CN104881580B - A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method - Google Patents
A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method Download PDFInfo
- Publication number
- CN104881580B CN104881580B CN201510277707.1A CN201510277707A CN104881580B CN 104881580 B CN104881580 B CN 104881580B CN 201510277707 A CN201510277707 A CN 201510277707A CN 104881580 B CN104881580 B CN 104881580B
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- msubsup
- zero
- corner
- 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.)
- Active
Links
Landscapes
- Feedback Control In General (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The invention discloses a kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method, including following steps：Step one, rotating speed degradation mechanism is analyzed；Step 2, analyzes the corner change mechanism based on the active/standby zero signal near zero-bit area border, determines health status index；Step 3, corner change modeling and checking based on the active/standby zero signal near zero-bit area border；Step 4, reliability and life prediction.The present invention breaches traditional defect for lacking data available in space using output torque or transmission efficiency as the method for health assessment indicators, it will cause the thought of corner generation deviation from actual speed and having differences property of theoretical rotational speed, the stoichiometric operation angle of active/standby zero signal and drive mechanism when being run by analysis-driven mechanism space, corner variation model is modeled, health state evaluation and and the life prediction of satellite in orbit drive mechanism is realized.
Description
Technical field
The present invention, which provides a kind of extracted from satellite telemetering data, can reflect the index and according to this of drive mechanism health status
The method that modeling carries out life prediction, provides technical support for the reliability demonstration of satellite in orbit, belongs to the health of satellite
Management and life prediction field.
Background technology
The health monitoring and life search of product are always the major issue in product research.For many space classes, light
For the core component of electric class, its life requirements is high, technical difficulty is high, production cost is big, production batch is small, therefore it is can
By there is great difficulty in property analysis and the realization predicted.
Drive mechanism is the executing agency of solar battery array drives subsystem, its function be realize solar battery array to day
Orientating function, while the power signal and measurement and control signal of solar battery array are transferred into celestial body correlation by the conducting slip ring of itself
System.From structure, drive mechanism mainly includes stepper motor, decelerator, slip ring, bearing, position sensor, drive shaft
Deng.In all parts, decelerator is without back-up arrangement, it is necessary to improve its bearing capacity and lubrication.Its lubrication failure is driving machine
The topmost failure mode of structure, therefore often commented using the lubrication failure of decelerator as bottleneck to be driven the health status of mechanism
Valency.
Conventional decelerator is harmonic speed reducer at present.The decline of harmonic speed reducer greasy property, can often cause driving machine
The reduction of structure output torque, transmission efficiency reduction, operating temperature rising, rotating speed degeneration etc..In laboratory research, often with output torque
Or transmission efficiency carrys out the lubrication failure of Modeling Research decelerator as health status index.But in space, it is more difficult to realize power
The accurate measurement of the actual value of square, so that not including this item data typically in telemetry.Therefore, it is traditional based on power output
The modeling method of square or transmission efficiency can not be used for assessing health status of the satellite drive mechanism in space.And temperature is by satellite
The influence of many factors such as change in location, collector ring heating, heat sink material aging, it is difficult to be used as the profit for only reflecting harmonic speed reducer
The index of sliding performance state.
The content of the invention
The defect existed for prior art, the purpose of the present invention is to propose to a kind of in-orbit health status of satellite drive mechanism
Index extraction and life-span prediction method.Pass through the data and the harmonic speed reducer of satellite drive mechanism that can be measured when in-orbit satellite
Greasy property degradation mechanism is analyzed, and the index of the in-orbit health status of satellite drive mechanism can be reflected by extracting, and be built according to this
Mould, realizes the reliability demonstration and life prediction when satellite is in-orbit.It declines caused rotating speed degeneration by analyzing greasy property
Influence principle to corner, and harmonic speed reducer is reflected with the changing rule of the active/standby zero signal near zero-bit area border
Corner change, the health status of drive mechanism is reflected by this change.
The technical scheme is that：
A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method, it is characterised in that including with
Lower step：
The first step, analyzes the rotating speed degradation mechanism of decelerator；
With the decline of decelerator greasy property, the abrasion of decelerator aggravates, the reduction of its transmission precision, the transmission to rotating speed
Ability declines, and difference occurs between actual reduction of speed ability and design reduction of speed ability, that is, when giving same input speed, drive mechanism
Reality output rotating speed will not gradually catch up with theoretical output speed, when reality output rotating speed does not catch up with theoretical output speed,
In identical run time, angle and the theory of actual rotation answer gyration to have differences, and pass through a fixed theoretical corner
The variation tendency of corresponding actual rotational angle is analyzed, and can be achieved with the lubrication degradation analysis of drive mechanism；
Second step, analyzes the corner change mechanism based on the active/standby zero signal near zero-bit area border, it is determined that healthy shape
State index；
Active/standby zero signal is the binary system telemetry for being used in satellite judge whether drive mechanism is in zero-bit area；
Zero-bit area is the given range that drive mechanism angle of operation is near 0 degree, and range wide is 3.5~4.5 degree, wherein, 0
Represent to be in nonzero digit area, 1 represents to be in zero-bit area；The zero-bit of main zero signal and standby zero signal is interval not exclusively overlapping；
In respective zero-bit is interval, signal all will be displayed as 1, cross this interval range, then be nonzero digit area, signal is shown as 0；
NoteTo enter the border in zero-bit area,To go out the border in zero-bit area, theoretical cornerAndWhen,
Zero signal is complete 1；Theoretical cornerWhen, zero signal is full 0；Due to vibration iso-stress interference, drive mechanism
There is certain margin of tolerance in real-world operation angle, actual rotational angle can be considered as into stochastic variable；Therefore when theoretical cornerOrWhen, according to the randomness of actual rotational angle, zero signal will take 1 with certain probability, and 0 is taken with certain probability；With reference to first
The rotating speed degradation mechanism analysis of step is understood, with the decline of decelerator greasy property, actual reduction of speed ability and design reduction of speed ability
Between there is difference, the actual rotation speed of drive mechanism does not catch up with theoretical velocity gradually,The neighbouring corresponding reality of theoretical corner
The distribution of border corner gradually will be offset toward nonzero digit area, and taking 1 probability reduces；Similarly,Neighbouring theoretical corner is corresponding
The distribution of actual rotational angle gradually will be offset toward zero-bit area, and taking 1 probability increases.
