CN106777819A - A kind of Normal Type has the computational methods of part replacement cycle in longevity - Google Patents
A kind of Normal Type has the computational methods of part replacement cycle in longevity Download PDFInfo
- Publication number
- CN106777819A CN106777819A CN201710040795.2A CN201710040795A CN106777819A CN 106777819 A CN106777819 A CN 106777819A CN 201710040795 A CN201710040795 A CN 201710040795A CN 106777819 A CN106777819 A CN 106777819A
- Authority
- CN
- China
- Prior art keywords
- longevity
- availability
- replacement cycle
- spare parts
- rep
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/04—Ageing analysis or optimisation against ageing
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Complex Calculations (AREA)
Abstract
The invention discloses the computational methods that a kind of Normal Type has the part replacement cycle in longevity, this computational methods mainly comprises the following steps:Calculate to longevity replacement probability, calculating uses availability, and utilizes using Calculation of Availability spare parts demand amount, wherein calculate use in availability, including following two important core procedures:Step 1):Having the working life of longevity part to the Normal Type, to carry out normal state equivalent;Step 2):According to the step 1) the normal state equivalent parameters obtained calculates and uses availability, by the use Calculation of Availability spare parts demand amount.According to the computational methods that the present invention is realized, the computational methods not made a distinction to the life-span for having longevity part and working life in the prior art are different from, the accuracy of result of calculation can be significantly increased.
Description
Technical field
The invention belongs to there is longevity part to change evaluation areas, it is related to a kind of Normal Type there are the computational methods of part replacement cycle in longevity.
Background technology
It is to define preventative maintenance to change or scrap the part in time limit and it is anticipated that the part of service life to have longevity part, also known as
Limit longevity part.In aviation field, aircraft spare parts are generally divided into initial spares, replenished spares and have longevity spare part.Can be had using there is longevity part
Effect ground trouble saving occurs, therefore the use problem for especially having longevity part in aviation field has great practice significance.Change week
Phase is an important parameter for having longevity part, takes which kind of method to obtain the scientific and rational replacement cycle, at present domestic correlation
Research is few.
The life-span and working life for having longevity part are two different concepts, and the life-span is not consider the replacement cycle, the unit from
Start working until what is hindered for some reason and scrap dies naturally.Working life considers the influence of replacement cycle, it be
In replacement cycle, unit from start working until hinder for some reason and scrap or because reach the time limit change this for a period of time, work
Make the no more than replacement cycle in life-span.
The characteristics of having longevity part maximum is to try hard to trouble saving, is tieed up after before failure occurs rather than failure
Repair, this equipment very serious to consequence after the generation of some failures is especially meaningful, such as the key components and parts on aircraft.
When it is determined that there is the replacement cycle of longevity part, two problems can be considered:
1) longevity part works the probability normally changed to the prescribed time-limit (i.e. replacement cycle) (hereinafter referred to as to longevity replacing generally
Rate) index request can be met
2) in the case where Combat readiness index request is met, spare part can as few as possible be configured
For problem 1), having longevity part to work, to be changed to the time limit be its optimal working condition, is hindered for some reason and replacing is then
Undesirable, consequence may be very serious.Obviously, shorter when the replacement cycle, the possibility broken down in the time limit is lower, arrives
Longevity replacement probability is higher.
For problem 2), when the replacement cycle more in short-term, it is possible to need more spare parts.Problem 2) from spare parts purchasing expense
Angle describe select certain replacement cycle financial cost.Using availability be the accumulated operating time with the support mission time it
Between ratio, be a kind of common index for reflecting Military Equipment Operational Readiness, be also that the top layer of the leading spare parts support work of the military refers to
One of mark.
Thus, it is existing at present under the background more than, it is especially desirable to propose a kind of method calculated the replacement cycle
Solution in the middle of technology is exactly come to problem 1 using empirical value) and problem 2) parameter calculate, in such case
Under, (reasonability is primarily referred to as the balance of cost absorbing and benefit, and wherein cost is embodied in spare part to cause the reasonability of replacement cycle
Buying expenses, income is embodied in longevity replacement probability) be difficult to ensure that, it is quantitative to calculate substantially impossible.
