学术 型海报模板ppt课件

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Under the same stress distribution, reliability curves of
different individual dispersion situations with the same
average value are almost the same, showing no
The first time that the degradation process crosses the critical
threshold value D follows an Inverse Gaussian distribution, and the
reliability
fRun(tc)tioncanDbegivte(nt
paper presents a novel method of field reliability prediction considering environment variation and product individual dispersion. Wiener diffusion process with drift was
degradation rate
with a link function such as the Arrhenius
relationship
R t aU zU R t | z, a f z f a dzda
aL
zL
The varied fen zvironmentfalafa ctors and individual dispersion can be
Type
Parameter
Average
Variance
N Norm,al
(200,15) (200,10)
200
225
200
100
(200,5)
200
25
Ga,mma,
(4,2/15,170)
200
225
(9,3/10,170)
200
100
(36,6/5,170)
200
as
)
Assume

exp

2 D (t ) 2t



D
t
(t )

xi (tij )
tij
xij

is
tBhe(dteijg)radatioijn
~ N (
value of
ijth, e
2ith tij
)
pregradation modelling
Case
Results
Wiener process is a widely used method in degradation process and can be seen as a degradation rate model.
X (t ) B(t ) (t )
INTRODUCTION
Reliability tests are usually conducted at a certain virtual environmental stress level whereas the field environment is highly varied from the virtual environment. This
ACKNOWLEGEMENT
This work is supported by the National Natural Science Foundation of China (Grant No. xxxxxxxx).
BIOGRAGHY xxxxxx
1 He is currently a Ph.D. candidate at the School of xxxxxx,
and 140°C. The degradation data for each unit
was observed at t1=100, t2=200, t3=300, t4=400, t5=500, t6=600, t7=700, t8=800, t9=900, t10=1000 (in hours).
used for degradation modeling and a link function which presents degradation rate is introduced to model the impact of varied environment and individual dispersion.
time , then and
f ( xij )
1

xij
ij

tij
tij
z

The effect that environmzentalafeacbtozrs and individual dispersion have on degradation process can be considered as changes in the
right-skewed, left-skewed and symmetric stress distribution. Results show obvious difference in reliability, failure intensity and failure rate between varied stress and constant stress situation and each other. It indicates that properly modeled (proper distribution type and parameters) environmental stress is the fundamental of varied environment oriented reliability prediction. In a linear drift degradation process and Arrhenius-type link function situation, it is reasonable not concerning about product individual dispersion because the impact is barely small, while other situations can be studied in the same way proposed in this present paper.
xxxxxx University. His research interests include xxxxxx.
Results considering dispersion
Normal and Gamma distribution with different parameters are chosen to study the influence of individual dispersion on reliability.
Gamma, transformed Gamma and Normal
diTsytpreibutionPrDoebnaswbiitlyiityth diffPearraementetr parAavmerageeters are Variance
chosen Gamma
to
study
the
in17f4luenc24e
of
tem2264perature1516o2 n
reliability.
4
7
21
196
14
2
30
56
T-Gamma
7
4
32
112
4
7
35
196
28
7.5
28
56
Normal
28
10.5
28
112
28
14
28
196
The reliability curve calculated by the method presented in this paper is rather different from the results by taking the average of environmental factors and different parameters for the same distribution have obvious impact on reliability. Under the condition of same average and variance, the curves of Gamma, TGamma, and Normal distributed temperature is different too.
modelled by giving a distribution to the parameter z and a .
The reliability function follows
Five units were subjected to an accelerated degradation test at each of 60°C, 85°C , 110°C
significant variance.
CONCLUSION
where and are density functions for z and a. Gamma, transformed-Gamma (T-Gamma) and Normal distribution with different parameters are employed to model
Results indicates that properly modeled (proper distribution type and parameters) environmental stress is the fundamental of varied environment oriented reliability