From the rotating speed degeneration of decelerator, by the changing rule of the active/standby zero signal near zero-bit area border come
The corner variation model degenerated based on rotating speed is set up, the analysis to the in-orbit health status of drive mechanism is realized, it can be speculated
In-orbit residual life；
3rd step, corner change modeling and checking based on the active/standby zero signal near zero-bit area border；
Remember that θ causes active/standby zero signal for one near zero-bit area borderBoth
1, which may be taken, may also take 0 theoretical corner, and x (t) is the actual rotational angle of the corresponding ts of θ, is a random quantity；y(t) it is zero-bit
The value of signal, then
Given x (t) corner variation model isWhereinFor the random of actual rotational angle
It is distributed item (β is model parameter), F (t, α) is drift term (α is model parameter)；The span for remembering x (t) is (B1(t), B2
(t))。
To any time t, zero signal y (t) takes 1 Probability p (t) to be calculated by following formula：
(1) whenAndThen
(2) whenAndThen
(3) whenAndWhen,
P (t)=1；
What the corresponding active/standby zero signals of note θ were measured at each moment takes 1 probable value for pr(t)；Satellite includes both wings,
Per the wing comprising main zero signal and standby zero signal, each signal was not only entering zero-bit area but also was going out zero-bit area and occur to take 1 probability
The situation of change, therefore have 8 groups of data；
If takingProbability-distribution function be γ (β).For situation (1), two moment t are taken1And t2, t2＞ t1, then have
For situation (2), two moment t are taken1And t2, t2＞ t1, then have：
According to degradation mechanism design F (t α) andModel (such as F (t, α) fetching number degradation model,Take normal state
Distributed model), pass through pr(t) Δ p is calculatedr(t), to Δ p (t) actual measured value Δ pr(t) estimated using maximum likelihood, square
The method for parameter estimation such as meter are fitted, obtain F (t, α) model parameter α andParameter beta, obtain moving back based on rotating speed
The corner variation model of change.And in pr(t) several groups of data are left and taken in, are contrasted with predicting the outcome for corner variation model, are carried out
Model is verified.
4th step, reliability and life prediction；
By corner variation model, failure threshold is provided, product reliability at any time is calculated and arbitrarily may be used
By the life-span under the conditions of degree；
Assuming thatFor with β1For distribution center, with 2 β2For being uniformly distributed for siding-to-siding block length, β=(β1, β2), F (t, α)=-
α × t, i.e. corner change turn to linear reduction.In linear regression model, model parameter α is that can be considered corner rate of change.；D
(t, β, α) can be designated as x (t)~U (β1-α×t-β2, β1-α×t+β2)；On the length of x (t) distributed area, due in office
Near meaning one zero-bit area border, there is corresponding zero signal in the presence of not only desirable 0 but also desirable 1 in general only one theoretical corner
Situation, then siding-to-siding block length, which will be less than, segments step angle, i.e. B2(t)-B1(t)=2 β2≤ d θ, subdivision step angle is 0.072, that is, takes 2
β2=0.072.Then stochastic variable x (t) probability density function is
Note is for x (t), and value is in interval (z, B2(t) probability) is：ω (z, B2(t)).