The content of the invention
For the disadvantages described above or Improvement requirement of prior art, there is the part replacement cycle in longevity the invention provides a kind of Normal Type
Computational methods, it is characterised in that the method comprises the following steps
Step one:Calculate to longevity replacement probability R (Trep):
Wherein, TrepTo treat the selected replacement cycle, μ, σ have part longevity, Parameters of Normal Distribution life-span for described;π is pi
Constant;
Step 2:Calculating uses availability, and using using Calculation of Availability spare parts demand amount, the wherein step includes
Following sub-step:
Step 1):Having the working life of longevity part to the Normal Type, to carry out normal state equivalent, including following sub-step:
Step 1.1):Equal difference array [x of the selection comprising m numbers in the range of (0, μ+4 σ)1,…,xm], 1≤i≤m;
Step 1.2):Traversal calculates f1(xi),
Step 1.3):Traversal is calculatedTo 100 × f2(xi) carry out round after obtain
N2(xi);
Step 1.4):In the equal difference array [x1,…,xm] in find closest to TrepSeveral xr, i.e. xr≤TrepAnd xr+1
> Trep;
Step 1.5):By N2(xi) obtain array [N3(x1),…N3(xr)],
Step 1.6):The generation equal difference array [μ in scope (0, μ)1,…,μn], in scope (0,0.4 μ)
Generation equal difference array [σ1,…,σq];
Step 1.7):In the way of following traversal, matrix of the generation comprising n × q rows
Wherein
Step 1.8):To the weight coefficient group [P1 of the matrix1,…,P1n·q] initialized, make
Step 1.9):To the weight coefficient group [P11,…,P1n·q] it is circulated renewal, sub-step specific as follows:
Step 1.9.1):Make i1=1, wherein 1≤i1≤r;
Step 1.9.2):Make x2=xi1, i2=1, wherein 1≤i2≤n·q;
Step 1.9.3):To gi2Traversal calculating is carried out, is obtained
Step 1.9.4):Update i2, make i2=i2+ 1, if i2≤ nq, then perform 1.9.3), otherwise perform 1.9.5);
Step 1.9.5):Update weight coefficient group [P11,…,P1n·q], order
Step 1.9.6):Update i1, make i1=i1+1;If i1≤ r, then perform 1.9.2), otherwise perform 1.10);
Step 1.10) according to the weight coefficient group [P1 after the renewal1,…,P1n·q], calculate it is equivalent go out normal state ginseng
Number μ ', σ ':
Step 2):According to the step 1) the normal state equivalent parameters obtained calculates and uses availability, by institute
State using Calculation of Availability spare parts demand amount:
It is calculated as follows and uses availability Pa, set the threshold value of the use availability so that PaMore than or equal to the threshold
The Z values of value are the spare parts demand amount for calculating;
Wherein, b is the spare parts demand quantitative change amount, TwIt it is the support mission time, the support mission time refers to described standby
Expected accumulated operating time of the part when a certain task is completed;
Step 3:The selection replacement cycle
Index request is not less than to longevity replacement probability using what the step one was obtained, according to the step 2) obtain most
Few spare parts demand amount, treats to determine the replacement cycle in the selected replacement cycle described.
In general, by the contemplated above technical scheme of the present invention compared with prior art, algorithm for design is quantified
Calculate to longevity replacement probability and spare part and use availability two indices, the two indices more than select the replacement cycle;
Wherein to the application reliability degree calculation method for relating generally to of longevity replacement probability, because to the mathematics of longevity replacement probability
Essence is exactly reliability, and this method application is come actually also to have reached accurate calculating effect;
Wherein spare part mainly employs that to carry out normal state to the working life of spare part equivalent using the computational methods of availability,
The life-span and working life that have longevity part are not made a distinction in the prior art, more be may not realize that life-span distribution and worked
Life-span distribution can be what is differed, also just not allow to be readily conceivable that that normal state is carried out to working life is equivalent, and the present invention is contemplated and adopted
Calculated with the equivalent method of normal state and use availability, see that result of calculation accuracy is improved in implementation.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the computational methods that the Normal Type realized according to the present invention has the part replacement cycle in longevity.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that instantiation described herein is only used to explain the present invention, not
For limiting the present invention.As long as additionally, technical characteristic involved in invention described below each implementation method that
Conflict is not constituted between this can be just mutually combined.
