CN104657785A - Method for determining and optimizing system maintenance rate - Google Patents

Method for determining and optimizing system maintenance rate Download PDF

Info

Publication number
CN104657785A
CN104657785A CN201510037802.4A CN201510037802A CN104657785A CN 104657785 A CN104657785 A CN 104657785A CN 201510037802 A CN201510037802 A CN 201510037802A CN 104657785 A CN104657785 A CN 104657785A
Authority
CN
China
Prior art keywords
maintenance
maintenance rate
rate
working field
minimum
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
Application number
CN201510037802.4A
Other languages
Chinese (zh)
Other versions
CN104657785B (en
Inventor
荣德生
贺莹
崔铁军
赫飞
马恒
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Liaoning Technical University
Original Assignee
Liaoning Technical University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Liaoning Technical University filed Critical Liaoning Technical University
Priority to CN201510037802.4A priority Critical patent/CN104657785B/en
Publication of CN104657785A publication Critical patent/CN104657785A/en
Application granted granted Critical
Publication of CN104657785B publication Critical patent/CN104657785B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Marketing (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Liquid Crystal Substances (AREA)

Abstract

The invention discloses a method for determining and optimizing a system maintenance rate. The method is characterized in that the maintenance rate is adopted to ensure the system availability when a storage element and the element failure rate are affected by the working environment, the system is shown by using a dynamic fault tree, and the distribution of the element failure rate is determined by using the space fault tree theory to further determine the distribution of the element maintenance rate. The method comprises the following steps: solving a subtree and the system, determining the distribution of the element maintenance rate after giving the system availability, and determining the maintenance rate under different optimization objectives. The method can be used for determining and optimizing the system maintenance rate.