Entering zero-bit area, having
In formulaAs p carries out slope during linear fit；
Going out zero-bit area, having
In formulaAlso slope during linear fit is carried out for p；
Time when note satellite is just launched is t=0, then initial time actual speed is not yet degenerated, and has β1=θ, takes 2
Individual moment t1, t2, t1＜ t2, pr(t1) it is t1When for zero signal y (t1) take 1 probability, pr(t2) it is t2When zero signal y (t2)
Take 1 probability, using taking 1 statistical probability average as the probability for taking 1 this moment in a period of time before and after this moment；
To every group of pr(t) data, carry out linear fit；Entering zero-bit area, the slope of fitting dataThat is the β of α=22K,
Going out zero-bit area, the slope of fitting data isThat is the β of α=- 22k；
The corner rate of change α each obtained with reference to 8 groups of data, to α using Normal Discrimination with fitting, set up model for N (μ,
σ2)；
According to corner rate of change α, it is known that actual rotation angle and the difference of theoretical rotational angle obey distribution N after t durations
(μ t, σ2t2), reliability prediction and durability analysis are realized on this basis；
In terms of model checking, the mode for staying a validation-cross is taken：One group is left as verification data every time, uses it
He is fitted seven groups of data, estimates N (μ, σ2), then judge the parameter alpha of validation group whether in given confidential interval；
With the increase of drive mechanism test period, it is assumed that actual rotation angle and the difference of theoretical rotational angle are more than certain
One threshold value DfWhen, harmonic speed reducer fails, according to parameter alpha Normal Distribution, and further derive harmonic speed reducer can
By degree function R (t)
According to above-mentioned model and given failure threshold Df, can calculate and obtain harmonic speed reducer at any time reliable
Degree, and try to achieve the drive mechanism life-span L in the case where given reliability requires R；
The method have the benefit that：
(1) present invention reflects reality indirectly by active/standby zero signal in the variation tendency of zero-bit area border probability
The degeneration of border rotating speed, reflects the decline of harmonic speed reducer greasy property as index with corner change breakthroughly, realizes
The reliability analysis of satellite in orbit drive mechanism.
(2) the cited data item of the present invention all effectively can easily be measured in space, it is easy to practical operation.
Brief description of the drawings
Fig. 1 flow charts of the method for the present invention
Fig. 2 star+Y airfoil theories corner corresponding standby zero signal value figure when being 355.752
Fig. 3 actual rotational angle change demonstration figures
Reliability graph of Fig. 4 drive mechanisms under certain threshold value
Embodiment
The in-orbit health status index extraction of satellite drive mechanism and life-span prediction method that the present invention is provided, specific steps are such as
Under：
Step one, rotating speed degradation mechanism is analyzed；
With the decline of decelerator greasy property, the abrasion of decelerator aggravates, the reduction of its transmission precision, the transmission to rotating speed
Ability declines, and difference occurs between actual reduction of speed ability and design reduction of speed ability.When giving same input speed, drive mechanism
Reality output rotating speed will not gradually catch up with theoretical output speed.When torque and transmission efficiency are difficult to accurate measurement, by right
The difference of the theoretical rotational speed of drive mechanism and the actual speed of operating is analyzed, you can realized to harmonic speed reducer greasy property
The indirect analysis of degeneration, can also model and carry out reliability analysis and the life prediction of drive mechanism according to this.But drive mechanism
The size of rotating speed is adjusted with gear according to different modes, then realizes solar battery sheet by this regulation
Position adjustments.Actual speed is a transient volume, it is difficult to direct measurement, and will lack when rotating speed directly being considered as into health status index must
The modeling data wanted, it is therefore necessary to reflect the degeneration of rotating speed by other specification.
Step 2, analyzes the corner change mechanism based on the active/standby zero signal near zero-bit area border, it is determined that healthy shape
State index；
When actual speed does not catch up with theoretical rotational speed, in identical run time, the angle of actual rotation is answered with theoretical
Gyration has differences.Analyzed by the variation tendency of the actual rotational angle corresponding to a fixed theoretical corner, can
Realize the lubrication degradation analysis of drive mechanism.
During active/standby zero signal is satellite, for judging whether drive mechanism is in the binary system telemetry in zero-bit area.
Zero-bit area is the given range that drive mechanism angle of operation is near 0 degree, and range wide is usually 3.5~4.5 degree.Its
In, 0 represents to be in nonzero digit area, and 1 represents to be in zero-bit area.The interval endless full weight of zero-bit of main zero signal and standby zero signal
It is folded.In respective zero-bit is interval, signal all will be displayed as 1, cross this interval range, then be nonzero digit area, signal is shown as
0。
NoteTo enter the border in zero-bit area,To go out the border in zero-bit area, generally,360 degree of the right side should be located at
Side.In theory, theoretical cornerAndWhen, zero signal is complete 1；Theoretical cornerWhen, zero-bit
Signal is full 0.In fact, due to vibration iso-stress interference, there is certain margin of tolerance in the real-world operation angle of drive mechanism,
Actual rotational angle can be considered as stochastic variable.Therefore when theoretical cornerOrWhen, according to the randomness of actual rotational angle, zero
Position signal will take 1 with certain probability, and 0 is taken with certain probability.Understood with reference to the analysis of rotating speed degradation mechanism, with decelerator lubricity
, there is difference, the actual rotation speed of drive mechanism is not gradually between actual reduction of speed ability and design reduction of speed ability in the decline of energy
Upper theoretical velocity,The distribution of the neighbouring corresponding actual rotational angle of theoretical corner gradually will be offset toward nonzero digit area, take 1 probability
Reduction；Similarly,The distribution of the neighbouring corresponding actual rotational angle of theoretical corner gradually will be offset toward zero-bit area, take 1 probability
Increase, such as Fig. 2~3.