Specifically, there are the computational methods of the replacement cycle of longevity part the invention provides a kind of Normal Type, normally use
Mechanical parts life-span general Normal Distribution, such as collector ring, gear-box, decelerator.The analysis pair that emphasis is directed to likes the life-span
Normal Distribution has longevity part, is designated as N (μ, σ2), the replacement cycle is designated as Trep, the support mission time is designated as Tw, the replacement cycle is
Refer to time of the spare part from starting working to being replaced for the replacement cycle, the replacing reaches one not because failure because of it
The working time of individual regulation;The support mission time refers to just expected accumulated operating time of the spare part when a certain task is completed.
Reliability is a conventional spare part reliability index, and it is defined as:Spare part under conditions of regulation and regulation
In time t, the probability of predetermined function is completed, represented with R (t).From definition:R (t)=P (T>T), wherein T refers to the spare part longevity
Life.For life-span T Normal Distribution N (μ, σ2) spare part for, to longevity replacement probability be equal in replacement cycle TrepInterior reliability
Work, trouble-proof probability R (Trep), such as formula (1):
The use of the essence of Calculation of Availability is a guarantee recruitment evaluation problem, i.e.,:Rule are distributed when the life-span of known units
When rule, replacement cycle, spare part quantity and support mission cycle, calculating can be quantified and use availability, once can quantify exactly
Calculating uses availability, it is possible to calculate the spare parts demand amount for meeting spare parts support index request.
The alternate maintenance for having longevity part has two kinds:Changed to the longevity and failure replacement, the former refers to have longevity part in work to its rule
Periodically limit has not occurred the replacing that failure needs to carry out preventative maintenance and carries out, and the latter refers to have longevity part not work to the regulation phase
The replacing that limit is carried out with regard to having broken down.If only being changed to the longevity, as long as preparingPart spare part just expire by energy 100%
Sufficient spare parts demand.But there is longevity part to be likely to occur failure in the specified period, therefore only preparePart can not reliably expire
Sufficient spare parts demand.This has caused that longevity part spare parts support recruitment evaluation works becomes complexity.
Having being changed to the longevity for longevity part means its working life this moment stops abruptly in the replacement cycle.This and normal state are divided
" concentration " failure (99.73% normal variate falls in the range of (μ -3 σ, μ+3 σ)) of cloth has similarity in phenomenon, can be with
Trial carrys out approximate description with normal distribution the distribution of longevity part working life, recycles Normal Type spare parts support computational methods to count
Calculation uses availability.
As shown in figure 1, the computational methods of the replacement cycle realized according to the present invention, mainly comprise the following steps:
First, calculate to longevity replacement probability:
2nd, calculate and be made up of following two parts using the method for availability:
1) to carry out normal state to the working life for having longevity part equivalent
Comprise the following steps that:
1.1) equal difference array [x of the selection comprising m numbers in the range of (0, μ+4 σ)1,…,xm], it is proposed thatxmThe σ of≤μ+4 and1≤i≤m;I.e. more than above-mentioned 99.73%
Selected within the scope of security probability, certainly, the selection of equal difference not considered critical as above, equal difference spacing m suggestions are not small
In 20;
1.2) traversal calculates f1(xi),Obtain xiThe frequency of appearance;
1.3) traversal is calculatedTo 100 × f2(xi) carry out round after obtain N2
(xi), as xiThe number of times of appearance;
1.4) in array [x1,…,xm] in find closest to TrepSeveral xr, i.e. xr≤TrepAnd xr+1> Trep;
1.5) by N2(xi) obtain array [N3(x1),…N3(xr)],The parameter is anti-
Reflect xjThe number of times of appearance;I.e. equivalent to working life xjThe number of times of appearance is life-span xiThe a subset of the number of times of appearance;
1.6) the generation equal difference array [μ in scope (0, μ)1,…,μn], it is proposed that
μn≤ μ and μn+ d μ > μ;The selection of equal difference not considered critical as above,
Equal difference spacing n suggestions are not less than 10;
The generation equal difference array [σ in scope (0,0.4 μ)1,…,σq], it is proposed that
σq≤ 0.4 μ and σqThe μ of+d σ > 0.4;The selection of equal difference not considered critical as above, equal difference spacing q suggestion be not less than 50;
1.7) in the way of following traversal, matrix of the generation comprising n × q rows
Above-mentioned matrix is wherein obtained using following program
Make k=1
1.8) to weight coefficient group [P11,…,P1n·q] initialized, make
1.9) to weight coefficient group [P11,…,P1n·q] renewal is circulated, it is specific as follows:
1.9.1 i) is made1=1, wherein 1≤i1≤r;
1.9.2) makei2=1, wherein 1≤i2≤n·q;
1.9.3) to i2Traversal calculating is carried out, is obtained
1.9.4 i) is updated2, make i2=i2+ 1, if i2≤ nq, then perform 1.9.3), otherwise perform 1.9.5);
1.9.5 weight coefficient group [P1) is updated1,…,P1n·q], order
1.9.6 i) is updated1, make i1=i1+1;If i1≤ r, then perform 1.9.2), otherwise perform 1.10).