Description

A kind of method that system maintenance rate is determined and optimized
Technical field
The present invention relates to safety system engineering, particularly relate to system maintenance rate and determine and optimize.
Background technology
In reality, generally wish that system is macroscopically reaching certain target, as the reliability, availability, failure rate, total maintenance cost etc. of system.The realization of system macro-goal, is difficult to ensure from the general level of system, should by controlling to the primary element parameter of composition system the target ensureing system, and these parameters comprise: the crash rate, maintenance rate, maintenance cost etc. of element.Parameter as part failure rate is that element nature determines, user cannot change; And maintenance rate can adjust at work, namely reach some macro-goal of system by the adjustment of maintenance rate.Be generally a definite value for part failure rate, but in fact a lot of part failure rate is subject to the impact of working environment, is namely become crash rate, as temperature, working time, air pressure etc.Another problem is modern system is ensure that reliability all can take spare part strategy.So how component maintenance rate in certainty annuity after consideration the problems referred to above, thus the realization of the system of guarantee macro-goal just becomes problem.
According to the research to system reliability, the change crash rate that usage space fault tree theory represents element is proposed, use dynamic fault tree theory to represent contacting containing spare part system architecture and system macro-goal and component parameters, thus the component maintenance rate being met requirement distribute.And expect to obtain corresponding component maintenance rate distribution for system performance in three kinds of situations in reality.
Summary of the invention
1 space fault tree
Space fault tree (Space Fault Tree, SFT) proposed in 2012, had achieved some achievements in research up to now.The basic theories of space fault tree thinks that system works is among environment, because the composition elementary event of system or the character of physical component determine its fault rate difference worked at different conditions.Such as, as the diode in electrical system, its probability of malfunction is just with working time, working temperature, have direct relation by electric current and voltage etc.If analyzed this system, the working time of each element and the temperature of work accommodation etc. may be all different, and along with the working time of entire system and the change of environment temperature, the probability of malfunction of system is also different.This phenomenon is in esse, but unheeded often, and thinks that probability of malfunction is invariable.
The author attempts the change crash rate using element in SFT expression system.In order to describe SFT theory and analytic process below clearly, list the example of necessary SFT related content and analyzed system.Discuss with regard to simple electrical system, this system is constituted by a diode, and the rated operation of diode affects by several factors, wherein importantly working time tand working temperature c.For the electrical system affected by these two factors as research object.Related definition is as follows:
1) space fault tree (or hyperspace event tree): the probability of happening of elementary event is not fixing, be by nindividual factor determines, such event tree is called multidimensional event tree, represents with T.
2) influence factor of elementary event: make the factor that elementary event probability of happening changes.In this example, trepresent time factor, crepresent temperature factor.
3) fundamental function (fundamental function) of the probability of happening of elementary event: elementary event under the impact of single influence factor, the probability of happening variation characteristic that the change with influence factor shows.It can elementary function, and piecewise function etc., use P x ix () represents, irepresent the iindividual element, xreplace influence factor.As this example ithe temporal characteristics function P of individual original paper t i(t)=1-e -λ t, and temperature profile function P c i(c)=0.5 (cos (2 π c/A)+1), wherein, tfor element service time, λ is cell failure rate, afor temperature variation is divided into.
4) the probability of happening space distribution of elementary event: elementary event exists nunder individual influence factor impact, the probability of happening change that the change with them shows in hyperspace. nindividual influence factor is as separate independent variable, and elementary event probability of happening is as functional value.Use P i(x 1, x 2..., x n) represent, i.e. P i(x 1, x 2..., x n)=1-П (1-P xi i(xi)), wherein i=1,2 ..., n, nfor influence factor number, be P in this example i(t, c)=1-(1-P t i(t)) (1-P c i(c)).
2 Dynamic fault trees
A kind of analysis that the reliability that Dynamic fault tree method is the nineties in 20th century is analysis space station and air-traffic control system by professor J.B.Dugan proposes has the method for the system reliability of dynamic random fault characteristic.Dynamic fault tree method introduces dynamic logic gate on the basis of fault tree, as cold reserve door, hot reserve door, order associated gate, preferential and door etc., for characterization system cold reserve, hot reserve, can repair, the dynamic perfromance such as resource sharing.
Here adopt Markov state transition matrix to process problem, comprise analytical method and matrix iteration.When calculating the repaiied reliability index of single system, adopt analytical method; Calculate comparatively complication system time, especially application matrix process of iteration when the fiduciary level of solving system and failure frequency.Analytical method is the feature according to logic gate, sets up the system of equations based on Markov state transition diagram, in conjunction with the feature of logic gate, derives and can obtain the expression formula of reliability index, directly apply mechanically the method calculating reliability index.Matrix iteration is probability matrix and the systematic state transfer matrix multiple iteration of foundation system, solves the probability of different conditions residing for given time system, in conjunction with normal working probability, the malfunction probability of the feature compartment system of Different Logic door.Whole dynamic fault tree model is finally utilized to carry out each reliability index of evaluating system.
λcrash rate, μit is maintenance rate.The function of each logic gate is respectively: with door: the incoming event of and if only if door x, ywhen all occurring, the outgoing event of door zoccur; Or door: when the incoming event of door x 1, x 2, x 3has 1 generation at least, the outgoing event of door zoccur; Cold reserve door: primary input event xin running order, stand-by equipment ybe in cold standby state, only when master/slave device all fault time, the outgoing event of door zoccur; Hot reserve door: primary input event xin running order, stand-by equipment ybe in hot stand-by duty, only when master/slave device all fault time, the outgoing event of door zoccur.
In 3 systems, the maintenance rate of element is determined
First studied Dynamic fault tree is provided, as shown in Figure 1.
3.1 x 1with x 2subnumber solves
x 1subtree module is the hot standby combination of element, and the crash rate of element is λ, maintenance rate is μ. define its shape space: state 0 represents that 2 modules all normally work, system worked well; Shape 1 represents in 2 modules, and one lost efficacy in maintenance, and another module normally works, system worked well; State 2 represents that 2 modules all lost efficacy, and a module is in repairing, and another module is to be repaired, thrashing.
According to the feature of probability in conjunction with hot reserve door, the expression formula formula (1) as shown in Figure 2 of each reliability index of deriving to obtain
In formula (1), availability awhen expression system reaches steady operational status can probability.Failure frequency is m( t) refer to [0, t] the mean failure rate number of times of system in the time, be the failure-frequency of system in the unit interval.
3.2 tsolve
System tby or door connect lower floor event.Definition status space is: state 0 is that 2 modules are all normal, system worked well; State 1 is x 1subtree module failure is being repaired, x 2subtree module is normal, tlost efficacy; State 2 is x 2subtree module failure is being repaired, x 1subtree module is normal, tlost efficacy.
Combine or the feature of door according to probability, the expression formula of each reliability index as shown in Figure 3 shown in formula (2) of deriving to obtain, in formula, Λ= λ 1+ λ 2.
After 3.3 given system availabilities, the distribution of component maintenance rate is determined
If system availability t a=0.8, ask μ e1E2and μ e3E4, due to e 1with e 2be x 1hot reserve event, use μ e1E2represent e 1with e 2maintenance rate (element x 1maintenance rate), μ e3E4in like manner define.By in formula (2) a= t aavailability known, 1/TA=1+ λ x1/ μ x1+ λ x2/ μ x2, wherein λ x1represent x 1having in hot reserve situation ( e 1e 2) crash rate, λ x2in like manner define; μ x1represent x 1having in hot reserve situation ( e 1e 2) maintenance rate, μ x2in like manner define.Know λ again x1/ μ x1=(1/MUT e1E2)/(1/MDT e1E2), wherein MUT e1E2represent E 1and E 2average operation time, MDT e1E2represent E 1and E 2average shut down time, according to formula (1), obtain λ x1/ μ x1=1/ (μ e1E2/ λ e1E2+ 0.5 (μ e1E2/ λ e1E2) 2), λ in formula e1E2represent e 1with e 2maintenance rate (element x 1maintenance rate), λ e3E4in like manner define.For separating the problems referred to above, introduce variable k, k=(λ x1/ μ x1): (λ x2/ μ x2), consider than symmetry to facilitate research, if
k∈{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1,1/0.9,1/0.8,1/0.7,1/0.6,1/0.5,1/0.4,1/0.3,1/0.2,1/0.1}。Arrange said process and obtain formula (3) as shown in Figure 4.
If the working field of element, namely the variation range of condition of work be A total={ t ∈ [0,100] sky ∩ c ∈ [0,50] DEG C }, namely the time of system works is 100 days, and operating temperature range is 0 to 50 DEG C.Discuss according to first segment, the failure probability distributions λ under the fault tree state of space e1E2and λ e3E4(namely x 1, x 2) .so can according to λ e1E2and λ e3E4with formula (3), draw this Dynamic fault tree and exist k=1, t aμ when=0.8 e1E2and μ e3E4distribution plan.
Meet system availability as seen t a=0.8, kunder=1 condition, for system element x 1hot reserve event e 1, e 2maintenance rate to meet in working field maintenance rate distribution; And x 2meet maintenance rate distribution, such system can reach t athe macro-goal of=0.8.
The determination of maintenance rate under 4 Different Optimization targets
First three kinds of in esse system optimization problems are proposed, 1) when research range (working field) is determined, whole system maintenance rate summation is minimum.The meaning of this actual demand wishes that maintenance frequency is minimum in whole working field, and maintenance frequency minimum like this can reduce shut down time, can reduce maintenance cost simultaneously.2) in Practical Project, generally all can a given acceptable minimal maintenance rate, just implement maintenance when the maintenance rate of element exceedes minimal maintenance rate, or standby preparations of maintenance personal is keeped in repair.Generally wish that system is in whole working field, the region being greater than minimal maintenance rate is the smaller the better, and then minimizing maintenance personal's waiting time improves maintenance efficiency.3) when the expense of element dissimilar in maintenance system is different, maintenance rates different between element can cause system maintenance total expensess different in working field, certainly more low better.Certainly above-mentioned 3 all will ensure that system held is on certain availability basis, otherwise nonsensical.
For Section of three system mentioned, due to t a=0.8, and λ e1E2and λ e3E4to know, so determine that the key of maintenance rate depends on variable k.Due to 1/TA=1+ λ x1/ μ x1+ λ x2/ μ x2with k=(λ x1/ μ x1): (λ x2/ μ x2), namely exist t awhen fixing, krepresent a kind of distributional effects, so different distribution ( kdifferent) different μ can be brought e1E2/ λ e1E2and μ e3E4/ λ e3E4, so by regulating kunder can meeting the condition of above-mentioned three problems, determine the μ in working field e1E2and μ e3E4.
4.1 maintenance rate distributions when asking maintenance rate summation minimum
For first problem, make A maintenance rate minimum μm of in always={ t ∈ [0,100] sky ∩ c ∈ [0,50] DEG C } in working field, it defines formula (4) as shown in Figure 5.
4.2 ask the minimum zone of specifying maintenance rate
If the tolerable maintenance rate of system, so will determine μ in working field e1E2and μ e3E4be greater than respectively 2 scope minimum time kvalue.Method is the whole working field of traversal, kto μ time different e1E2and μ e3E4the region being greater than 2 counts, and count results reckling is corresponding krequired by value is.
4.3 maintenance rate distributions when asking total upkeep cost minimum
In order to be described element expense difference, definition C x1and C x2be respectively element x 1with x 2upkeep cost, total maintenance cost defines as shown in Figure 6 shown in formula (5).
Can according to the C of element x1: C x2value finds corresponding kvalue is to determine μ e1E2and μ e3E4distribution in working field.Such as, if element x 1with x 2upkeep cost be 20 yuan and 100 yuan, i.e. C x1: C x2=2:10, so kwhen=0.3, the maintenance cost of entire system is minimum, the availability of certain system t a=0.8.
Accompanying drawing explanation
The Dynamic fault tree of Fig. 1 system.
Fig. 2 formula (1).
Fig. 3 formula (2).
Fig. 4 formula (3).
Fig. 5 formula (4).
Fig. 6 formula (5).
Embodiment
1 space fault tree
Space fault tree (Space Fault Tree, SFT) proposed in 2012, had achieved some achievements in research up to now.The basic theories of space fault tree thinks that system works is among environment, because the composition elementary event of system or the character of physical component determine its fault rate difference worked at different conditions.Such as, as the diode in electrical system, its probability of malfunction is just with working time, working temperature, have direct relation by electric current and voltage etc.If analyzed this system, the working time of each element and the temperature of work accommodation etc. may be all different, and along with the working time of entire system and the change of environment temperature, the probability of malfunction of system is also different.This phenomenon is in esse, but unheeded often, and thinks that probability of malfunction is invariable.
The author attempts the change crash rate using element in SFT expression system.In order to describe SFT theory and analytic process below clearly, list the example of necessary SFT related content and analyzed system.Discuss with regard to simple electrical system, this system is constituted by a diode, and the rated operation of diode affects by several factors, wherein importantly working time tand working temperature c.For the electrical system affected by these two factors as research object.Related definition is as follows:
1) space fault tree (or hyperspace event tree): the probability of happening of elementary event is not fixing, be by nindividual factor determines, such event tree is called multidimensional event tree, represents with T.
2) influence factor of elementary event: make the factor that elementary event probability of happening changes.In this example, trepresent time factor, crepresent temperature factor.
3) fundamental function (fundamental function) of the probability of happening of elementary event: elementary event under the impact of single influence factor, the probability of happening variation characteristic that the change with influence factor shows.It can elementary function, and piecewise function etc., use P x ix () represents, irepresent the iindividual element, xreplace influence factor.As this example ithe temporal characteristics function P of individual original paper t i(t)=1-e -λ t, and temperature profile function P c i(c)=0.5 (cos (2 π c/A)+1), wherein, tfor element service time, λ is cell failure rate, afor temperature variation is divided into.
4) the probability of happening space distribution of elementary event: elementary event exists nunder individual influence factor impact, the probability of happening change that the change with them shows in hyperspace. nindividual influence factor is as separate independent variable, and elementary event probability of happening is as functional value.Use P i(x 1, x 2..., x n) represent, i.e. P i(x 1, x 2..., x n)=1-П (1-P xi i(xi)), wherein i=1,2 ..., n, nfor influence factor number, be P in this example i(t, c)=1-(1-P t i(t)) (1-P c i(c)).
2 Dynamic fault trees
A kind of analysis that the reliability that Dynamic fault tree method is the nineties in 20th century is analysis space station and air-traffic control system by professor J.B.Dugan proposes has the method for the system reliability of dynamic random fault characteristic.Dynamic fault tree method introduces dynamic logic gate on the basis of fault tree, as cold reserve door, hot reserve door, order associated gate, preferential and door etc., for characterization system cold reserve, hot reserve, can repair, the dynamic perfromance such as resource sharing.
Here adopt Markov state transition matrix to process problem, comprise analytical method and matrix iteration.When calculating the repaiied reliability index of single system, adopt analytical method; Calculate comparatively complication system time, especially application matrix process of iteration when the fiduciary level of solving system and failure frequency.Analytical method is the feature according to logic gate, sets up the system of equations based on Markov state transition diagram, in conjunction with the feature of logic gate, derives and can obtain the expression formula of reliability index, directly apply mechanically the method calculating reliability index.Matrix iteration is probability matrix and the systematic state transfer matrix multiple iteration of foundation system, solves the probability of different conditions residing for given time system, in conjunction with normal working probability, the malfunction probability of the feature compartment system of Different Logic door.Whole dynamic fault tree model is finally utilized to carry out each reliability index of evaluating system.
λcrash rate, μit is maintenance rate.The function of each logic gate is respectively: with door: the incoming event of and if only if door x, ywhen all occurring, the outgoing event of door zoccur; Or door: when the incoming event of door x 1, x 2, x 3has 1 generation at least, the outgoing event of door zoccur; Cold reserve door: primary input event xin running order, stand-by equipment ybe in cold standby state, only when master/slave device all fault time, the outgoing event of door zoccur; Hot reserve door: primary input event xin running order, stand-by equipment ybe in hot stand-by duty, only when master/slave device all fault time, the outgoing event of door zoccur.
In 3 systems, the maintenance rate of element is determined
First studied Dynamic fault tree is provided, as shown in Figure 1.
3.1 x 1with x 2subnumber solves
x 1subtree module is the hot standby combination of element, and the crash rate of element is λ, maintenance rate is μ. define its shape space: state 0 represents that 2 modules all normally work, system worked well; Shape 1 represents in 2 modules, and one lost efficacy in maintenance, and another module normally works, system worked well; State 2 represents that 2 modules all lost efficacy, and a module is in repairing, and another module is to be repaired, thrashing.State transition diagram as shown in Figure 1.
According to the feature of probability in conjunction with hot reserve door, the expression formula formula (1) as shown in Figure 2 of each reliability index of deriving to obtain
In formula (1), availability awhen expression system reaches steady operational status can probability.Failure frequency is m( t) refer to [0, t] the mean failure rate number of times of system in the time, be the failure-frequency of system in the unit interval.
3.2 tsolve
System tby or door connect lower floor event.Definition status space is: state 0 is that 2 modules are all normal, system worked well; State 1 is x 1subtree module failure is being repaired, x 2subtree module is normal, tlost efficacy; State 2 is x 2subtree module failure is being repaired, x 1subtree module is normal, tlost efficacy.
Combine or the feature of door according to probability, the expression formula of each reliability index as shown in Figure 3 shown in formula (2) of deriving to obtain, in formula, Λ= λ 1+ λ 2.
After 3.3 given system availabilities, the distribution of component maintenance rate is determined
If system availability t a=0.8, ask μ e1E2and μ e3E4, due to e 1with e 2be x 1hot reserve event, use μ e1E2represent e 1with e 2maintenance rate (element x 1maintenance rate), μ e3E4in like manner define.By in formula (2) a= t aavailability known, 1/TA=1+ λ x1/ μ x1+ λ x2/ μ x2, wherein λ x1represent x 1having in hot reserve situation ( e 1e 2) crash rate, λ x2in like manner define; μ x1represent x 1having in hot reserve situation ( e 1e 2) maintenance rate, μ x2in like manner define.Know λ again x1/ μ x1=(1/MUT e1E2)/(1/MDT e1E2), wherein MUT e1E2represent E 1and E 2average operation time, MDT e1E2represent E 1and E 2average shut down time, according to formula (1), obtain λ x1/ μ x1=1/ (μ e1E2/ λ e1E2+ 0.5 (μ e1E2/ λ e1E2) 2), λ in formula e1E2represent e 1with e 2maintenance rate (element x 1maintenance rate), λ e3E4in like manner define.For separating the problems referred to above, introduce variable k, k=(λ x1/ μ x1): (λ x2/ μ x2), consider than symmetry to facilitate research, if
k∈{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1,1/0.9,1/0.8,1/0.7,1/0.6,1/0.5,1/0.4,1/0.3,1/0.2,1/0.1}。Arrange said process and obtain formula (3) as shown in Figure 4.
If the working field of element, namely the variation range of condition of work be A total={ t ∈ [0,100] sky ∩ c ∈ [0,50] DEG C }, namely the time of system works is 100 days, and operating temperature range is 0 to 50 DEG C.Discuss according to first segment, the failure probability distributions λ under the fault tree state of space e1E2and λ e3E4(namely x 1, x 2) .so can according to λ e1E2and λ e3E4with formula (3), draw this Dynamic fault tree and exist k=1, t aμ when=0.8 e1E2and μ e3E4distribution plan.
Meet system availability as seen t a=0.8, kunder=1 condition, for system element x 1hot reserve event e 1, e 2maintenance rate to meet in working field maintenance rate distribution; And x 2meet maintenance rate distribution, such system can reach t athe macro-goal of=0.8.
The determination of maintenance rate under 4 Different Optimization targets
First three kinds of in esse system optimization problems are proposed, 1) when research range (working field) is determined, whole system maintenance rate summation is minimum.The meaning of this actual demand wishes that maintenance frequency is minimum in whole working field, and maintenance frequency minimum like this can reduce shut down time, can reduce maintenance cost simultaneously.2) in Practical Project, generally all can a given acceptable minimal maintenance rate, just implement maintenance when the maintenance rate of element exceedes minimal maintenance rate, or standby preparations of maintenance personal is keeped in repair.Generally wish that system is in whole working field, the region being greater than minimal maintenance rate is the smaller the better, and then minimizing maintenance personal's waiting time improves maintenance efficiency.3) when the expense of element dissimilar in maintenance system is different, maintenance rates different between element can cause system maintenance total expensess different in working field, certainly more low better.Certainly above-mentioned 3 all will ensure that system held is on certain availability basis, otherwise nonsensical.
For Section of three system mentioned, due to t a=0.8, and λ e1E2and λ e3E4to know, so determine that the key of maintenance rate depends on variable k.Due to 1/TA=1+ λ x1/ μ x1+ λ x2/ μ x2with k=(λ x1/ μ x1): (λ x2/ μ x2), namely exist t awhen fixing, krepresent a kind of distributional effects, so different distribution ( kdifferent) different μ can be brought e1E2/ λ e1E2and μ e3E4/ λ e3E4, so by regulating kunder can meeting the condition of above-mentioned three problems, determine the μ in working field e1E2and μ e3E4.
4.1 maintenance rate distributions when asking maintenance rate summation minimum
For first problem, make A maintenance rate minimum μm of in always={ t ∈ [0,100] sky ∩ c ∈ [0,50] DEG C } in working field, it defines formula (4) as shown in Figure 5.
4.2 ask the minimum zone of specifying maintenance rate
If the tolerable maintenance rate of system, so will determine μ in working field e1E2and μ e3E4be greater than respectively 2 scope minimum time kvalue.Method is the whole working field of traversal, kto μ time different e1E2and μ e3E4the region being greater than 2 counts, and count results reckling is corresponding krequired by value is.
4.3 maintenance rate distributions when asking total upkeep cost minimum
In order to be described element expense difference, definition C x1and C x2be respectively element x 1with x 2upkeep cost, total maintenance cost defines as shown in Figure 6 shown in formula (5).
Can according to the C of element x1: C x2value finds corresponding kvalue is to determine μ e1E2and μ e3E4distribution in working field.Such as, if element x 1with x 2upkeep cost be 20 yuan and 100 yuan, i.e. C x1: C x2=2:10, so kwhen=0.3, the maintenance cost of entire system is minimum, the availability of certain system t a=0.8.

Claims (3)

1. the system maintenance rate method determining and optimize, it is characterized in that, when affecting by working environment containing storage element and part failure rate for understanding, for ensureing the maintenance rate that system availability is taked, this system is used dynamic fault tree representation, usage space fault tree theory determines that its part failure rate distributes, and then determines the distribution of component maintenance rate; It comprises the steps: that subtree solves, solving of system, and after given system availability, the distribution of component maintenance rate is determined, the determination of maintenance rate under Different Optimization target; The present invention can be used for system maintenance rate and determines and optimize.
2. the determination of maintenance rate under Different Optimization target according to claim 1, it is characterized in that, 1) when research range (working field) is determined, whole system maintenance rate summation is minimum, the meaning of this actual demand wishes that maintenance frequency is minimum in whole working field, maintenance frequency minimum like this can reduce shut down time, can reduce maintenance cost simultaneously; 2) in Practical Project, general all can a given acceptable minimal maintenance rate, maintenance is just implemented when the maintenance rate of element exceedes minimal maintenance rate, or the standby preparation maintenance of maintenance personal, generally wish that system is in whole working field, the region being greater than minimal maintenance rate is the smaller the better, and then minimizing maintenance personal's waiting time improves maintenance efficiency; 3) when the expense of element dissimilar in maintenance system is different, maintenance rates different between element can cause system maintenance total expensess different in working field, certainly more low better.
3. the determination of maintenance rate under Different Optimization target according to claim 1, it is characterized in that, if tolerable maintenance rate=2 of system, so will determine in working field μ E1E2 and μ E3E4 be greater than respectively 2 scope minimum time k value, method is the whole working field of traversal, when k is different, the region that μ E1E2 and μ E3E4 is greater than 2 is counted, required by the k value that count results reckling is corresponding is.
CN201510037802.4A 2015-01-26 2015-01-26 A kind of system maintenance rate determines and the method for optimization Active CN104657785B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510037802.4A CN104657785B (en) 2015-01-26 2015-01-26 A kind of system maintenance rate determines and the method for optimization

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510037802.4A CN104657785B (en) 2015-01-26 2015-01-26 A kind of system maintenance rate determines and the method for optimization

Publications (2)

Publication Number Publication Date
CN104657785A true CN104657785A (en) 2015-05-27
CN104657785B CN104657785B (en) 2018-01-12

Family

ID=53248882

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510037802.4A Active CN104657785B (en) 2015-01-26 2015-01-26 A kind of system maintenance rate determines and the method for optimization

Country Status (1)

Country Link
CN (1) CN104657785B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106055856A (en) * 2015-09-15 2016-10-26 辽宁工程技术大学 Method for determining component fault probability based on discrete data
CN106529693A (en) * 2015-09-14 2017-03-22 辽宁工程技术大学 Method for determining and optimizing system maintenance rate
CN106527398A (en) * 2016-11-14 2017-03-22 辽宁工程技术大学 Element maintenance rate distribution determining method in different electric element forming systems
CN106777464A (en) * 2016-11-14 2017-05-31 辽宁工程技术大学 Component maintenance rate distribution determination method in a kind of similar electrical equipment system

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102419799A (en) * 2012-01-10 2012-04-18 杜玉龙 Fire fighting system reliability analysis and calculation method
CN103324795A (en) * 2013-06-21 2013-09-25 南方电网科学研究院有限责任公司 Direct current system reliability assessment method considering station power utilization influence
CN103903064A (en) * 2014-03-26 2014-07-02 东南大学 Maintenance strategy optimization system used for multi-state system based on space reduction
CN103955616A (en) * 2014-05-04 2014-07-30 兰州交通大学 Method for estimating reliability of ATP (Automatic Train Protection) system of CTCS-3 (Chinese Train Control System of Level 3) based on dynamic fault tree

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102419799A (en) * 2012-01-10 2012-04-18 杜玉龙 Fire fighting system reliability analysis and calculation method
CN103324795A (en) * 2013-06-21 2013-09-25 南方电网科学研究院有限责任公司 Direct current system reliability assessment method considering station power utilization influence
CN103903064A (en) * 2014-03-26 2014-07-02 东南大学 Maintenance strategy optimization system used for multi-state system based on space reduction
CN103955616A (en) * 2014-05-04 2014-07-30 兰州交通大学 Method for estimating reliability of ATP (Automatic Train Protection) system of CTCS-3 (Chinese Train Control System of Level 3) based on dynamic fault tree

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
张文韬 等: ""基于动态故障树的CTCS-3级ATP***可靠性分析"", 《工程设计学报》 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106529693A (en) * 2015-09-14 2017-03-22 辽宁工程技术大学 Method for determining and optimizing system maintenance rate
CN106055856A (en) * 2015-09-15 2016-10-26 辽宁工程技术大学 Method for determining component fault probability based on discrete data
CN106055856B (en) * 2015-09-15 2018-08-31 辽宁工程技术大学 A kind of element fault probability based on discrete data determines method
CN106527398A (en) * 2016-11-14 2017-03-22 辽宁工程技术大学 Element maintenance rate distribution determining method in different electric element forming systems
CN106777464A (en) * 2016-11-14 2017-05-31 辽宁工程技术大学 Component maintenance rate distribution determination method in a kind of similar electrical equipment system
CN106777464B (en) * 2016-11-14 2019-11-29 辽宁工程技术大学 Component maintenance rate distribution determination method in a kind of similar electrical component system

Also Published As

Publication number Publication date
CN104657785B (en) 2018-01-12

Similar Documents

Publication Publication Date Title
CN104657785A (en) Method for determining and optimizing system maintenance rate
US10355478B2 (en) System and method for asset health monitoring using multi-dimensional risk assessment
Hirata et al. Real-time pricing leading to optimal operation under distributed decision makings
CA2908965A1 (en) Multi-farm wind power generation system
DE112018000125B4 (en) Quantifying a combined impact of interdependent uncertain resources in an electric power grid
CN106355308B (en) A method of wind power integration system core equipment is recognized based on decision tree
CN104700326A (en) Power distribution network risk assessment method
EP2381094A1 (en) Energy network and control thereof
CN110110933A (en) A kind of maintenance circle optimization method of intelligent substation protection system
Yusuf Comparative analysis of profit between three dissimilar repairable redundant systems using supporting external device for operation
Wiest et al. Dynamic curtailment method for renewable energy sources in distribution grid planning
CN106971239B (en) Improved reference power grid evaluation method
Sun et al. Short-term reliability evaluation using control variable based dagger sampling method
Mostafa et al. Optimal distribution systems operation using smart matching scheme (SMS) for smart grid applications
Grigoras et al. Energy losses estimation in electrical distribution networks with a decision trees-based algorithm
Konishi et al. Optimal allocation of photovoltaic systems and energy storage systems considering constraints of both transmission and distribution systems
Zafir et al. Relationship between loss of load expectation and reserve margin for optimal generation planning
Bento et al. Analysis of the load growth direction variation in the dynamic security assessment
Lei et al. Reliability analysis of modern substations considering cyber link failures
Aziz et al. Enhanced PSO for network reconfiguration under different fault locations in smart grids
Ciapessoni et al. Effect of renewable and load uncertainties on the assessment of power system operational risk
Alpcan et al. Assessment of voltage stability risks under intermittent renewable generation
CN110377005B (en) TLD medium-short-time fault dispatching interval determining method based on Markov model
CN109494718B (en) Damping-considered emergency control method for complex power system
CN106529693A (en) Method for determining and optimizing system maintenance rate

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
CB03 Change of inventor or designer information

Inventor after: Cui Tiejun

Inventor after: Li Shasha

Inventor after: Han Guang

Inventor after: Wang Wei

Inventor before: Rong Desheng

Inventor before: He Ying

Inventor before: Cui Tiejun

Inventor before: He Fei

Inventor before: Ma Heng

COR Change of bibliographic data
GR01 Patent grant
GR01 Patent grant
CP02 Change in the address of a patent holder

Address after: 125105 Longwan South Street, Huludao, Huludao, Liaoning

Patentee after: Liaoning Technical University

Address before: No. 47, Zhonghua Road, Xihe District, Fuxin, Liaoning Province

Patentee before: Liaoning Technical University

CP02 Change in the address of a patent holder