In Fig. 3, left side is non-standby zero-bit area, and right side is standby zero-bit area, and blue moulding is the reality near zero-bit area border
Corner x (t) distribution.Skew over time, the corresponding actual rotational angle in theoretical rotational angle theta=355.752 is gradually toward non-standby
Zero-bit area is offset, and standby zero signal takes 1 probability gradually to reduce, and to the last whole distribution all enters non-standby zero-bit area.And θ
=355.824 corresponding actual rotational angle distributions also will progressively march toward non-standby zero-bit area, and standby zero signal becomes with certain general from complete 1
Rate takes 0.Nearby there is also similar mechanism.
Therefore, from the rotating speed degeneration thought of decelerator, the change of the active/standby zero signal near zero-bit area border is passed through
Law sets up the corner variation model degenerated based on rotating speed, can be achieved the analysis to the in-orbit health status of drive mechanism,
Speculate its in-orbit residual life.
Step 3, corner change modeling and checking based on the active/standby zero signal near zero-bit area border；
Note θ be zero-bit area border near one cause active/standby zero signal be possible take 1 may also take 0 theory turn
Angle, such as certain star existNeighbouring θ is 355.752,Neighbouring θ is 0.072.X (t) turns for the reality of the corresponding ts of θ
Angle, is a random quantity.Y (t) is the value of zero signal.Then
Given x (t) variation model isWhereinFor the random distribution of actual rotational angle
Item (β is model parameter), F (t, α) is drift term (α is model parameter).The span for remembering x (t) is (B1(t), B2(t))。
To any time t, zero signal y (t) takes 1 Probability p (t) to be calculated by following formula：
(1) whenAndThen
(2) whenAndThen
(3) whenAndWhen,
P (t)=1.
What the corresponding active/standby zero signals of note θ were measured at each moment takes 1 probable value for pr(t).Satellite includes both wings,
Per the wing comprising main zero signal and standby zero signal, each signal was not only entering zero-bit area but also was going out zero-bit area and occur to take 1 probability
The situation of change, therefore have 8 groups of data.
If takingProbability-distribution function be γ (β).For situation (1), two moment t are taken1And t2, t2＞ t1, then have：
For situation (2), two moment t are taken1And t2, t2＞ t1, then have：
According to degradation mechanism design F (t, α) andModel (such as F (t, α) fetching number degradation model,Take just
State distributed model), pass through pr(t) Δ p is calculatedr(t), to Δ p (t) actual measured value Δ pr(t) using maximum likelihood, square
The method for parameter estimation such as estimation are fitted, obtain F (t, α) model parameter α andParameter beta, obtain be based on rotating speed
The corner variation model of degeneration.And in pr(t) several groups of data are left and taken in, contrasts, enters with predicting the outcome for corner variation model
Row model is verified.
4th step, reliability and life prediction；
By corner variation model, failure threshold is provided, product reliability at any time is calculated and arbitrarily may be used
By the life-span under the conditions of degree.
Assuming thatFor with β1For distribution center, with 2 β2For being uniformly distributed for siding-to-siding block length, β=(β1, β2), F (t, α)
=-α × t, i.e. corner change turn to linear reduction.In linear regression model, model parameter α is that can be considered corner rate of change..
D (t, β, α) can be designated as x (t)~U (β1-α×t-β2, β1-α×t+β2).On the length of x (t) distributed area, due in office
Near meaning one zero-bit area border, there is corresponding zero signal in the presence of not only desirable 0 but also desirable 1 in general only one theoretical corner
Situation, then siding-to-siding block length, which will be less than, segments step angle, i.e. B2(t)-B1(t)=2 β2≤dθ.Common subdivision step angle is 0.072,
It can use 2 β2=0.072.Then stochastic variable x (t) probability density function is
Note is for x (t), and value is in interval (z, B2(t) probability) is：ω (z, B2(t)).
Entering zero-bit area, having
In formulaAs p carries out slope during linear fit.
Going out zero-bit area, having
In formulaAlso slope during linear fit is carried out for p.
Time when note satellite is just launched is t=0, then initial time actual speed is not yet degenerated, and has β1=θ, takes 2
Individual moment t1, t2, t1＜ t2, pr(t1) it is t1When for zero signal y (t1) take 1 probability, pr(t2) it is t2When zero signal y (t2)
Take 1 probability, can be using taking 1 statistical probability average in a period of time before and after this moment as the probability for taking 1 this moment.
To every group of pr(t) data, carry out linear fit.Entering zero-bit area, the slope of fitting dataThat is the β of α=22K,
Going out zero-bit area, the slope of fitting data isThat is the β of α=- 22k。
The corner rate of change α each obtained with reference to 8 groups of data, to α using Normal Discrimination with fitting, set up model for N (μ,
σ2)。
According to corner corner rate of change α, it is known that actual rotation angle and the difference of theoretical rotational angle are obeyed and divided after t durations
Cloth N (μ t, σ2t2).Reliability prediction and durability analysis can be achieved on this basis.
In terms of model checking, the present embodiment takes the mode for staying a validation-cross.One group is left every time to use as checking
Data, are fitted with other seven groups of data, estimate N (μ, σ2), then judge the parameter alpha of validation group whether in given confidence area
In.