1.10) according to weight coefficient group [P11,…,P1n·q], calculate it is equivalent go out normal state parameter μ1、σ1:
2) according to use Calculation of Availability spare parts demand amount
When b spare part is configured, can be calculated with formula (2) and use availability Pa.Spare part is calculated to can be used to calculate spare parts demand
Amount:Make s increases one by one since 0, until certain Z value so that PaThe use availability index of >=regulation, the Z values are and are asked for perfection
Part demand.
It is assumed that:Life-span T Normal Distribution N (μ, the σ of certain unit2), it is stipulated that its replacement cycle is Trep, during support mission
Between be Tw, it is desirable to index request must not be less than using availability, spare parts demand amount is designated as Z.
3rd, the replacement cycle is selected
Index request is not less than to longevity replacement probability using what step one was obtained, under the conditions of this is met, according to step
2) the minimum spare parts demand amount for obtaining then can determine that the replacement cycle.
It is assumed that the replacement cycle of candidate is 100,200,300,400,500, it is desirable to must not be less than 0.8 to longevity replacement probability,
According to step one obtain it is corresponding be respectively 0.95,0.9,0.86,0.78,0.65 to longevity replacement probability, find to reduce and change week
Phase scope is 100,200,300, and according to step 2) to obtain corresponding spare parts demand amount be 5,4,3, this when of selection 300 is made
It is the replacement cycle for determining.
In order to verify the validity of the above method, the spare parts support simulation model for having longevity part as follows is set up, carry out emulation and test
Card.The simulation model simulates a support mission process.The idiographic flow of simulation model is as follows:
1) life-span is simulated
Produce 1+Z random number ti, tiNormal Distribution N (μ, σ2);
2) working life is simulated
To this 1+Z random number tiTraversal amendment is carried out, is obtainedModification method such as following formula:
3) analog result is exported
Analog result has 2:Use availability simPaWith the normal ratio simR changed to the longevity in the guarantee phase;SimR determines
Justice is:Within the support mission phase, the ratio between the number of times and total replacing number of times of simulation of simulation to longevity replacing.
CalculateThe use availability degree simP for then simulatingaSuch as following formula:
After the simulation model is run multiple times, to simPaCounted, its averageAs use the mould of availability
Intend result, simR is counted, its averageAs to longevity replacement probability.
The parameter of example 1:Certain spare part life-span Normal Distribution N (μ, σ2), μ=600, σ=130, support mission time
It is Tw=2000h, it is desirable to be not less than 0.95, replacement cycle T using availabilityrepSpan be 200~500h.Emulation knot
Fruit and the result such as table 1 of context of methods.
The simulation result of the example 1 of table 1 and the result of context of methods
If it is required that be not less than 0.85 to longevity replacement probability, as known from Table 1:Selected 450h is above-mentioned time as the replacement cycle
Preferable selection in option, spare parts demand amount now is 4.
The parameter of example 2:Certain cell life Normal Distribution N (μ, σ2), μ=600, σ=230, remaining parameter is with calculation
Example 1.The result of simulation result and context of methods such as table 2.The cell life root variances sigma of example 2 is larger with respect to for its mean μ.
The simulation result of the example 2 of table 2 and the result of context of methods
If it is required that be not less than 0.85 to longevity replacement probability, as known from Table 2:Selected 350h is above-mentioned time as the replacement cycle
Preferable selection in option, spare parts demand amount now is 5.
Tables 1 and 2 represents the smaller and larger both of these case of root variance of cell life respectively.A large amount of simulating, verifying knots
Fruit shows:Result (spare parts demand amount, using availability and to longevity replacement probability) and the emulation being calculated using context of methods
Result is all very close to.Context of methods can make related personnel accurately understand the spare parts purchasing cost and safety of various replacement cycles
In the case of income, auxiliary determines the replacement cycle for having longevity part.
Herein by life-span Normal Distribution have longevity part as a example by, " concentration " failure and convolution using normal distribution can add
Characteristic, the working life that carrying out approximate expression with normal distribution has longevity part is distributed, by quantum chemical method each replacement cycle corresponding peace
Full income and spare parts cost, give a kind of method for aiding in and determining to have the part replacement cycle in longevity.Simulation results show:The party
Method result can accurately reflect the assessment for having the part replacement cycle in longevity to Normal Type.
As it will be easily appreciated by one skilled in the art that the foregoing is only presently preferred embodiments of the present invention, it is not used to
The limitation present invention, all any modification, equivalent and improvement made within the spirit and principles in the present invention etc., all should include
Within protection scope of the present invention.
Claims (1)
1. a kind of Normal Type has the computational methods of part replacement cycle in longevity, it is characterised in that the method comprises the following steps
Step one:Calculate to longevity replacement probability R (Trep):
Wherein, TrepTo treat the selected replacement cycle, μ, σ have part longevity, Parameters of Normal Distribution life-span for described;π is pi constant;
Step 2:Calculating uses availability, and using Calculation of Availability spare parts demand amount is used, the wherein step includes as follows
Sub-step:
Step 1):Having the working life of longevity part to the Normal Type, to carry out normal state equivalent, including following sub-step:
Step 1.1):Equal difference array [x of the selection comprising m numbers in the range of (0, μ+4 σ)1,…,xm], 1≤i≤m;
Step 1.2):Traversal calculates f1(xi),
Step 1.3):Traversal is calculatedTo 100 × f2(xi) carry out round after obtain N2
(xi);
Step 1.4):In the equal difference array [x1,…,xm] in find closest to TrepSeveral xr, i.e. xr≤TrepAnd xr+1> Trep;
Step 1.5):By N2(xi) obtain array [N3(x1),…N3(xr)],Step
1.6):The generation equal difference array [μ in scope (0, μ)1,…,μn], the generation equal difference array [σ in scope (0,0.4 μ)1,…,
σq];
Step 1.7):In the way of following traversal, matrix of the generation comprising n × q rows
Wherein
Step 1.8):To the weight coefficient group [P1 of the matrix1,…,P1n·q] initialized, make
Step 1.9):To the weight coefficient group [P11,…,P1n·q] it is circulated renewal, sub-step specific as follows:
Step 1.9.1):Make i1=1, wherein 1≤i1≤r;
Step 1.9.2):Orderi2=1, wherein 1≤i2≤n·q;
Step 1.9.3):It is rightTraversal calculating is carried out, is obtained
Step 1.9.4):Update i2, make i2=i2+ 1, if i2≤ nq, then perform 1.9.3), otherwise perform 1.9.5);
Step 1.9.5):Update weight coefficient group [P11,…,P1n·q], orderStep
1.9.6):Update i1, make i1=i1+1;If i1≤ r, then perform 1.9.2), otherwise perform 1.10);
Step 1.10) according to the weight coefficient group [P1 after the renewal1,…,P1n·q], calculate it is equivalent go out normal state parameter μ ',
σ′:
Step 2):According to the step 1) the normal state equivalent parameters obtained calculates and uses availability, by the use availability meter
Calculate spare parts demand amount:
It is calculated as follows and uses availability Pa, set the threshold value of the use availability so that PaMore than or equal to the threshold value
Z values are the spare parts demand amount for calculating;
Wherein, b is the spare parts demand quantitative change amount, TwIt it is the support mission time, the support mission time refers to the spare part complete
Into expected accumulated operating time during a certain task;
Step 3:The selection replacement cycle
Using the step one obtain be not less than index request to longevity replacement probability, according to the step 2) obtain it is minimum standby
Part demand, treats to determine the replacement cycle in the selected replacement cycle described.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710040795.2A CN106777819B (en) | 2017-01-20 | 2017-01-20 | Method for calculating replacement period of normal type life-bearing part |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710040795.2A CN106777819B (en) | 2017-01-20 | 2017-01-20 | Method for calculating replacement period of normal type life-bearing part |
Publications (2)
Publication Number | Publication Date |
---|---|
CN106777819A true CN106777819A (en) | 2017-05-31 |
CN106777819B CN106777819B (en) | 2020-05-19 |
Family
ID=58943465
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710040795.2A Active CN106777819B (en) | 2017-01-20 | 2017-01-20 | Method for calculating replacement period of normal type life-bearing part |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106777819B (en) |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108334720A (en) * | 2018-04-09 | 2018-07-27 | 中国人民解放军海军工程大学 | A kind of Normal Type unit spare parts demand amount computational methods under store failure risk |
CN108470250A (en) * | 2018-03-25 | 2018-08-31 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of Normal Type series components |
CN108509390A (en) * | 2018-03-25 | 2018-09-07 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of gamma type series components |
CN108509389A (en) * | 2018-03-25 | 2018-09-07 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of Weibull type series components |
CN108733883A (en) * | 2018-04-16 | 2018-11-02 | 中国人民解放军海军工程大学 | A kind of method of determining Normal Type unit replenished spares demand |
CN109376334A (en) * | 2018-09-17 | 2019-02-22 | 中国人民解放军海军工程大学 | A kind of service life estimation of distribution parameters method of Normal Type unit |
CN109523160A (en) * | 2018-11-15 | 2019-03-26 | 青岛航讯网络技术服务有限公司 | The more normal state assembly of elements spare parts demand amounts of the long-term support mission of larger cargo ships determine method |
CN110727921A (en) * | 2019-09-30 | 2020-01-24 | 中国人民解放军海军工程大学 | Normal type universal part spare part demand calculation method and device |
CN111080104A (en) * | 2019-12-05 | 2020-04-28 | 成都飞机工业(集团)有限责任公司 | Periodic task management scheduling method based on test flight management and control service |
CN116843231A (en) * | 2023-07-20 | 2023-10-03 | 中国人民解放军海军工程大学 | Mechanical equipment use availability quantification method and system considering maintenance time consumption |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1858753A (en) * | 2006-04-18 | 2006-11-08 | 燕山大学 | Simulation technology based on after repair and repair time product effectiveness |
US7200518B1 (en) * | 1998-11-12 | 2007-04-03 | Jan Bryan Smith | Method for assessing plant capacity |
CN103033752A (en) * | 2011-09-30 | 2013-04-10 | 吴昌旭 | Predication method and prolonging method for service life of electric vehicle battery |
CN104657613A (en) * | 2015-02-26 | 2015-05-27 | 电子科技大学 | Estimation method for service life of complex electromechanical system |
-
2017
- 2017-01-20 CN CN201710040795.2A patent/CN106777819B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7200518B1 (en) * | 1998-11-12 | 2007-04-03 | Jan Bryan Smith | Method for assessing plant capacity |
CN1858753A (en) * | 2006-04-18 | 2006-11-08 | 燕山大学 | Simulation technology based on after repair and repair time product effectiveness |
CN103033752A (en) * | 2011-09-30 | 2013-04-10 | 吴昌旭 | Predication method and prolonging method for service life of electric vehicle battery |
CN104657613A (en) * | 2015-02-26 | 2015-05-27 | 电子科技大学 | Estimation method for service life of complex electromechanical system |
Non-Patent Citations (1)
Title |
---|
邵松世 等: "基于寿命周期备件费用的***可靠性优化设计", 《中国工程科学》 * |
Cited By (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108470250A (en) * | 2018-03-25 | 2018-08-31 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of Normal Type series components |
CN108509390A (en) * | 2018-03-25 | 2018-09-07 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of gamma type series components |
CN108509389A (en) * | 2018-03-25 | 2018-09-07 | 中国人民解放军海军工程大学 | A kind of spare parts demand amount computational methods of Weibull type series components |
CN108509389B (en) * | 2018-03-25 | 2022-01-14 | 中国人民解放军海军工程大学 | Spare part demand calculation method for Weibull serial parts |
CN108509390B (en) * | 2018-03-25 | 2021-11-02 | 中国人民解放军海军工程大学 | Spare part demand calculation method for gamma type serial parts |
CN108470250B (en) * | 2018-03-25 | 2021-11-02 | 中国人民解放军海军工程大学 | Spare part demand calculation method for normal series connection component |
CN108334720B (en) * | 2018-04-09 | 2021-08-31 | 中国人民解放军海军工程大学 | Method for calculating demand of normal type unit spare parts under risk of storage failure |
CN108334720A (en) * | 2018-04-09 | 2018-07-27 | 中国人民解放军海军工程大学 | A kind of Normal Type unit spare parts demand amount computational methods under store failure risk |
CN108733883A (en) * | 2018-04-16 | 2018-11-02 | 中国人民解放军海军工程大学 | A kind of method of determining Normal Type unit replenished spares demand |
CN108733883B (en) * | 2018-04-16 | 2021-08-13 | 中国人民解放军海军工程大学 | Method for determining demand of subsequent spare parts of normal type unit |
CN109376334A (en) * | 2018-09-17 | 2019-02-22 | 中国人民解放军海军工程大学 | A kind of service life estimation of distribution parameters method of Normal Type unit |
CN109523160A (en) * | 2018-11-15 | 2019-03-26 | 青岛航讯网络技术服务有限公司 | The more normal state assembly of elements spare parts demand amounts of the long-term support mission of larger cargo ships determine method |
CN110727921A (en) * | 2019-09-30 | 2020-01-24 | 中国人民解放军海军工程大学 | Normal type universal part spare part demand calculation method and device |
CN110727921B (en) * | 2019-09-30 | 2023-11-07 | 中国人民解放军海军工程大学 | Method and device for calculating demand quantity of normal general spare parts |
CN111080104A (en) * | 2019-12-05 | 2020-04-28 | 成都飞机工业(集团)有限责任公司 | Periodic task management scheduling method based on test flight management and control service |
CN116843231A (en) * | 2023-07-20 | 2023-10-03 | 中国人民解放军海军工程大学 | Mechanical equipment use availability quantification method and system considering maintenance time consumption |
CN116843231B (en) * | 2023-07-20 | 2024-03-19 | 中国人民解放军海军工程大学 | Mechanical equipment use availability quantification method and system considering maintenance time consumption |
Also Published As
Publication number | Publication date |
---|---|
CN106777819B (en) | 2020-05-19 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106777819A (en) | A kind of Normal Type has the computational methods of part replacement cycle in longevity | |
CN105096053B (en) | A kind of health control decision-making technique suitable for complicated technology system | |
CN106844953A (en) | A kind of Weibull type has the security probability computational methods of longevity part spare part | |
CN104376400A (en) | Risk assessment method based on fuzzy matrix and analytic hierarchy process | |
CN107644694B (en) | A kind of nuclear power plant's large break crash analysis method | |
CN103440419B (en) | A kind of based on fault tree and the reliable dispensing systems of analytic hierarchy process (AHP) and distribution method | |
Joy et al. | An empirical analysis of sustainability of public debt among BRICS nations | |
CN110046379A (en) | A kind of structure entirety damnification recognition method based on space-frequency information | |
CN104537211A (en) | Enterprise safety risk early warning method based on analytic hierarchy process and grey theory | |
CN106022710A (en) | Insurance check method and apparatus | |
CN113570138A (en) | Method and device for predicting residual service life of equipment of time convolution network | |
CN107169635A (en) | A kind of man-machine system reliability index decomposes distribution method and appraisal procedure | |
CN104766250A (en) | Risk factor weight value calculation method for pipe of pipe gallery | |
CN109523160A (en) | The more normal state assembly of elements spare parts demand amounts of the long-term support mission of larger cargo ships determine method | |
Chandy et al. | Detection of cyber-attacks to water systems through machine-learning-based anomaly detection in SCADA data | |
CN107194604A (en) | A kind of fired power generating unit method for evaluating reliability | |
CN105138850B (en) | Civil aircraft system maintenance time interval calculating method | |
CN117494950B (en) | Optical storage, filling and inspection micro-grid integrated station operation safety evaluation method | |
CN114169711A (en) | Accident emergency disposal scheme generation method, device and system for distillation device | |
CN106933780A (en) | A kind of computational methods of blade of wind-driven generator fatigue life | |
Kloos et al. | Consideration of human actions in combination with the probabilistic dynamics method Monte Carlo dynamic event tree | |
CN114363004B (en) | Risk assessment method, risk assessment device, computer equipment and storage medium | |
Zhou et al. | Fuzzy PSA evaluation method for passive residual heat removal system | |
CN115755831A (en) | Fault diagnosis method and system based on fuzzy hierarchical analysis | |
CN113094816B (en) | Method for constructing comprehensive working condition vibration spectrum and long-life test spectrum of armored vehicle |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |