), E () table
Show mathematical expectation；
The fault rate of the chance failure pattern is constant, can be passed through based on formula (1) under conditions of t → ∞ and derived
Arrive：
In formula, x represents the random fault time of adjacent failure twice；
The random failure rate is also also considered as the function of time, i.e. λrm(t), wherein 0≤t≤TL, TLFor the life-span of element；
The formula of the fault rate of the random failure rate continuous mode interdependent with certain external condition is：
λrm=F (Ω) (3)
In formula, Ω is external environment condition variable vector.
3. a kind of interacted system reliability estimation method for considering equipment life cycle management according to claim 2, it is special
Levy and be：
The fault rate of the early stage of putting into operation：
The element fault of early stage of putting into operation follows early stage and accidental two kinds of fault modes, in [0, t] under the effect of two kinds of fault modes
Total expectation number of stoppages can be decomposed into two parts sum, i.e.,：
E[Nel(t)]=E [Nrm(t)]+E[Nin(t)] (4)
Understood according to formula (1), element infant mortality can also be obtained by superposition：
λel(t)=λin(t)+λrm(t) (5)
For λin(t), a kind of typical model is exponential model, and its expression formula is：
λin(t)=α e-βt, 0≤t<Tin (6)
α in formula>0 is the primary fault rate of early stage of putting into operation, TinFor the end time threshold values for early stage of putting into operation, λin(t≥Tin)≈0；
Bring formula (6) into formula (5) and obtain equipment infant mortality model and be：
λel(t)=λin(t)+λrm(t), 0≤t<Tin (7)
The fault rate of the normality runtime：
The chife failure models that the equipment of normality runtime is undergone are random failure pattern, therefore its fault rate is：
λno(t)=λrm(t), Tin≤t<Tno (8)
In formula, TnoFor the finish time of normality runtime；
The fault rate of phase is safeguarded in the aging：
Equipment fault in the aging maintenance phase is based on random failure, and its failure is recoverable, and specific modeling process is as follows：
First from the point of view of element repairing effect, repair can be grown from weak to strong and be in turn divided into minimum reparation, not exclusively repair
Multiple, reparation completely；
If do not consider periodic maintenance effect or think to repair only with minimum, the failure rate characteristic before and after repairing is constant, allusion quotation
The failure rate model of type is described using Power-law Process：
In formula, η>0, σ>1, η and σ represents that the scope scale parameters and shape shape parameters of phase, T are safeguarded in aging respectivelynoTo be old
Carved at the beginning of changing the maintenance phase, TomThe finish time of phase, λ are safeguarded for agingom(t<Trm)=0；
If considering the repair of periodic maintenance, service age reduction factor q can be introduced to set up and repair front and rear element failure rate
Relation, is expressed as follows：
If element breaks down at the t ' moment, by trTime is repaired, then element is in t=t '+trThe fault rate of+Δ t
It can be expressed as：
λ′om(t)=λom[q(t′+tr)+Δt] (10)
Aging safeguards that the fault rate of phase can be taken and be obtained by (3) (10) two parts：
λma(t)=λ 'om(t)+λrm(t), Trm≤t<Tom (11)
The fault rate of the accelerated ageing phase：
With respect to the definition of formula (1) repairable elements fault rate, the concept of unrepairable element failure rate level of significance is substituted, its
Mathematical definition is：
In formula, had(t) it is ageing equipment failure level of significance, Fad(t)、fad(t) be respectively the degradation failure time accumulation probability and
Probability density function；
According to the definition of formula (12), there is one-to-one relation between aging level of significance and the probability distribution of fault time：
The final fault rate of accelerated ageing phase can be obtained by (3) (12) superposition：
λaa(t)=had(t)+λrm(t) Tom≤t≤TL (14)
4. a kind of interacted system reliability estimation method for considering equipment life cycle management according to claim 1, it is special
Levy and be：
The specific method of the step (S2) is：
If the initial time of period to be assessed is Ts, period span is Φ, and putting into operation for equipment be T constantly0, then equipment full longevity
Formula (15) can be obtained by four period operation troubles rate (5) (8) (11) (14) superpositions by ordering the simulation model of cycle fault rate：
λc(t)=λel(t)+λno(t)+λma(t)+λaa(t), Ts-T0≤t≤Ts-T0+Φ (15)
5. a kind of interacted system reliability estimation method for considering equipment life cycle management according to claim 1, it is special
Levy and be：
When handling ageing failure time simulation problems, using sparse emulation mode, it is specially：
Two independent (0,1) interval uniform random number a, b is produced respectively, from moment TsSet out, first with λmax=max
[λad(t):Ts-T0≤t≤Ts-T0+ Φ] and a be known parameters, randomly generated using inverse transformation method old under corresponding exponential distribution
Change fault time TTF；
If λad(TTF+T)/λmax>=b, then receive TTF；Otherwise, a is regenerated, b repeats said process.
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| CN110896369A (en) * | 2019-11-06 | 2020-03-20 | 腾讯科技（深圳）有限公司 | Method, device, equipment and medium for determining working time limit of equipment |
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| CN104778635A (en) * | 2015-04-24 | 2015-07-15 | 西安交通大学 | Replacing method for distribution transformer under whole life cycle frame |
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| CN104778635A (en) * | 2015-04-24 | 2015-07-15 | 西安交通大学 | Replacing method for distribution transformer under whole life cycle frame |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110896369A (en) * | 2019-11-06 | 2020-03-20 | 腾讯科技（深圳）有限公司 | Method, device, equipment and medium for determining working time limit of equipment |
| CN110896369B (en) * | 2019-11-06 | 2021-09-14 | 腾讯科技（深圳）有限公司 | Method, device, equipment and medium for determining working time limit of equipment |
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