With the increase of drive mechanism test period, it is assumed that actual rotation angle and the difference of theoretical rotational angle are more than certain
One threshold value DfWhen, harmonic speed reducer fails, according to parameter alpha Normal Distribution, can further derive harmonic speed reducer
Reliability Function R (t)
Reliability graph of the drive mechanism under certain threshold value such as Fig. 4.According to above-mentioned model and given failure threshold Df, you can
Calculating obtains the reliability of harmonic speed reducer at any time, can also try to achieve the drive mechanism longevity in the case where given reliability requires R
Order L.
In summary, although the present invention is preferably to implement disclosed above, and so it is not limited to the present invention, Ren Heben
Field those of ordinary skill, without departing from the spirit and scope of the present invention, when can make it is various change with retouching, therefore the present invention
Protection domain when being defined depending on the scope that claims are defined.
Claims (1)
1. a kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method, it is characterised in that including following
Step：
The first step, analyzes the rotating speed degradation mechanism of decelerator；
With the decline of decelerator greasy property, the abrasion of decelerator aggravates, its transmission precision reduction, to the transfer capability of rotating speed
Decline, difference occur between actual reduction of speed ability and design reduction of speed ability, that is, when giving same input speed, the reality of drive mechanism
Border output speed will not gradually catch up with theoretical output speed, when reality output rotating speed does not catch up with theoretical output speed, identical
Run time in, angle and the theory of actual rotation answer gyration to have differences, right by a fixed theoretical corner institute
The variation tendency for the actual rotational angle answered is analyzed, and can be achieved with the lubrication degradation analysis of drive mechanism；
Second step, analyzes the corner change mechanism based on the active/standby zero signal near zero-bit area border, determines that health status refers to
Mark；
Active/standby zero signal is the binary system telemetry for being used in satellite judge whether drive mechanism is in zero-bit area；Zero-bit
Area is the given range that drive mechanism angle of operation is near 0 degree, and range wide is 3.5~4.5 degree, wherein, 0 represents
Represent to be in zero-bit area in nonzero digit area, 1；The zero-bit of main zero signal and standby zero signal is interval not exclusively overlapping；Each
Interval interior from zero-bit, signal all will be displayed as 1, cross this interval range, then be nonzero digit area, signal is shown as 0；
NoteTo enter the border in zero-bit area,To go out the border in zero-bit area, theoretical cornerAndWhen, zero-bit
Signal is complete 1；Theoretical cornerWhen, zero signal is full 0；Due to vibration interference, the real-world operation angle of drive mechanism
There is certain margin of tolerance in degree, actual rotational angle can be considered as into stochastic variable；Therefore when theoretical cornerOrWhen,
According to the randomness of actual rotational angle, zero signal will take 1 with certain probability, and 0 is taken with certain probability；Moved back with reference to the rotating speed of the first step
Change Analysis on Mechanism to understand, with the decline of decelerator greasy property, difference occur between actual reduction of speed ability and design reduction of speed ability,
The actual rotation speed of drive mechanism does not catch up with theoretical velocity gradually,The distribution of the neighbouring corresponding actual rotational angle of theoretical corner
Gradually it will be offset toward nonzero digit area, taking 1 probability reduces；Similarly,Point of the neighbouring corresponding actual rotational angle of theoretical corner
Cloth gradually will be offset toward zero-bit area, and taking 1 probability increases,
From the rotating speed degeneration of decelerator, set up by the changing rule of the active/standby zero signal near zero-bit area border
The corner variation model degenerated based on rotating speed, is realized the analysis to the in-orbit health status of drive mechanism, can speculate that its is in-orbit
Residual life；
3rd step, corner change modeling and checking based on the active/standby zero signal near zero-bit area border；
Remember that θ causes active/standby zero signal for one near zero-bit area borderBoth may
0 theoretical corner may also be taken by taking 1, and x (t) is the actual rotational angle of the corresponding ts of θ, is a random quantity；Y (t) is zero signal
Value, then
Given x (t) corner variation model isWhereinFor the random distribution of actual rotational angle
, β is model parameter, and F (t, α) is drift term, and α is model parameter；The span for remembering x (t) is (B1(t), B2(t))；
To any time t, zero signal y (t) takes 1 Probability p (t) to be calculated by following formula：
<mrow>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<mi>y</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>=</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
<mo>)</mo>
</mrow>
<mo>.</mo>
</mrow>
(1) whenAndThen
<mrow>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>;</mo>
</mrow>
(2) whenAndThen
<mrow>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
<mo>)</mo>
</mrow>
<mo>;</mo>
</mrow>
1
(3) whenAndWhen,
P (t)=1；
What the corresponding active/standby zero signals of note θ were measured at each moment takes 1 probable value for pr(t)；Satellite includes both wings, per wing bag
Containing main zero signal and standby zero signal, each signal was not only entering zero-bit area but also was going out zero-bit area and occur to take what 1 probability changed
Situation, therefore have 8 groups of data；
If takingProbability-distribution function be γ (β)；For situation (1), two moment t are taken1And t2,t2＞ t1, then have：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>&Delta;</mi>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msubsup>
<mo>&Integral;</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mrow>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
<mo>-</mo>
<msubsup>
<mo>&Integral;</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mrow>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<msubsup>
<mo>&Integral;</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mrow>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>F</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<mi>&alpha;</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>F</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<mi>&alpha;</mi>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
<mo>-</mo>
<msubsup>
<mo>&Integral;</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mrow>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
<mo>;</mo>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
For situation (2), two moment t are taken1And t2,t2＞ t1, then have：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>&Delta;</mi>
<mi>p</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>P</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
<mo>&le;</mo>
<mi>x</mi>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
<mo>&le;</mo>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>=</mo>
<msubsup>
<mo>&Integral;</mo>
<mrow>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
<mo>-</mo>
<msubsup>
<mo>&Integral;</mo>
<mrow>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>=</mo>
<msubsup>
<mo>&Integral;</mo>
<mrow>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mi>F</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<mi>&alpha;</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>F</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<mi>&alpha;</mi>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
<mo>-</mo>
<msubsup>
<mo>&Integral;</mo>
<mrow>
<msub>
<mi>B</mi>
<mn>1</mn>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mn>360</mn>
<mo>+</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
</mrow>
</msubsup>
<mi>&gamma;</mi>
<mrow>
<mo>(</mo>
<mi>&beta;</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>x</mi>
<mo>;</mo>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
According to degradation mechanism design F (t, α) andModel, pass through pr(t) Δ p is calculatedr(t), to Δ p (t) actual survey
Value Δ pr(t) be fitted using maximum likelihood or moment estimation method, obtain F (t, α) model parameter α andGinseng
Number β, obtains the corner variation model degenerated based on rotating speed, and in pr(t) several groups of data, the knot with corner variation model are left and taken in
Fruit is contrasted, and carries out model checking；
4th step, reliability and life prediction；
By corner variation model, failure threshold is provided, product reliability at any time is calculated and in any reliability
Under the conditions of life-span；
Assuming thatFor with β1For distribution center, with 2 β2For being uniformly distributed for siding-to-siding block length, β=(β1, β2), F (t, α)=- α ×
T, i.e. corner change turn to linear reduction；In linear regression model, model parameter α is that can be considered corner rate of change；D (t, β,
α) it is designated as x (t)~U (β1-α×t-β2, β1-α×t+β2)；On the length of x (t) distributed area, due to any one zero
Near the area border of position, general only one theoretical corner has that corresponding zero signal is present and not only can use 0 but also desirable 1, then
Siding-to-siding block length will be less than subdivision step angle, i.e. B2(t)-B1(t)=2 β2≤ d θ, subdivision step angle is 0.072, that is, takes 2 β2=
0.072；Then stochastic variable x (t) probability density function is
Note is for x (t), and value is in interval (z, B2(t) probability) is：ω (z, B2(t)).
Entering zero-bit area, having
<mrow>
<mi>&Delta;</mi>
<mi>p</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>p</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>&omega;</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mo>,</mo>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>-</mo>
<mi>&omega;</mi>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
<mo>,</mo>
<msub>
<mi>B</mi>
<mn>2</mn>
</msub>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>&beta;</mi>
<mn>1</mn>
</msub>
<mo>-</mo>
<mi>&alpha;</mi>
<mo>&times;</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>+</mo>
<msub>
<mi>&beta;</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>1</mn>
</msubsup>
</mrow>
<mrow>
<mn>2</mn>
<msub>
<mi>&beta;</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
<mo>-</mo>
<mfrac>
<mrow>
<msub>
<mi>&beta;</mi>
<mn>1</mn>
</msub>
<mo>-</mo>
<mi>&alpha;</mi>
<mo>&times;</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>+</mo>
<msub>
<mi>&beta;</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<msubsup>
<mi>&theta;</mi>
<mi>b</mi>
<mn>2</mn>
</msubsup>
</mrow>
<mrow>
<mn>2</mn>
<msub>
<mi>&beta;</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<mrow>
<mi>&alpha;</mi>
<mo>&times;</mo>
<mrow>
<mo>(</mo>
<msub>
<mi>t</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<msub>
<mi>t</mi>
<mn>1</mn>
</msub>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mn>2</mn>
<msub>
<mi>&beta;</mi>
<mn>2</mn>
</msub>
</mrow>
</mfrac>
<mo>;</mo>
</mrow>
In formulaAs p carries out slope during linear fit；
Going out zero-bit area, having
In formulaAlso slope during linear fit is carried out for p；
Time when note satellite is just launched is t=0, then initial time actual speed is not yet degenerated, and has β1=θ, when taking 2
Carve t1, t2,t1＜ t2, pr(t1) it is t1When for zero signal y (t1) take 1 probability, pr(t2) it is t2When zero signal y (t2) take 1
Probability, using taking 1 statistical probability average as the probability for taking 1 this moment in a period of time before and after this moment；
To every group of pr(t) data, carry out linear fit；Entering zero-bit area, the slope of fitting dataThat is the β of α=22K, is going out
Zero-bit area, the slope of fitting data isThat is the β of α=- 22k；
The corner rate of change each obtained with reference to 8 groups of data, to α using Normal Discrimination and fitting, sets up model for N (μ, σ2)；
According to corner rate of change α, it is known that actual rotation angle and the difference of theoretical rotational angle obey distribution N (μ t, σ after t durations2t2), reliability prediction and durability analysis are realized on this basis；
In terms of model checking, the mode for staying a validation-cross is taken：One group is left every time as verification data, with other seven
Group data are fitted, and estimate N (μ, σ2), then judge the parameter alpha of validation group whether in given confidential interval；
With the increase of drive mechanism test period, it is assumed that actual rotation angle and the difference of theoretical rotational angle are more than a certain threshold
Value DfWhen, harmonic speed reducer fails, and according to parameter alpha Normal Distribution, further derives the reliability of harmonic speed reducer
Function R (t)
<mrow>
<mi>R</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>P</mi>
<mo>{</mo>
<mi>b</mi>
<mo>&times;</mo>
<mi>t</mi>
<mo><</mo>
<msub>
<mi>D</mi>
<mi>f</mi>
</msub>
<mo>}</mo>
<mo>=</mo>
<mi>P</mi>
<mo>{</mo>
<mfrac>
<mrow>
<mi>b</mi>
<mo>&times;</mo>
<mi>t</mi>
<mo>-</mo>
<mi>&mu;</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>&sigma;</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo><</mo>
<mfrac>
<mrow>
<msub>
<mi>D</mi>
<mi>f</mi>
</msub>
<mo>-</mo>
<mi>&mu;</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>&sigma;</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>}</mo>
<mo>=</mo>
<mi>&Phi;</mi>
<mo>{</mo>
<mfrac>
<mrow>
<msub>
<mi>D</mi>
<mi>f</mi>
</msub>
<mo>-</mo>
<mi>&mu;</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>&sigma;</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>}</mo>
</mrow>
According to above-mentioned model and given failure threshold Df, it can calculate and obtain the reliability of harmonic speed reducer at any time, and
Try to achieve the drive mechanism life-span L in the case where given reliability requires R；
<mrow>
<mi>L</mi>
<mo>=</mo>
<mo>{</mo>
<mi>t</mi>
<mo>|</mo>
<mi>R</mi>
<mrow>
<mo>(</mo>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>R</mi>
<mo>}</mo>
<mo>=</mo>
<mo>{</mo>
<mi>t</mi>
<mo>|</mo>
<mi>&Phi;</mi>
<mo>{</mo>
<mfrac>
<mrow>
<mo>(</mo>
<msub>
<mi>D</mi>
<mi>f</mi>
</msub>
<mo>-</mo>
<mi>&mu;</mi>
<mi>t</mi>
<mo>)</mo>
</mrow>
<mrow>
<mi>&sigma;</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>}</mo>
<mo>=</mo>
<mi>R</mi>
<mo>}</mo>
<mo>.</mo>
</mrow>
3
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510277707.1A CN104881580B (en) | 2015-05-27 | 2015-05-27 | A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510277707.1A CN104881580B (en) | 2015-05-27 | 2015-05-27 | A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104881580A CN104881580A (en) | 2015-09-02 |
| CN104881580B true CN104881580B (en) | 2017-08-29 |
Family
ID=53949073
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510277707.1A Active CN104881580B (en) | 2015-05-27 | 2015-05-27 | A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104881580B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106019936B (en) * | 2016-05-23 | 2018-10-02 | 中车戚墅堰机车车辆工艺研究所有限公司 | The optimization method of RV retarder tolerances grouping based on Monte Carlo simulation |
| CN106599580B (en) * | 2016-12-14 | 2019-03-12 | 中国人民解放军国防科学技术大学 | The in-orbit health state evaluation method of satellite and assessment system based on restructural degree |
| CN111947904A (en) * | 2020-07-31 | 2020-11-17 | 上海卫星工程研究所 | Micro-vibration-based on-orbit health monitoring method, system, medium and equipment for spacecraft structure |
| CN112464140B (en) * | 2020-12-03 | 2022-07-29 | 上海卫星工程研究所 | Satellite power supply system health assessment method and system based on gradient threshold |
| CN114297744A (en) * | 2021-11-25 | 2022-04-08 | 国网河北省电力有限公司保定供电分公司 | Method for calculating structural health degree probability of power transmission tower |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1587989A (en) * | 2004-07-15 | 2005-03-02 | 上海交通大学 | Movable yro life predicting method based on gray mode |
| CN101666662A (en) * | 2009-09-25 | 2010-03-10 | 北京航空航天大学 | Accelerated degradation test prediction method based on fuzzy theory |
| CN103675637A (en) * | 2013-11-14 | 2014-03-26 | 南京航空航天大学 | Power MOSFET health state assessment and residual life prediction method |
| CN103745089A (en) * | 2013-12-20 | 2014-04-23 | 北京工业大学 | Multi-dimensional public transport operation index evaluation method |
| CN104598734A (en) * | 2015-01-22 | 2015-05-06 | 西安交通大学 | Life prediction model of rolling bearing integrated expectation maximization and particle filter |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3914999B2 (en) * | 2001-04-19 | 2007-05-16 | 川崎重工業株式会社 | Shift control method and shift control apparatus |
-
2015
- 2015-05-27 CN CN201510277707.1A patent/CN104881580B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1587989A (en) * | 2004-07-15 | 2005-03-02 | 上海交通大学 | Movable yro life predicting method based on gray mode |
| CN101666662A (en) * | 2009-09-25 | 2010-03-10 | 北京航空航天大学 | Accelerated degradation test prediction method based on fuzzy theory |
| CN103675637A (en) * | 2013-11-14 | 2014-03-26 | 南京航空航天大学 | Power MOSFET health state assessment and residual life prediction method |
| CN103745089A (en) * | 2013-12-20 | 2014-04-23 | 北京工业大学 | Multi-dimensional public transport operation index evaluation method |
| CN104598734A (en) * | 2015-01-22 | 2015-05-06 | 西安交通大学 | Life prediction model of rolling bearing integrated expectation maximization and particle filter |
Non-Patent Citations (10)
| Title |
|---|
| Methods for Reliability Assessment under Irregular Time-Varying-Stress Degradation Testing;LIU Tian-yu et. al.;《Journal of Donghua University》;20141231;第31卷(第6期);全文 * |
| Satellite Lithium-Ion Battery Remaining Cycle Life Prediction with Novel Indirect Health Indicator Extraction;Datong Liu et.al.;《Energies》;20131231(第6期);全文 * |
| Storage-Work Joint Degradation Model for Discontinuous-Working Devices;Jinglun Zhou et.al.;《IEEE》;20121231;全文 * |
| The Residual Life Prediction of the Satellite Attitude Control System Based on Petri Net;Haiming Qi et.al.;《IEEE》;20141231;全文 * |
| 二项式分布场合加速退化零失效可靠性验证试验;黄秀平 等;《***工程与电子技术》;20120930;第34卷(第9期);全文 * |
| 卫星天线双轴驱动机构健康评估与寿命预测方法研究;王福亚;《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》;20140315(第3期);全文 * |
| 基于加速退化试验数据的可靠性分析;赵建印 等;《可靠性分析与研究》;20051231(第7期);全文 * |
| 基于性能退化的控制力矩陀螺寿命预测;王竣德 等;《科学技术与工程》;20131130;第13卷(第33期);全文 * |
| 基于退化与寿命数据融合的产品剩余寿命预测;彭宝华 等;《***工程与电子技术》;20110531;第33卷(第5期);全文 * |
| 运动副间隙对卫星天线双轴机构动态特性影响;潘冬 等;《中国空间科学技术》;20121031(第5期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104881580A (en) | 2015-09-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104881580B (en) | A kind of in-orbit health status index extraction of satellite drive mechanism and life-span prediction method | |
| Schluntz et al. | The effect of blockage on tidal turbine rotor design and performance | |
| Abkar et al. | Wake flow in a wind farm during a diurnal cycle | |
| Danao et al. | A numerical study of blade thickness and camber effects on vertical axis wind turbines | |
| Dhanraj et al. | An effective evaluation on fault detection in solar panels | |
| Joo et al. | Aerodynamic characteristics of two-bladed H-Darrieus at various solidities and rotating speeds | |
| Carrigan et al. | Aerodynamic shape optimization of a vertical‐axis wind turbine using differential evolution | |
| Andersen et al. | Simulation of the inherent turbulence and wake interaction inside an infinitely long row of wind turbines | |
| CN105550943A (en) | Method for identifying abnormity of state parameters of wind turbine generator based on fuzzy comprehensive evaluation | |
| Elfarra et al. | Investigations on blade tip tilting for HAWT rotor blades using CFD | |
| Storey et al. | Large eddy simulation of turbine loading and performance in a wind farm | |
| CN102663495B (en) | Neural net data generation method for nonlinear device modeling | |
| Churchfield et al. | A comparison of the dynamic wake meandering model, large-eddy simulation, and field data at the egmond aan Zee offshore wind plant | |
| CN103530449A (en) | Multivariable accelerating storage test optimized design method for lifetime piece on missile | |
| Molnár et al. | Mathematical models for indirect measurement of contact forces in hexagonal idler housing of pipe conveyor | |
| CN107103411A (en) | Based on the markovian simulation wind power time series generation method of improvement | |
| Zhou et al. | Influence of inflow conditions on turbine loading and wake structures predicted by large eddy simulations using exact geometry | |
| CN106780134A (en) | The determination method and system of the wind power generating algorithm apoplexy electricity condition number upper limit | |
| Gebreslassie et al. | Experimental and CFD analysis of the wake characteristics of tidal turbines | |
| Shukla et al. | Dynamic overset 2D CFD numerical simulation of a small vertical axis wind turbine | |
| CN104517233B (en) | The method of space flight unit product maturity control | |
| Patel et al. | Aerodynamic analysis of a 2-stage elliptical-bladed Savonius wind rotor: Numerical simulation and experimental validation | |
| Mazarbhuiya et al. | Effect of blade attachments on the performance of an asymmetric blade H-Darrieus turbine at low wind speed | |
| McNaughton et al. | CFD power and load prediction on a 1MW tidal stream turbine with typical velocity profiles from the EMEC test site | |
| Elgammi et al. | Combining unsteady blade pressure measurements and a free-wake vortex model to investigate the cycle-to-cycle variations in wind turbine aerodynamic blade loads in yaw |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| EXSB | Decision made by sipo to initiate substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |