I
AE
S
I
nte
rna
t
io
na
l J
o
urna
l o
f
Art
if
icia
l In
t
ellig
ence
(
I
J
-
AI
)
Vo
l.
9
,
No
.
3
,
Sep
t
em
b
er
2020
,
p
p
.
5
45
~
5
52
I
SS
N:
2252
-
8938
,
DOI
: 1
0
.
1
1
5
9
1
/i
j
ai.
v
9
.i
3
.
p
p
5
45
-
5
52
545
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
i
.
ia
esco
r
e.
co
m
Desig
n and
i
m
ple
m
en
tatio
n of
w
ire
less
sy
ste
m
f
o
r vi
bra
tion
fault de
tec
tion usi
ng
f
u
zz
y
log
ic
M
o
neer
Ali Li
lo
1
,
M
a
a
t
h J
a
s
e
m
M
a
ha
m
m
a
d
2
1
De
p
a
rtme
n
t
o
f
Ch
e
m
ic
a
l
En
g
in
e
e
rin
g
,
A
l
M
u
th
a
n
n
a
Un
iv
e
rsity
,
Ira
q
2
De
p
a
rtme
n
t
o
f
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
,
Un
iv
e
rsity
o
f
A
n
b
a
r,
Ira
q
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
A
p
r
2
0
,
2
0
20
R
ev
i
s
ed
J
u
n
7
,
2
0
20
A
cc
ep
ted
J
u
n
13
,
2
0
20
T
h
is
p
a
p
e
r
p
re
se
n
ts
th
e
w
irele
ss
s
y
ste
m
f
o
r
fa
u
lt
d
e
tec
ti
o
n
a
n
d
m
o
n
it
o
rin
g
b
a
se
d
o
n
f
u
z
z
y
lo
g
ic
tec
h
n
iq
u
e
.
W
irele
ss
a
p
p
li
c
a
ti
o
n
s
a
re
u
ti
li
z
e
d
to
i
d
e
n
ti
f
y
,
c
las
si
fy
,
a
n
d
m
o
n
it
o
r
f
a
u
lt
s in
t
h
e
re
a
l
ti
m
e
to
p
ro
tec
t
m
a
c
h
in
e
s
f
ro
m
d
a
m
a
g
e
.
Tw
o
sc
h
e
m
e
s
w
e
r
e
tes
te
d
;
f
irst
sc
h
e
m
e
f
a
u
lt
c
o
ll
e
c
ted
X
-
Y
-
Z
-
a
x
e
s
m
o
d
e
w
h
il
e
th
e
se
c
o
n
d
sc
h
e
m
e
c
o
ll
e
c
te
d
Y
-
a
x
is
m
o
d
e
,
w
h
ich
is
u
ti
li
z
e
d
to
p
ro
tec
t
th
e
in
d
u
c
ti
o
n
m
o
to
r
(IM
)
f
ro
m
v
ib
ra
ti
o
n
s
f
a
u
lt
.
T
h
e
v
ib
ra
ti
o
n
sig
n
a
ls
w
e
re
p
ro
c
e
ss
e
d
in
th
e
c
e
n
tral
c
o
m
p
u
ter
to
re
d
u
c
e
n
o
ise
b
y
si
g
n
a
l
p
ro
c
e
ss
in
g
sta
g
e
,
a
n
d
th
e
n
th
e
f
a
u
lt
w
a
s
c
las
si
f
ied
a
n
d
m
o
n
it
o
re
d
b
a
se
d
o
n
F
u
z
z
y
Lo
g
ic
(F
L
).
T
h
e
w
irele
ss
v
ib
ra
ti
o
n
se
n
so
r
w
a
s
d
e
sig
n
e
d
d
e
p
e
n
d
in
g
o
n
t
h
e
w
irele
s
s
tec
h
n
iq
u
e
s
a
n
d
C+
+
c
o
d
e
.
A
f
a
u
lt
c
o
ll
e
c
ti
o
n
,
n
o
ise
re
d
u
c
ti
o
n
,
v
ib
r
a
ti
o
n
f
a
u
lt
c
las
si
f
ica
ti
o
n
a
n
d
m
o
n
it
o
rin
g
w
e
r
e
i
m
p
le
m
e
n
ted
b
y
M
AT
LA
B
c
o
d
e
.
In
th
e
se
c
o
n
d
sc
h
e
m
e
th
e
p
ro
c
e
ss
e
d
re
a
l
ti
m
e
w
a
s
re
d
u
c
e
d
to
6
0
%
,
w
h
ich
is
in
c
lu
d
e
d
c
o
ll
e
c
ti
o
n
,
f
il
terin
g
,
a
n
d
m
o
n
it
o
ri
n
g
f
a
u
lt
le
v
e
l.
Re
su
lt
s
s
h
o
w
e
d
th
a
t
th
e
sy
ste
m
h
a
s
th
e
a
b
il
it
y
to
e
a
rl
y
d
e
tec
t
th
e
f
a
u
l
t
o
c
c
u
rre
n
c
e
o
n
th
e
m
a
c
h
in
e
w
it
h
p
ro
c
e
ss
in
g
ti
m
e
o
f
1
.
7
2
1
s.
T
h
is
w
o
rk
w
il
l
re
d
u
c
e
t
h
e
m
a
in
ten
a
n
c
e
c
o
st
a
n
d
p
ro
v
i
d
e
th
e
a
b
il
it
y
to
u
ti
li
z
e
th
e
s
y
ste
m
w
it
h
h
a
rsh
in
d
u
strial
a
p
p
li
c
a
ti
o
n
s
to
d
iag
n
o
se
th
e
f
a
u
lt
i
n
re
a
l
ti
m
e
p
ro
c
e
ss
in
g
.
K
ey
w
o
r
d
s
:
Fau
lt
d
etec
tio
n
Fu
zz
y
lo
g
ic
R
ea
l ti
m
e
p
r
o
ce
s
s
in
g
Sig
n
als p
r
o
ce
s
s
i
n
g
W
ir
eless
s
en
s
o
r
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Ma
ath
J
ase
m
Ma
h
a
m
m
ad
,
Dep
ar
t
m
en
t o
f
E
lectr
ical,
C
o
ll
eg
e
o
f
E
n
g
i
n
ee
r
in
g
,
U
n
i
v
er
s
it
y
o
f
An
b
ar
,
I
r
aq
.
E
m
ail:
m
aa
t
h
.
m
a
h
a
m
m
ad
@
u
o
an
b
ar
.
ed
u
.
iq
1.
I
NT
RO
D
UCT
I
O
N
I
n
d
u
ctio
n
m
o
to
r
(
I
M)
is
i
m
p
o
r
tan
t
in
i
n
d
u
s
tr
ial
ap
p
licatio
n
s
.
I
t
ca
n
b
e
u
tili
ze
d
as
a
p
r
i
m
e
m
o
v
er
f
o
r
th
e
elec
tr
icit
y
g
e
n
er
atio
n
.
Ho
w
e
v
er
,
th
e
v
ib
r
atio
n
f
a
u
lt
s
p
r
ea
d
s
th
r
o
u
g
h
o
u
t
th
e
m
ac
h
in
e
an
d
s
u
b
s
eq
u
e
n
tl
y
d
am
a
g
e
s
th
e
s
y
s
te
m
i
f
it
is
h
i
g
h
e
n
o
u
g
h
.
R
e
s
ea
r
ch
e
s
p
r
o
p
o
s
ed
th
e
r
ed
u
ctio
n
,
p
r
ev
en
tio
n
,
an
d
m
o
n
ito
r
in
g
o
f
th
e
f
au
l
t
lev
e
l
b
ased
o
n
s
p
ec
i
f
ic
co
n
d
itio
n
s
[
1
-
2
]
.
T
h
e
v
ib
r
atio
n
f
a
u
lt
i
s
a
n
eu
tr
al
p
h
en
o
m
e
n
o
n
li
n
k
ed
to
s
tatic
an
d
d
y
n
a
m
ic
s
y
s
te
m
s
.
I
t
is
also
p
r
o
p
o
r
tio
n
al
to
th
e
lo
ad
ap
p
lied
o
n
th
e
m
ac
h
in
e
an
d
s
p
ee
d
[
3
-
4
]
.
Mo
s
t
r
esear
ch
e
s
i
n
te
n
d
ed
to
p
r
o
tect
th
e
m
ac
h
in
e
f
r
o
m
d
a
m
ag
e
s
b
y
m
o
n
ito
r
i
n
g
t
h
e
f
au
l
t
an
d
s
h
u
tti
n
g
d
o
w
n
th
e
s
y
s
te
m
,
esp
ec
iall
y
if
t
h
e
f
au
lt
lie
s
in
t
h
e
d
an
g
er
o
u
s
zo
n
e.
T
h
ese
p
r
o
ce
s
s
es
lead
t
o
th
e
r
ed
u
ctio
n
o
f
m
ai
n
ten
a
n
ce
co
s
t
s
as it sa
v
es t
h
e
m
ac
h
i
n
e
f
r
o
m
d
a
m
a
g
es [
5
]
.
T
h
e
w
ir
eless
tec
h
n
iq
u
e
u
s
es
elec
tr
o
m
a
g
n
etic
w
av
e
s
f
o
r
th
e
tr
an
s
ce
iv
er
o
f
th
e
d
ata.
W
ith
elec
tr
o
m
a
g
n
etic
w
a
v
e
s
,
in
te
n
d
ed
d
is
tan
ce
s
ca
n
b
e
f
ar
,
s
u
c
h
as
k
ilo
m
eter
s
f
o
r
s
p
ac
e
r
ad
io
co
m
m
u
n
icatio
n
s
o
r
as
s
h
o
r
t,
as
B
lu
eto
o
th
.
T
h
e
elec
tr
o
m
a
g
n
etic
i
n
cl
u
d
es
d
i
f
f
er
e
n
t
k
i
n
d
s
o
f
f
i
x
ed
,
m
o
b
ile
a
n
d
p
o
r
tab
le
ap
p
licatio
n
s
.
R
ec
e
n
tl
y
,
th
e
W
ir
el
ess
tech
n
iq
u
e
w
a
s
u
s
ed
in
m
an
y
ap
p
licatio
n
s
s
u
c
h
as
d
ata
s
a
n
d
s
f
o
r
th
e
ca
m
er
a,
r
o
b
o
tic
co
n
tr
o
l,
f
au
lt,
an
d
w
ir
ele
s
s
l
y
p
o
w
er
t
r
an
s
m
is
s
io
n
[
6
-
7
]
.
T
h
er
e
ar
e
m
an
y
s
tan
d
ar
d
s
u
t
ili
ze
d
f
o
r
tr
an
s
ce
iv
er
d
ata
w
it
h
w
ir
ele
s
s
s
e
n
s
o
r
n
et
w
o
r
k
w
h
er
e
s
elec
tin
g
s
tan
d
ar
d
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
9
,
No
.
3
,
Sep
t
e
m
b
er
20
20
:
5
4
5
–
5
52
546
w
il
l
b
e
b
ased
o
n
t
h
e
p
o
w
er
co
n
s
u
m
p
tio
n
,
t
h
e
d
is
tan
ce
o
f
th
e
tr
an
s
ce
i
v
er
,
f
r
eq
u
e
n
c
y
b
an
d
,
an
d
w
ir
eles
s
n
et
w
o
r
k
ap
p
licatio
n
s
[
8
-
9
]
.
I
n
d
u
s
tr
ial
w
ir
eles
s
s
e
n
s
o
r
n
et
w
o
r
k
s
(
I
W
SNs
)
,
s
u
ch
a
s
Z
i
g
B
ee
,
I
E
E
E
8
0
2
.
1
5
.
4
,
an
d
I
S
A
1
0
0
w
er
e
u
tili
ze
d
i
n
m
an
y
ap
p
licatio
n
s
to
a
u
g
m
e
n
t
th
e
f
lex
ib
il
it
y
o
f
d
ata
co
llec
tio
n
a
n
d
r
ed
u
ce
t
h
e
co
s
t
o
f
s
y
s
te
m
i
m
p
le
m
en
ta
tio
n
[
1
0
-
1
2
]
.
R
esear
ch
er
s
r
elied
o
n
I
E
E
E
s
ta
n
d
ar
d
s
s
u
ch
a
s
Z
i
g
B
ee
,
an
d
I
S
A
100
to
g
ath
er
d
ata
f
r
o
m
i
n
d
u
s
tr
ial
an
d
g
r
ee
n
h
o
u
s
e
ap
p
licatio
n
s
[
1
3
-
1
4
]
.
R
ec
en
t
l
y
,
I
W
SN
h
y
b
r
id
ized
w
it
h
ar
ti
f
icial
i
n
telli
g
e
n
ce
(
AI
)
tech
n
iq
u
e
s
s
u
ch
a
s
Neu
r
al
Net
w
o
r
k
(
NN)
,
Fu
zz
y
L
o
g
ic
(
F
L
)
,
an
d
Su
p
p
o
r
t
Vec
to
r
Ma
ch
i
n
e
(
S
V
M)
to
i
m
p
le
m
e
n
t
s
m
ar
t
w
ir
ele
s
s
s
y
s
te
m
s
[
1
5
-
1
6
]
.
A
I
w
as
u
s
ed
o
w
i
n
g
to
its
ca
p
ab
ilit
y
f
o
r
s
ig
n
al
id
en
tif
icat
io
n
an
d
class
if
icatio
n
in
a
ti
m
e
o
r
a
f
r
eq
u
en
c
y
d
o
m
ai
n
[
1
7
-
1
8
]
.
Fu
zz
y
L
o
g
ic
w
a
s
u
s
ed
to
d
escr
ib
e
th
e
m
ac
h
i
n
e
b
eh
a
v
io
r
s
b
y
clas
s
i
f
y
i
n
g
th
e
s
y
s
te
m
s
’
s
it
u
atio
n
d
u
r
in
g
t
h
e
r
ea
l
ti
m
e
p
r
o
ce
s
s
i
n
g
[
1
9
-
2
0
]
.
Fu
zz
y
lo
g
ic
is
a
w
id
el
y
u
s
ed
w
id
eb
an
d
f
o
r
co
n
tr
o
l
an
d
p
r
o
tectio
n
en
h
a
n
ce
s
y
s
te
m
b
eh
a
v
io
r
[
2
1
-
2
2
]
.
So
m
e
p
r
o
p
o
s
als
w
er
e
f
o
c
u
s
ed
o
n
h
y
b
r
id
f
u
zz
y
lo
g
ic
w
i
th
o
th
er
tec
h
n
iq
u
e
s
f
o
r
p
r
ec
is
io
n
i
m
p
r
o
v
e
m
e
n
t o
f
th
e
s
y
s
te
m
co
n
tr
o
l,
a
n
d
d
ec
is
i
o
n
m
a
k
i
n
g
f
o
r
w
it
h
t
h
e
p
r
o
tectio
n
s
y
s
te
m
[
23
-
2
5
]
.
Ma
n
y
r
e
s
ea
r
ch
es
w
er
e
in
ter
e
s
t
ed
in
clas
s
if
y
i
n
g
an
d
id
e
n
ti
f
y
i
n
g
th
e
f
a
u
lt b
y
a
ce
n
tr
al
co
m
p
u
ter
af
ter
t
h
e
d
ata
i
s
co
llected
v
ia
w
ir
ele
s
s
s
en
s
o
r
s
f
o
r
m
o
n
i
to
r
in
g
,
a
n
al
y
zi
n
g
,
an
d
co
n
tr
o
lli
n
g
[
2
6
-
2
7
]
.
T
h
e
Vib
r
atio
n
Fa
u
lt
Diag
n
o
s
is
o
f
a
m
ac
h
i
n
e
m
a
y
u
s
e
d
i
f
f
er
e
n
t
m
e
th
o
d
o
lo
g
ies
t
o
s
av
e
th
e
m
ac
h
in
e
f
r
o
m
d
a
m
ag
e
s
u
c
h
as
f
u
zz
y
,
n
eu
r
al
an
d
s
u
p
p
o
r
t
v
ec
to
r
m
a
ch
in
e
[
2
8
-
3
0
]
.
W
h
ile
t
h
is
m
e
th
o
d
o
lo
g
ies
h
y
b
r
id
w
i
th
w
ir
e
less
tec
h
n
o
lo
g
y
to
i
m
p
r
o
v
e
th
e
s
y
s
te
m
ap
p
licatio
n
s
f
o
r
in
d
u
s
tr
ial
an
d
b
e
u
til
ize
d
w
it
h
a
h
ar
s
h
en
v
ir
o
n
m
e
n
t [
3
1
]
.
I
n
[
3
2
]
,
au
t
h
o
r
p
r
o
p
o
s
ed
a
n
e
w
s
c
h
e
m
e
u
s
i
n
g
a
w
ir
eles
s
s
en
s
o
r
to
i
m
p
r
o
v
e
t
h
e
p
r
o
tectio
n
o
f
t
h
e
w
i
n
d
tu
r
b
in
e
f
r
o
m
v
ib
r
atio
n
f
a
u
lts
b
ased
o
n
th
e
p
r
ed
ictio
n
an
d
class
i
f
icatio
n
o
f
v
ib
r
atio
n
f
a
u
lts
.
T
h
is
w
o
r
k
d
id
n
o
t
f
o
cu
s
o
n
ar
tific
ial
i
n
tell
ig
e
n
t
t
ec
h
n
iq
u
e
f
o
r
th
e
f
au
l
t
d
etec
tio
n
.
I
n
[
3
3
]
i
m
p
le
m
e
n
ted
a
w
ir
e
less
s
en
s
o
r
th
a
t
h
as
th
e
ab
ilit
y
to
d
etec
t
lo
w
-
f
r
eq
u
en
c
y
v
alu
e
s
a
n
d
lo
w
-
a
m
p
lit
u
d
e
o
f
ac
ce
ler
atio
n
.
T
h
e
d
esi
g
n
d
ep
en
d
ed
o
n
t
h
e
co
n
v
er
s
io
n
o
f
th
e
o
u
tp
u
ts
o
f
th
e
p
h
y
s
ica
l
s
en
s
o
r
f
r
o
m
v
o
ltag
e
to
f
r
eq
u
en
c
y
.
T
h
e
co
n
v
e
n
tio
n
al
m
et
h
o
d
d
ep
en
d
s
o
n
tr
an
s
f
er
r
in
g
d
ata
f
r
o
m
an
alo
g
-
to
-
d
ig
ital,
w
h
i
l
e
n
e
w
m
et
h
o
d
(
tr
an
s
f
er
v
o
lt
ag
e
to
f
r
eq
u
en
c
y
)
in
cr
ea
s
es
th
e
ac
c
u
r
ac
y
a
n
d
s
en
s
iti
v
it
y
o
f
t
h
e
f
a
u
lt
d
etec
tio
n
.
Ho
w
e
v
er
,
[
3
3
]
li
m
ited
b
y
er
r
o
r
s
,
w
ir
ele
s
s
p
r
o
to
co
l,
an
d
o
p
er
atin
g
r
an
g
e
w
h
ic
h
is
d
es
ig
n
ed
f
o
r
a
s
h
o
r
t
d
is
ta
n
ce
f
o
r
ap
p
licatio
n
s
o
f
civ
il
en
g
i
n
ee
r
in
g
.
I
n
[
3
4
]
d
e
v
elo
p
ed
a
s
y
s
te
m
to
m
ea
s
u
r
e
th
e
v
ib
r
atio
n
s
f
au
l
t
u
tili
z
in
g
an
d
r
o
id
d
ev
ices
co
n
n
ec
ted
v
ia
B
lu
eto
o
t
h
.
Data
w
er
e
e
v
al
u
ated
i
n
t
h
e
m
a
in
d
a
tab
ase
an
d
f
ed
to
th
e
p
o
r
tab
le
b
o
x
f
o
r
co
n
tr
o
lli
n
g
an
o
th
er
s
y
s
te
m
.
T
h
e
B
lu
eto
o
th
n
ee
d
s
h
i
g
h
p
o
w
er
an
d
d
o
es
n
o
t
u
s
e
f
o
r
f
ar
d
is
ta
n
ce
ap
p
licatio
n
s
w
h
ic
h
ar
e
r
ep
r
esen
ted
w
ea
k
o
f
d
esi
g
n
.
I
n
[
3
5
]
p
r
o
p
o
s
ed
a
w
ir
ele
s
s
s
y
s
te
m
to
co
n
tr
o
l
t
h
e
v
ib
r
atio
n
f
au
lt
o
n
t
h
e
b
ea
m
.
T
h
e
v
ib
r
atio
n
f
a
u
l
t
s
ig
n
al
w
as
an
a
l
y
ze
d
o
n
a
ce
n
t
r
al
co
m
p
u
ter
to
g
en
er
ate
s
i
g
n
al
f
o
r
r
ed
u
cin
g
th
e
b
ea
m
v
ib
r
atio
n
.
T
h
e
r
ea
l
tim
e
r
esp
o
n
s
e
an
d
r
eliab
ilit
y
w
er
e
i
m
p
r
o
v
ed
b
ased
o
n
th
e
wir
eless
tec
h
n
iq
u
e.
T
h
e
s
y
s
te
m
w
as
u
tili
ze
d
f
o
r
co
n
tr
o
llin
g
t
h
e
s
tatic
v
ib
r
atio
n
a
n
d
n
o
t
u
s
ed
f
u
zz
y
o
r
n
e
u
r
al
o
f
f
a
u
lt
a
n
al
y
s
i
s
.
I
n
[
3
6
]
,
au
th
o
r
p
r
ese
n
ted
a
s
y
s
te
m
b
ased
o
n
th
e
n
eu
r
al
te
ch
n
iq
u
e
to
d
iag
n
o
s
e
t
h
e
v
ib
r
at
io
n
f
a
u
lt
lev
el,
w
h
er
e
th
e
d
ata
w
as
g
a
th
er
ed
f
r
o
m
a
m
ac
h
i
n
e
w
it
h
i
n
th
e
n
o
d
es.
B
y
a
u
g
m
e
n
ti
n
g
th
e
s
a
m
p
li
n
g
r
at
e
f
o
r
th
e
g
ath
er
i
n
g
d
ata,
th
e
r
ea
l
ti
m
e
p
r
o
ce
s
s
in
g
w
a
s
p
r
o
lo
n
g
ed
.
T
h
e
s
y
s
te
m
was
i
n
ter
ested
in
t
h
e
co
n
s
u
m
p
ti
o
n
p
o
w
er
an
d
f
o
u
n
d
a
n
e
w
to
p
o
lo
g
y
f
o
r
th
e
W
SN
co
n
s
id
er
in
g
th
a
t th
e
f
a
u
lt d
etec
tio
n
ac
cu
r
ac
y
w
as n
o
t i
m
p
r
o
v
ed
.
A
s
y
s
te
m
to
id
en
ti
f
y
an
d
cla
s
s
i
f
y
t
h
e
v
ib
r
atio
n
f
a
u
lt
to
in
f
lu
e
n
ce
th
e
p
r
o
tectio
n
o
f
th
e
m
ac
h
i
n
e
w
a
s
p
r
esen
ted
b
y
[
1
5
]
.
T
h
e
s
y
s
te
m
w
as
i
m
p
le
m
e
n
ted
u
s
i
n
g
w
ir
ele
s
s
s
e
n
s
o
r
s
,
s
ig
n
al
p
r
o
ce
s
s
in
g
,
n
eu
r
al,
f
u
zz
y
,
an
d
d
ec
is
io
n
ca
r
d
.
5
1
2
b
y
tes
ar
e
r
elate
d
to
v
ib
r
atio
n
f
a
u
lt
i
n
t
h
r
ee
ax
e
s
a
n
d
s
p
ee
d
v
a
lu
e,
w
h
ic
h
ar
e
co
llected
f
r
o
m
t
h
e
W
SN.
A
l
s
o
,
th
e
s
y
s
te
m
r
elies o
n
th
e
t
w
o
s
ta
g
es o
f
t
h
e
A
I
(
n
e
u
r
al,
f
u
zz
y
)
to
id
en
tify
th
e
f
a
u
lt
s
ar
is
i
n
g
in
th
e
m
ac
h
i
n
e.
T
h
e
ti
m
e
p
r
o
ce
s
s
o
f
d
ata
co
llecti
n
g
,
f
ilter
i
n
g
,
an
d
an
al
y
zi
n
g
is
5
.
8
9
2
s
,
f
o
r
f
au
lt d
etec
tio
n
.
T
h
is
w
o
r
k
i
n
ten
d
s
to
d
esig
n
a
w
ir
ele
s
s
s
y
s
te
m
to
d
etec
t
th
e
r
ea
l
ti
m
e
v
ib
r
atio
n
f
a
u
lt
b
ased
o
n
a
f
u
zz
y
tech
n
iq
u
e.
I
t
ca
n
b
e
u
s
ed
to
p
r
o
tect
th
e
in
d
u
c
tio
n
m
o
to
r
f
r
o
m
th
e
v
ib
r
atio
n
f
au
l
t
th
at
m
a
y
d
estro
y
t
h
e
m
ac
h
i
n
e
if
it
is
b
ein
g
in
h
ig
h
lev
el.
T
h
e
s
y
s
te
m
m
o
n
ito
r
s
th
e
v
ib
r
ati
o
n
f
au
l
t
af
ter
d
etec
tin
g
b
y
ap
p
l
y
i
n
g
v
ib
r
atio
n
d
ata
to
f
u
zz
y
.
Mo
r
eo
v
er
,
t
h
e
r
ea
l
t
i
m
e
p
r
o
ce
s
s
i
s
i
m
p
r
o
v
ed
b
ased
o
n
t
h
e
w
ir
ele
s
s
a
n
d
f
u
zz
y
tec
h
n
iq
u
e
to
b
e
4
.
5
0
1
s
f
o
r
co
llectin
g
d
ata
in
3
-
ax
is
m
o
d
.
T
h
e
r
est
o
f
th
i
s
p
ap
er
is
o
r
g
an
ized
in
th
e
f
o
l
lo
w
i
n
g
o
r
d
er
:
th
e
f
ir
s
t
s
ec
t
io
n
d
escr
ib
es
th
e
in
tr
o
d
u
ctio
n
an
d
r
elate
d
w
o
r
k
s
,
t
h
e
s
ec
o
n
d
s
ec
tio
n
p
r
esen
t
s
th
e
m
et
h
o
d
o
lo
g
ical
d
esig
n
,
an
d
th
e
th
ir
d
s
ec
tio
n
s
h
o
w
s
co
m
p
let
e
s
y
s
te
m
d
esig
n
.
W
h
i
le,
in
th
e
f
o
u
r
th
s
ec
tio
n
th
e
r
e
s
u
l
t
s
,
th
e
la
s
t
s
ec
t
io
n
co
n
clu
d
es t
h
e
w
o
r
k
.
2.
M
E
T
H
O
DO
L
O
G
Y
I
n
th
is
w
o
r
k
,
th
e
s
y
s
te
m
i
s
i
m
p
le
m
en
ted
v
ia
t
w
o
co
d
es;
th
e
f
ir
s
t
is
li
n
k
ed
to
C
++
,
w
h
ic
h
is
u
s
ed
to
d
esig
n
an
d
i
m
p
le
m
en
t
th
e
W
ir
eless
Vib
r
atio
n
Se
n
s
o
r
(
W
VS)
an
d
w
ir
eles
s
s
p
ee
d
s
en
s
o
r
(
W
SS
)
.
T
h
e
W
SS
s
en
d
s
t
h
e
s
p
ee
d
d
ata
to
W
VS
,
an
d
th
e
d
ata
w
ill
b
e
co
llected
f
r
o
m
t
h
e
in
d
u
ctio
n
m
o
to
r
v
ia
W
VS
as
a
o
n
e
p
ac
k
et
af
ter
m
o
d
if
y
i
n
g
t
h
e
d
ata
o
f
s
p
ee
d
an
d
v
ib
r
atio
n
in
o
n
e
p
ac
k
et.
T
h
e
s
ec
o
n
d
co
d
e
in
v
o
lv
es
M
A
T
L
A
B
to
d
esig
n
th
e
s
ig
n
al
p
r
o
ce
s
s
i
n
g
an
d
f
u
zz
y
lo
g
ic
s
ta
g
es.
T
h
ese
s
tag
e
s
ar
e
u
s
ed
to
r
ed
u
ce
th
e
n
o
is
e,
tr
an
s
f
er
t
h
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Desig
n
a
n
d
imp
leme
n
ta
tio
n
o
f
w
ir
ele
s
s
s
y
s
tem
fo
r
vib
r
a
tio
n
fa
u
lt d
etec
tio
n
u
s
in
g
... (
Mo
n
ee
r
A
li Lilo
)
547
s
ig
n
al
to
f
r
eq
u
en
c
y
d
o
m
ai
n
,
an
d
id
en
tify
an
d
class
if
y
th
e
f
a
u
lt
in
t
h
e
m
ai
n
co
m
p
u
ter
.
Fi
n
all
y
,
th
e
in
teg
r
ated
s
y
s
te
m
h
as
t
h
e
ab
ilit
y
to
d
etec
t
lev
el
o
f
t
h
e
v
ib
r
atio
n
f
au
lt
an
d
alar
m
u
s
er
i
f
t
h
e
f
au
l
t
is
i
n
d
an
g
er
o
r
alar
m
zo
n
e.
Fi
g
u
r
e
1
s
h
o
w
s
th
e
f
lo
w
c
h
ar
t th
e
s
y
s
te
m
.
Fig
u
r
e
1
.
Flo
w
c
h
ar
t o
f
m
e
th
o
d
o
lo
g
y
an
d
m
ater
ia
l
C
o
m
p
lete
S
y
s
te
m
De
s
i
g
n
T
h
e
s
ch
e
m
e
h
a
s
b
ee
n
d
esi
g
n
e
d
to
r
ep
r
esen
t
w
ir
eles
s
s
y
s
te
m
f
o
r
f
a
u
lt
d
etec
t
io
n
s
s
h
o
w
n
i
n
Fig
u
r
e
1
.
T
h
is
s
ec
tio
n
p
r
o
v
id
es d
etails
p
er
tain
i
n
g
to
ea
ch
p
ar
t o
f
t
h
e
s
y
s
te
m
.
2
.
1
.
Wirele
s
s
s
ens
o
r
net
w
o
rk
i
m
ple
m
ent
a
t
io
n
T
w
o
w
ir
ele
s
s
s
en
s
o
r
s
w
er
e
u
s
ed
to
co
llect
th
e
d
ata
f
r
o
m
t
h
e
m
ac
h
i
n
e
a
n
d
o
n
e
co
o
r
d
in
a
to
r
,
w
h
ich
f
ee
d
s
th
e
d
ata
to
th
e
m
ain
co
m
p
u
ter
.
T
h
e
f
ir
s
t
s
en
s
o
r
is
W
VS,
w
h
ic
h
w
a
s
u
s
e
d
to
co
llect
v
ib
r
atio
n
d
ata
in
th
r
ee
an
d
o
n
e
ax
es.
T
h
e
s
ec
o
n
d
s
en
s
o
r
w
a
s
W
SS
an
d
it
w
as
u
s
ed
to
co
llect
th
e
s
p
ee
d
d
ata
o
f
th
e
m
ac
h
in
e
.
T
h
ese
s
en
s
o
r
s
(
W
VS,
W
SS
)
w
er
e
co
n
s
tr
u
c
ted
b
ased
o
n
th
e
m
icr
o
co
n
tr
o
ller
t
y
p
e
A
T
m
e
g
a3
2
8
,
th
e
Z
ig
B
ee
b
ased
o
n
th
e
I
E
E
E
8
0
2
.
1
5
.
4
P
HY
an
d
MA
C
la
y
er
s
,
L
i
th
i
u
m
b
atter
y
,
an
d
p
h
y
s
ic
s
en
s
o
r
.
T
h
e
d
if
f
er
en
ce
b
et
w
ee
n
th
e
W
V
S
an
d
W
SS
i
s
r
elate
d
to
th
e
p
h
y
s
ica
l
s
e
n
s
o
r
.
,
W
VS
ex
h
ib
ited
an
ac
ce
ler
atio
n
s
e
n
s
o
r
,
w
h
i
le,
W
SS
u
s
ed
a
m
a
g
n
e
tic
f
ield
s
e
n
s
o
r
i
n
t
h
e
W
S
S
to
co
llect
s
p
ee
d
d
ata.
A
ct
u
all
y
,
t
h
e
d
ata
o
f
th
e
v
ib
r
atio
n
f
au
l
t
an
d
t
h
e
s
p
ee
d
o
f
t
h
e
m
ac
h
i
n
e
w
ill
b
e
p
r
ep
ar
ed
as
a
o
n
e
p
a
ck
et
w
i
th
in
t
h
e
v
ib
r
atio
n
s
e
n
s
o
r
b
ef
o
r
e
s
en
d
i
n
g
.
Fin
all
y
,
t
h
e
m
ai
n
co
m
p
u
ter
co
llects
d
ata
f
r
o
m
W
SN
v
ia
a
co
o
r
d
in
ato
r
th
at
is
co
n
n
ec
ted
w
it
h
co
m
p
u
ter
s
as
a
o
n
e
p
ac
k
et
co
n
tai
n
i
n
g
t
h
e
ac
ce
ler
atio
n
an
d
s
p
ee
d
v
al
u
es.
2
.
2
.
Sig
na
l pro
ce
s
s
ing
s
t
a
g
e
T
h
e
r
a
w
d
ata
o
f
v
ib
r
atio
n
f
a
u
lt
co
n
tai
n
n
o
is
e(
s
)
as
s
h
o
w
n
i
n
F
i
g
u
r
e
2
o
w
i
n
g
to
t
h
e
elec
tr
o
m
a
g
n
etic
d
ev
ices,
w
h
ich
ca
u
s
es
er
r
o
r
s
in
t
h
e
f
a
u
lt a
m
p
lit
u
d
e.
T
h
e
d
ata
n
ee
d
to
b
e
f
ilter
ed
in
o
r
d
er
to
r
ed
u
ce
n
o
is
e
b
ased
o
n
th
e
b
an
d
p
ass
f
ilter
(
B
P
F
)
.
T
h
er
ea
f
ter
,
v
ib
r
atio
n
f
a
u
lt
s
ig
n
al
s
h
o
w
s
o
n
t
h
e
r
eso
n
a
n
t
f
r
eq
u
en
c
y
f
o
r
th
e
s
elec
ted
s
p
ee
d
.
T
h
u
s
,
th
e
lo
w
p
as
s
f
il
ter
(
L
P
F)
is
u
t
ilize
d
to
d
i
s
p
lay
t
h
e
f
a
u
lt
s
ig
n
al
i
n
th
e
s
e
f
r
eq
u
e
n
cie
s
.
T
h
en
,
th
e
v
ib
r
atio
n
f
a
u
lt
s
i
g
n
a
ls
p
o
s
t
-
f
i
ltra
tio
n
ar
e
tr
an
s
f
er
r
e
d
to
th
e
f
r
eq
u
e
n
c
y
d
o
m
ai
n
u
s
i
n
g
th
e
f
a
s
t
Fo
u
r
ier
tr
an
s
f
o
r
m
(
FF
T
)
alg
o
r
ith
m
[
3
7
]
.
S
t
a
r
t
W
S
N
I
n
s
t
a
l
l
a
t
i
o
n
a
c
c
e
l
e
r
a
t
i
o
n
s
e
n
s
o
r
c
a
l
i
b
r
a
t
e
d
C
o
l
l
e
c
t
i
n
g
a
n
d
p
r
o
c
e
s
s
i
n
g
d
a
t
a
C
l
a
s
s
i
f
y
i
n
g
d
a
t
a
b
y
F
u
z
z
y
L
o
g
i
c
M
o
n
i
t
o
r
i
n
g
t
h
e
f
a
u
l
t
l
e
v
e
l
F
a
u
l
t
i
n
d
a
n
g
e
r
z
o
n
e
E
n
d
w
i
t
h
a
l
a
r
m
F
u
z
z
y
L
o
g
i
c
m
e
m
b
e
r
s
h
i
p
d
e
s
i
g
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
9
,
No
.
3
,
Sep
t
e
m
b
er
20
20
:
5
4
5
–
5
52
548
Fig
u
r
e
2
.
R
a
w
v
ib
r
atio
n
f
au
lt f
o
r
th
e
Y
-
a
x
is
co
llected
f
r
o
m
wir
eless
s
e
n
s
o
r
2
.
3
.
F
uzzy
lo
g
ic
a
nd
m
o
nito
ring
s
t
a
g
e
T
h
e
d
ata
r
esu
lted
f
r
o
m
t
h
e
s
i
g
n
al
p
r
o
ce
s
s
in
g
s
tag
e
w
i
ll
b
e
f
ed
to
th
e
f
u
zz
y
lo
g
ic
f
o
r
id
en
t
if
y
in
g
a
n
d
class
i
f
y
in
g
v
ib
r
atio
n
f
a
u
lt
lev
e
l
o
n
I
M.
I
n
th
is
w
o
r
k
,
t
h
e
Su
g
en
o
Fu
zz
y
I
n
f
er
e
n
ce
S
y
s
te
m
(
SF
I
S)
w
a
s
s
elec
ted
to
m
o
n
ito
r
th
e
f
a
u
lt c
ase,
i
f
th
e
v
ib
r
atio
n
f
a
u
lt o
cc
u
r
s
in
t
h
e
s
ev
er
it
y
o
r
alar
m
zo
n
e.
A
ct
u
al
l
y
,
th
e
f
u
zz
y
s
y
s
te
m
w
a
s
u
s
ed
to
ap
p
ly
t
h
e
co
n
d
it
io
n
m
o
n
i
to
r
in
g
to
p
r
o
tect
th
e
I
M
f
r
o
m
v
ib
r
atio
n
f
a
u
lt
s
.
T
h
e
f
u
zz
y
s
y
s
te
m
i
s
d
esig
n
ed
w
it
h
t
w
o
i
n
p
u
t
s
th
a
t
ar
e
r
elate
d
to
th
e
v
ib
r
atio
n
f
a
u
lt a
n
d
t
h
e
s
p
ee
d
o
f
t
h
e
m
ac
h
in
e.
T
h
e
f
u
zz
y
o
u
tp
u
t
is
r
ep
r
esen
ted
b
y
o
n
e
o
u
tp
u
t
t
o
class
i
f
y
a
n
d
id
en
ti
f
y
th
e
f
a
u
l
t
lev
el,
as
s
h
o
w
n
i
n
F
i
g
u
r
e
3
.
T
h
e
m
ai
n
o
b
j
ec
tiv
e
o
f
u
s
i
n
g
f
u
zz
y
lo
g
ic
to
d
r
ag
o
n
s
a
n
d
class
i
f
y
v
ib
r
atio
n
f
au
l
t
lev
el.
T
h
u
s
,
th
e
“
e
x
p
er
t
ex
p
er
ien
ce
”
o
f
a
h
u
m
a
n
w
o
r
k
e
r
in
i
n
d
u
s
tr
ial
f
iled
an
d
th
e
I
SO
1
0
8
1
6
-
2
f
o
r
v
ib
r
atio
n
co
n
d
itio
n
s
i
s
in
co
r
p
o
r
ated
i
n
a
p
r
o
ce
s
s
w
h
o
s
e
in
p
u
t
-
o
u
tp
u
t
r
elatio
n
s
h
ip
is
d
e
s
cr
ib
ed
b
y
a
co
llecti
o
n
o
f
f
u
z
z
y
r
u
le
s
,
as
s
h
o
w
n
in
T
ab
le
1
.
W
h
er
e
R
SV
i
s
th
e
(
r
ed
u
ce
v
alu
e)
o
f
s
p
ee
d
,
an
d
SHD
is
m
ea
n
s
h
u
t
d
o
w
n
s
y
s
te
m
.
T
h
e
s
p
ee
d
v
alu
e
o
f
th
e
m
a
ch
in
e
w
a
s
u
s
ed
d
u
e
to
th
e
v
ib
r
atio
n
f
au
lt b
ein
g
af
f
ec
ted
b
y
t
h
e
s
p
ee
d
o
f
th
e
m
ac
h
in
e
[
3
7
]
.
T
ab
le
1
.
R
u
le
o
f
th
e
f
u
zz
y
lo
g
i
c
S
P
EED
(
r
p
m)
1
2
5
>
1
7
5
>
1
8
5
V
i
b
r
a
t
i
o
n
z
o
n
e
n
o
r
mal
A
c
c
p
.
A
c
c
p
.
A
c
c
p
.
A
l
a
r
m1
R
V
1
R
V
2
R
V
3
A
l
a
r
m2
R
V
2
R
V
3
R
V
4
A
l
a
r
m3
R
V
3
R
V
4
R
V
5
D
a
n
g
e
r
S
H
D
S
H
D
S
H
D
(
a)
(
b
)
Fig
u
r
e
3
.
(
a)
Fu
zz
y
s
y
s
te
m
co
n
s
tr
u
ctio
n
(
b
)
f
u
zz
y
m
e
m
b
er
s
h
ip
f
u
n
c
tio
n
s
3.
RE
SU
L
T
AND
DI
SCUS
SI
O
N
T
h
e
ac
ce
ler
atio
n
d
ata
co
llected
f
r
o
m
th
e
p
late
f
o
r
m
w
ill
b
e
co
llected
in
a
ti
m
e
d
o
m
ai
n
w
i
th
a
lar
g
e
a
m
o
u
n
t o
f
n
o
is
e,
as s
h
o
w
n
in
Fig
u
r
e
2
co
n
s
id
er
in
g
th
a
t th
e
a
cc
eler
atio
n
is
ex
p
r
es
s
ed
in
m
m
/s
2
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Desig
n
a
n
d
imp
leme
n
ta
tio
n
o
f
w
ir
ele
s
s
s
y
s
tem
fo
r
vib
r
a
tio
n
fa
u
lt d
etec
tio
n
u
s
in
g
... (
Mo
n
ee
r
A
li Lilo
)
549
3
.
1
.
T
i
m
e
pro
ce
s
s
ing
o
f
t
he
s
y
s
t
e
m
T
h
e
ac
ce
ler
atio
n
an
d
s
p
e
ed
d
ata
w
er
e
co
llected
f
r
o
m
t
h
e
w
ir
eless
s
e
n
s
o
r
s
n
et
w
o
r
k
.
T
h
e
m
ai
n
ch
al
len
g
es
f
o
r
u
s
in
g
th
e
w
ir
ele
s
s
s
e
n
s
o
r
te
ch
n
iq
u
e
ar
e
th
e
p
ac
k
et
lo
s
s
an
d
r
ea
l
ti
m
e
n
ee
d
ed
to
g
at
h
er
th
e
d
ata.
N
o
tab
ly
,
t
h
e
p
ac
k
et
lo
s
s
i
n
t
h
e
in
d
u
s
tr
ial
e
n
v
ir
o
n
m
en
t
is
p
r
eo
p
er
atio
n
al
to
th
e
d
is
tan
ce
o
f
t
h
e
n
o
d
es,
w
h
ile
t
h
e
r
ea
l
ti
m
e
d
ep
en
d
s
o
n
th
e
le
n
g
th
o
f
t
h
e
d
ata
[
1
5
,
38]
.
I
t
s
ee
m
s
th
a
t
t
h
e
s
ch
e
m
e
is
u
s
ed
to
m
a
n
ag
e
d
ata
co
llectio
n
f
r
o
m
W
SN
to
i
m
p
r
o
v
e
t
h
e
r
eliab
ilit
y
o
f
th
e
s
y
s
te
m
.
T
h
is
s
ch
e
m
e
co
llects
th
e
d
ata
f
r
o
m
th
e
r
o
u
ter
as
a
o
n
e
p
ac
k
et
m
ad
e
u
p
o
f
th
e
ac
ce
ler
atio
n
an
d
s
p
ee
d
d
ata.
I
n
th
e
m
ai
n
co
m
p
u
ter
,
th
e
d
ata
w
ill
b
e
s
e
p
ar
ated
to
th
e
ac
ce
ler
atio
n
d
ata
t
h
at
ar
e
u
s
ed
i
n
s
i
g
n
a
l
p
r
o
ce
s
s
in
g
s
tag
e,
w
h
ile
t
h
e
s
p
ee
d
v
alu
e
s
w
ill
b
e
f
ed
to
th
e
f
u
zz
y
s
ta
g
e
to
co
n
f
ir
m
t
h
e
d
ec
is
io
n
.
T
h
e
p
ac
k
et
len
g
t
h
in
t
h
i
s
w
o
r
k
i
s
3
8
5
in
teg
er
v
alu
e
o
f
ac
ce
ler
at
io
n
a
n
d
o
n
e
v
alu
e
o
f
s
p
ee
d
f
o
r
R
P
M,
X,
Y
,
Z
-
ax
is
s
ch
e
m
e.
T
h
e
r
ea
l
ti
m
e
p
r
o
ce
s
s
in
g
w
il
l
b
e
i
m
p
r
o
v
ed
o
w
i
n
g
to
th
e
co
llected
o
n
e
v
alu
e
o
f
s
p
ee
d
ev
er
y
1
2
9
v
alu
es
o
f
ac
ce
ler
atio
n
f
o
r
R
P
M,
Y
-
a
x
is
s
c
h
e
m
e.
T
h
e
r
ea
l
ti
m
e
n
ee
d
ed
to
co
llect
th
e
p
ac
k
ets
th
at
ar
e
co
n
tai
n
ed
in
t
h
ese
d
ata
ar
e
r
elate
d
to
1
2
8
*
3
s
a
m
p
les,
a
n
d
th
e
o
n
e
v
alu
e
o
f
s
p
ee
d
is
4
.
4
5
s
.
Mo
r
eo
v
er
,
th
e
r
ea
l
ti
m
e
p
r
o
ce
s
s
i
n
g
o
f
g
at
h
er
in
g
d
ata
w
it
h
len
g
t
h
1
2
9
f
o
r
ac
ce
ler
at
io
n
an
d
o
n
e
v
al
u
e
o
f
s
p
ee
d
i
s
1
.
6
7
s
.
T
h
ese
v
a
lu
e
s
ar
e
d
ep
icted
in
T
ab
le
2
.
T
h
e
r
eal
-
ti
m
e
p
r
o
ce
s
s
i
n
g
i
n
t
h
is
w
o
r
k
w
as
r
ed
u
ce
d
b
y
3
0
%
co
m
p
ar
is
o
n
w
i
th
[
1
5
]
.
T
h
at
ti
m
e
p
r
o
ce
s
s
i
n
g
is
r
elate
d
to
d
ata
p
r
o
ce
s
s
in
g
o
f
t
h
e
th
r
ee
a
x
es sc
h
e
m
e.
T
ab
le
2
.
T
im
e
p
r
o
ce
s
s
in
g
o
f
t
h
e
t
w
o
s
c
h
e
m
es
S
c
h
e
me
c
o
l
l
e
c
t
i
o
n
P
a
c
k
e
t
l
e
n
g
t
h
T
i
me
c
o
l
l
e
c
t
i
o
n
v
i
a
M
A
TL
A
B
(
s)
F
u
z
z
y
p
r
o
c
e
ssi
n
g
(
s)
C
o
mp
u
t
e
r
B
u
d
R
a
t
e
S
a
mp
l
e
s/
t
i
me
(
S
a
mp
l
i
n
g
r
a
t
e
)
S
e
n
so
r
c
o
n
v
e
n
i
e
n
t
T
i
me
p
r
o
c
e
ssi
n
g
O
v
e
r
a
l
l
(
s)
R
P
M
,
X
,
Y
,
Z
3
8
5
4
.
4
5
0
.
0
5
1
1
9
2
0
0
8
8
.
8
0
~
4
0
H
z
4
.
5
0
1
R
P
M
,
Y
1
2
9
1
.
6
7
0
.
0
5
1
1
9
2
0
0
8
8
.
8
0
~
4
0
H
z
1
.
7
2
1
3
.
2
.
Sig
na
l pro
ce
s
s
ing
s
t
a
g
e
T
h
e
d
ata
f
r
o
m
t
h
e
W
SN
s
ta
g
e
w
il
l
b
e
f
ed
to
th
e
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
s
ta
g
e
to
r
ed
u
ce
t
h
e
n
o
is
e
co
llected
w
it
h
th
e
r
a
w
d
ata
v
ia
u
s
i
n
g
t
h
e
L
o
w
P
as
s
Fi
lter
(
L
P
F)
an
d
B
an
d
P
ass
Fil
ter
(
B
P
F).
T
h
e
f
i
n
al
d
ata
f
r
o
m
t
h
e
f
iltra
tio
n
w
il
l
tr
a
n
s
f
er
t
h
e
f
r
eq
u
en
c
y
d
e
m
i
n
e
u
s
i
n
g
t
h
e
F
FT
tech
n
iq
u
e.
T
h
r
ee
m
o
d
es
o
f
v
ib
r
atio
n
s
i
g
n
al
w
h
ic
h
ar
e
v
elo
cit
y
,
ac
ce
ler
atio
n
a
n
d
d
is
p
lace
m
e
n
t.
T
h
e
v
elo
cit
y
m
o
d
e
is
r
ep
r
esen
ted
th
e
v
ib
r
atio
n
f
au
l
t
in
th
is
w
o
r
k
.
T
h
e
v
elo
cit
y
(
v
elo
cit
y
v
ib
r
atio
n
f
a
u
lt
m
o
d
e)
d
ata
is
e
x
p
r
ess
e
d
in
m
m
/
s
.
T
h
e
r
esu
lt
s
s
h
o
w
n
in
Fi
g
u
r
e
4
ar
e
th
e
v
ib
r
atio
n
f
a
u
lt
v
a
lu
e
s
af
ter
b
ein
g
f
ilter
ed
an
d
co
n
v
er
ted
b
y
L
P
F,
B
P
F,
an
d
FF
T
,
w
h
er
e
th
e
r
eso
n
an
t
f
r
eq
u
en
c
y
o
f
th
e
I
M
is
(
1
7
5
r
p
m
)
.
Fi
g
u
r
e
4
(
a)
s
h
o
w
s
th
e
r
es
u
lt
o
f
th
e
s
ig
n
al
p
r
o
ce
s
s
i
n
g
s
tag
e
f
o
r
th
e
f
ir
s
t
s
ch
e
m
e
w
h
ic
h
i
s
co
llec
ted
th
e
R
P
M
,
X,
Y,
Z
-
a
x
i
s
,
w
h
ile,
Fi
g
u
r
e
4
(
b
)
s
h
o
w
s
t
h
e
r
es
u
lt
a
f
ter
p
r
o
ce
s
s
in
g
t
h
e
r
a
w
d
ata
o
f
s
ec
o
n
d
s
c
h
e
m
e
t
h
at
is
co
llected
t
h
e
R
P
M,
Y
-
ax
is
.
T
h
e
v
ib
r
atio
n
f
a
u
lt
a
m
p
lit
u
d
es
w
er
e
ca
lc
u
lated
b
ased
o
n
(
1
)
,
w
h
ile
th
e
s
p
ee
d
o
f
I
M
is
m
ea
s
u
r
ed
as
f
r
eq
u
en
c
y
b
ased
o
n
(
2
)
.
(
1
)
(
2
)
w
h
er
e
a
d
en
o
tes
th
e
ac
ce
ler
atio
n
m
o
d
e
o
f
v
ib
r
atio
n
f
au
l
t,
=
2
,
an
d
is
th
e
f
r
eq
u
en
c
y
o
f
th
e
m
ac
h
in
e
(
Hz)
[
1
5
]
.
(
a)
(
b
)
Fig
u
r
e
4
.
R
esu
lt o
f
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
s
tag
e
(
a)
X,
Y,
Z
-
a
x
es (
b
)
f
o
r
th
e
Y
-
a
x
is
s
ch
e
m
e
s
i
n
a
A
t
s
p
e
e
d
r
p
m
6
0
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
9
,
No
.
3
,
Sep
t
e
m
b
er
20
20
:
5
4
5
–
5
52
550
3
.
3
.
F
uzzy
lo
g
ic
s
t
a
g
e
t
hro
u
g
hp
ut
I
n
th
is
w
o
r
k
,
t
h
e
s
u
g
e
n
o
FIS
tech
n
iq
u
e
w
as
co
n
s
tr
u
cted
to
class
i
f
y
a
n
d
id
en
ti
f
y
t
h
e
f
a
u
lt
le
v
els
b
ased
o
n
d
if
f
er
en
t
co
n
d
it
io
n
s
.
T
h
e
f
u
zz
y
tec
h
n
iq
u
e
w
a
s
i
m
p
le
m
en
ted
u
s
i
n
g
t
w
o
in
p
u
t
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
(
MF
s
)
;
th
e
f
ir
s
t
MF
w
as
d
esi
g
n
ed
b
ased
o
n
co
n
d
itio
n
s
o
f
I
SO
1
0
8
1
6
-
3
to
id
en
tify
an
d
clas
s
i
f
y
t
h
e
v
ib
r
atio
n
f
au
l
ts
,
w
h
ile
t
h
e
s
ec
o
n
d
d
escr
ib
ed
th
e
I
M
s
p
ee
d
.
T
h
e
o
u
tp
u
t
MF
was
co
n
s
tr
u
cted
to
clas
s
i
f
y
th
e
v
ib
r
atio
n
f
au
lt
le
v
el,
as
s
h
o
w
n
i
n
Fig
u
r
e
3
.
T
h
e
m
ai
n
p
u
r
p
o
s
e
o
f
u
s
in
g
th
e
F
u
zz
y
tec
h
n
iq
u
e
i
s
to
clas
s
i
f
y
th
e
f
au
lt
s
itu
a
tio
n
s
.
A
l
s
o
,
f
u
zz
y
r
es
u
lt
w
ill
g
e
n
er
at
e
lin
ea
r
s
i
g
n
a
ls
a
s
s
h
o
w
n
i
n
F
i
g
u
r
e
5
to
r
ep
r
esen
t
n
o
n
-
lin
ea
r
b
eh
av
io
r
s
y
s
te
m
as
s
h
o
w
n
i
n
F
i
g
u
r
e
2
.
T
h
u
s
,
th
e
o
u
tp
u
t
r
es
u
lt
f
r
o
m
f
u
zz
y
p
r
o
v
id
es
th
e
s
tab
ilit
y
o
f
th
e
m
ac
h
i
n
e
co
n
tr
o
l.
T
h
e
s
ig
n
a
l
o
f
f
u
zz
y
ca
n
b
e
f
ed
to
th
e
co
n
tr
o
l
s
y
s
te
m
f
o
r
p
r
o
tectin
g
t
h
e
m
ac
h
i
n
e
f
r
o
m
f
au
lt
i
f
it
is
i
n
t
h
e
d
an
g
er
zo
n
e.
T
h
e
r
esu
lts
o
f
t
h
i
s
r
esear
ch
s
h
o
w
t
h
at
r
ea
l
ti
m
e
p
r
o
ce
s
s
i
n
g
d
ec
r
ea
s
ed
to
1
.
7
2
1
s
if
th
e
v
ib
r
a
tio
n
f
a
u
lt
w
a
s
co
llected
w
ith
o
n
e
ax
is
o
n
l
y
,
a
s
s
h
o
w
n
i
n
T
ab
le
2
.
T
h
is
p
r
o
ce
s
s
w
il
l
i
m
p
r
o
v
e
t
h
e
r
ea
l
ti
m
e
p
r
o
tectio
n
a
n
d
co
n
d
itio
n
m
o
n
ito
r
in
g
f
o
r
m
ac
h
in
e
f
a
u
lt
d
iag
n
o
s
is
.
O
n
th
e
o
th
er
h
an
d
,
th
e
co
llected
th
r
ee
ax
es
o
f
t
h
e
v
ib
r
atio
n
f
au
lt
w
ill
in
cr
ea
s
e
t
h
e
ac
c
u
r
ac
y
o
f
t
h
e
f
au
l
t
d
etec
tio
n
wh
ich
is
u
s
ed
f
o
r
f
au
lt
an
a
l
y
s
is
an
d
p
r
o
tects
t
h
e
ex
p
en
s
iv
e
m
ac
h
in
e.
Fin
all
y
,
t
h
e
f
u
zz
y
o
u
tp
u
t
w
it
h
d
if
f
er
en
t
s
p
ee
d
v
al
u
es
s
h
o
w
t
h
at
t
h
e
v
ib
r
atio
n
f
au
l
t
is
s
u
cc
es
s
f
u
ll
y
id
en
ti
f
ied
b
y
f
u
zz
y
lo
g
ic.
C
o
m
p
ar
i
n
g
th
e
v
al
u
es
i
n
F
ig
u
r
es
2
an
d
5
allo
w
s
u
s
to
el
u
cid
at
e
th
e
i
m
p
r
o
v
e
m
e
n
t
o
f
th
e
s
y
s
te
m
b
e
h
av
io
r
to
p
r
o
d
u
ce
s
m
o
o
th
s
i
g
n
a
l
(
f
u
zz
y
o
u
tp
u
t)
to
r
ep
r
esen
t
co
m
p
lex
s
i
g
n
al
s
(
r
a
w
v
ib
r
atio
n
f
au
l
t)
an
d
s
u
c
ce
s
s
f
u
l
l
y
id
en
tify
an
d
clas
s
i
f
y
t
h
e
v
ib
r
atio
n
f
a
u
lt
d
u
r
i
n
g
r
ea
l
ti
m
e
p
r
o
ce
s
s
in
g
.
T
h
u
s
,
t
h
ese
s
y
s
te
m
t
h
r
o
u
g
h
p
u
ts
ca
n
b
e
u
s
ed
w
it
h
t
h
e
p
r
o
tectio
n
s
y
s
te
m
s
w
it
h
o
u
t
i
n
ter
f
er
i
n
g
w
it
h
th
e
co
n
tr
o
l
s
y
s
te
m
s
tab
ilit
y
.
Fig
u
r
e
5
.
S
y
s
te
m
o
u
tp
u
t
w
it
h
d
if
f
er
e
n
t sp
ee
d
s
v
a
lu
e
4.
CO
NCLU
SI
O
NS
T
h
is
w
o
r
k
i
n
v
o
l
v
es
t
h
e
v
ib
r
atio
n
a
n
d
s
p
ee
d
d
ata
co
llecti
o
n
f
r
o
m
w
ir
ele
s
s
v
ib
r
atio
n
s
en
s
o
r
an
d
w
ir
ele
s
s
s
p
ee
d
s
en
s
o
r
.
Data
co
llected
ar
e
p
r
o
ce
s
s
ed
in
m
ai
n
co
m
p
u
ter
to
d
iag
n
o
s
e
a
n
d
class
i
f
y
t
h
e
v
ib
r
atio
n
f
au
lt b
ased
o
n
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
an
d
f
u
zz
y
lo
g
ic
in
r
ea
l ti
m
e
p
r
o
ce
s
s
in
g
.
T
h
ese
p
r
o
ce
s
s
p
r
o
d
u
cts t
h
e
in
d
u
ctio
n
m
o
to
r
f
r
o
m
v
ib
r
atio
n
f
a
u
lt
i
f
it
is
in
th
e
d
an
g
er
le
v
el.
R
e
d
u
cin
g
n
o
i
s
e
an
d
tr
an
s
f
er
r
in
g
th
e
s
i
g
n
al
to
th
e
f
r
eq
u
en
c
y
d
o
m
ai
n
w
h
ic
h
is
d
o
n
e
v
ia
s
ig
n
al
p
r
o
ce
s
s
in
g
.
T
h
u
s
,
th
e
v
ib
r
atio
n
f
a
u
lt
w
a
s
id
en
ti
f
ied
an
d
class
i
f
ied
b
y
th
e
Fu
zz
y
lo
g
ic.
T
w
o
s
c
h
e
m
es
w
er
e
u
tili
ze
d
to
co
llect
d
ata
b
ased
o
n
v
ib
r
atio
n
d
ata
m
o
d
e
i
n
1
-
ax
i
s
an
d
3
-
ax
i
s
.
T
h
e
r
esu
lts
o
f
th
e
t
w
o
s
c
h
e
m
es
s
h
o
w
co
llectin
g
d
ata
in
1
-
ax
i
s
is
b
etter
th
an
3
-
a
x
i
s
b
ased
o
n
r
ea
l
ti
m
e
p
r
o
ce
s
s
i
n
g
.
Mo
r
eo
v
er
,
th
e
f
a
u
lt
w
a
s
d
etec
tio
n
an
d
p
r
ed
ictio
n
ac
cu
r
ac
y
o
f
v
ib
r
atio
n
f
au
lt
i
n
3
-
ax
i
s
b
etter
th
a
n
i
n
1
-
a
x
i
s
s
ch
e
m
e.
I
n
ad
d
itio
n
,
t
h
e
r
ea
l
t
i
m
e
p
r
o
ce
s
s
i
n
g
o
f
t
h
is
w
o
r
k
w
a
s
i
m
p
r
o
v
ed
3
0
%
w
it
h
s
a
m
e
ac
cu
r
ac
y
o
f
f
a
u
lt
d
iag
n
o
s
e.
T
h
u
s
,
f
au
lt
ca
n
b
e
d
etec
ted
ev
en
r
ed
u
ce
p
ac
k
et
len
g
th
f
o
r
i
m
p
r
o
v
e
th
e
r
ea
l
ti
m
e
p
r
o
ce
s
s
i
n
g
.
Mo
r
eo
v
er
,
f
au
lt
d
ia
g
n
o
s
e
s
s
u
cc
e
s
s
f
u
l
l
y
b
ased
o
n
u
ti
lized
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
a
n
d
f
u
zz
y
lo
g
ic
tec
h
n
iq
u
e.
T
h
e
u
s
ag
e
o
f
t
h
e
w
ir
ele
s
s
tech
n
iq
u
e
e
n
h
a
n
ce
s
th
e
s
y
s
te
m
’
s
r
el
iab
ilit
y
,
f
le
x
ib
ilit
y
,
an
d
co
s
t d
ec
r
ea
s
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Desig
n
a
n
d
imp
leme
n
ta
tio
n
o
f
w
ir
ele
s
s
s
y
s
tem
fo
r
vib
r
a
tio
n
fa
u
lt d
etec
tio
n
u
s
in
g
... (
Mo
n
ee
r
A
li Lilo
)
551
RE
F
E
R
E
NC
E
S
[1
]
L
.
Ho
u
a
n
d
N.
W
.
Be
rg
m
a
n
n
,
“
In
d
u
c
t
io
n
M
o
t
o
r
F
a
u
lt
Dia
g
n
o
sis
Us
in
g
In
d
u
strial
W
irele
ss
S
e
n
so
r
Ne
t
w
o
rk
s
a
n
d
De
m
p
ste
r
-
S
h
a
f
e
r
Cl
a
ss
i
f
ier
F
u
sio
n
,
”
in
2
0
1
1
IEE
E
In
d
u
stri
a
l
El
e
c
tro
n
ics
S
o
c
iety
,
Co
n
f
.
o
f
IECON
2
0
1
1
,
p
p
.
2
9
9
2
-
2
9
9
7
.
[2
]
Y.
Yu
,
W
.
L
i,
D.
S
h
e
n
g
,
a
n
d
J
.
Ch
e
n
,
“
A
n
o
v
e
l
se
n
so
r
f
a
u
lt
d
iag
n
o
sis
m
e
th
o
d
b
a
se
d
o
n
M
o
d
i
f
ied
En
se
m
b
le
Em
p
iri
c
a
l
M
o
d
e
De
c
o
m
p
o
siti
o
n
a
n
d
P
ro
b
a
b
il
isti
c
Ne
u
ra
l
Ne
tw
o
rk
,
”
M
e
a
su
re
me
n
t
,
v
o
l.
6
8
,
p
p
.
3
2
8
-
3
3
6
,
2
0
1
5
.
[3
]
M
.
A
.
L
il
o
,
L
.
A
.
L
a
ti
ff
,
A
.
Bin
Ha
ji
A
b
u
,
Y.
I.
A
l
M
a
sh
h
a
d
a
n
y
,
a
n
d
A
.
K.
Ili
jan
,
“
G
a
s
T
u
rb
in
e
Be
a
rin
g
a
n
d
V
ib
ra
ti
o
n
Clas
sif
ica
ti
o
n
o
f
Us
in
g
M
u
lt
i
-
lay
e
r
Ne
u
ra
l
Ne
t
w
o
rk
,
”
IEE
E
Co
n
f.
IC
S
S
A
2
0
1
5
,
p
p
.
3
-
6
,
2
0
1
5
.
[4
]
X
.
Z
h
a
n
g
,
Y.
L
ian
g
,
J.
Zh
o
u
,
a
n
d
Y.
Zan
g
,
“
A
n
o
v
e
l
b
e
a
rin
g
f
a
u
lt
d
iag
n
o
sis
m
o
d
e
l
in
teg
ra
ted
p
e
rm
u
tatio
n
e
n
tr
o
p
y
,
e
n
se
m
b
le e
m
p
iri
c
a
l
m
o
d
e
d
e
c
o
m
p
o
siti
o
n
a
n
d
o
p
ti
m
ize
d
S
V
M
,
”
M
e
a
su
re
me
n
t
,
v
o
l.
6
9
,
p
p
.
1
6
4
-
1
7
9
,
2
0
1
5
.
[5
]
M
.
A
.
L
.
I.
L
il
o
,
L
.
A
.
L
a
ti
ff
,
A
.
Bin
,
a
n
d
H.
A
b
u
,
“
I
d
e
n
ti
f
y
a
n
d
Clas
sify
V
ib
ra
ti
o
n
F
a
u
lt
Ba
se
d
o
n
A
rti
f
icia
l
In
telli
g
e
n
c
e
T
e
c
h
n
iq
u
e
s,”
v
o
l.
9
4
,
n
o
.
2
,
p
p
.
4
6
4
-
4
7
4
,
2
0
1
6
.
[6
]
H.
A
.
Ka
d
h
im
,
N.
S
.
A
li
,
a
n
d
D
.
M
.
A
b
d
u
lsa
h
i
b
,
“
M
a
n
a
g
e
m
e
n
t
a
n
d
a
rc
h
iv
in
g
sy
ste
m
f
o
r
m
e
tal
d
e
tec
ti
o
n
r
o
b
o
t
u
sin
g
w
irele
ss
-
b
a
s
e
d
tec
h
n
o
l
o
g
y
a
n
d
o
n
li
n
e
d
a
tab
a
se
re
g
istr
y
,
”
In
t.
J
.
Po
we
r
El
e
c
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
1
0
,
n
o
.
1
,
p
.
2
1
9
,
2
0
1
9
.
[7
]
A
.
A
li
,
M
.
N.
Ya
s
in
,
M
.
F
.
C.
Hu
sin
,
a
n
d
N.
A
.
A
.
Ha
m
b
a
li
,
“
De
si
g
n
a
n
d
a
n
a
ly
sis
o
f
2
-
c
o
il
w
irele
ss
p
o
w
e
r
tran
sf
e
r
(W
P
T
)
u
sin
g
m
a
g
n
e
ti
c
c
o
u
p
li
n
g
t
e
c
h
n
iq
u
e
,
”
In
t.
J
.
P
o
we
r E
lec
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
1
0
,
n
o
.
2
,
p
.
6
1
1
,
2
0
1
9
.
[8
]
M
.
T
jen
sv
o
ld
,
“
Co
m
p
a
riso
n
o
f
th
e
IEE
E
8
0
2
.
1
1
,
8
0
2
.
1
5
.
1
,
8
0
2
.
1
5
.
4
a
n
d
8
0
2
.
1
5
.
6
w
irele
ss
sta
n
d
a
rd
s.
S
e
p
2
0
0
7
,
”
Co
m/2
0
0
8
/0
7
/Co
m
p
a
riso
n
-
Ie
e
e
-
8
0
2
-
S
ta
n
d
a
rd
s.
PDF
,
n
o
.
1
,
p
p
.
1
-
7
,
2
0
0
7
.
[9
]
M
.
Nix
o
n
,
“
A
Co
m
p
a
riso
n
o
f
W
ir
e
les
sH
A
R
T
TM
a
n
d
IS
A
1
0
0
.
1
1
a
,
”
wh
it
e
Pa
p
.
J
u
ly
,
p
p
.
1
-
3
6
,
2
0
1
2
.
[1
0
]
M
.
A
.
L
il
o
,
L
.
A
.
Latiff
,
A
.
Bin
,
H.
A
b
u
,
Y.
I.
A
l
M
a
sh
h
a
d
a
n
y
,
a
n
d
S
.
M
.
A
.
A
l
-
,
“
De
sig
n
o
f
In
d
u
strial
W
irele
ss
S
e
n
so
r
S
y
ste
m
f
o
r
Re
a
l
-
T
i
m
e
Da
ta
Co
ll
e
c
ti
o
n
i
n
S
tea
m
T
u
rb
in
e
s,”
in
S
COPUS
-
2
0
1
5
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Co
mp
u
ter
S
y
ste
ms
a
n
d
In
str
u
me
n
ta
ti
o
n
,
2
0
1
5
.
[1
1
]
G
.
Zh
a
n
g
,
C.
a
.
Du
n
c
a
n
,
J.
Ka
n
n
o
,
a
n
d
R.
R.
S
e
lm
ic,
“
Un
m
a
n
n
e
d
G
ro
u
n
d
V
e
h
icle
Na
v
ig
a
ti
o
n
i
n
C
o
o
r
d
in
a
te
-
F
re
e
a
n
d
L
o
c
a
li
z
a
ti
o
n
-
F
re
e
W
irele
ss
S
e
n
so
r
a
n
d
A
c
tu
a
to
r
Ne
tw
o
rk
s,”
J
.
In
tell.
R
o
b
o
t.
S
y
st.
,
v
o
l.
7
4
,
n
o
.
3
-
4
,
p
p
.
8
6
9
-
8
9
1
,
2
0
1
4
.
[1
2
]
L
.
Ho
u
a
n
d
N.
W
.
Be
r
g
m
a
n
n
,
“
No
v
e
l
in
d
u
strial
w
irele
ss
se
n
so
r
n
e
tw
o
rk
s
f
o
r
m
a
c
h
in
e
c
o
n
d
it
i
o
n
m
o
n
it
o
rin
g
a
n
d
f
a
u
lt
d
iag
n
o
sis,”
IEE
E
T
ra
n
s.
In
st
ru
m.
M
e
a
s.
,
v
o
l.
6
1
,
n
o
.
1
0
,
p
p
.
2
7
8
7
-
2
7
9
8
,
2
0
1
2
.
[1
3
]
I.
Ja
w
h
a
r,
N.
M
o
h
a
m
e
d
,
J.
A
l
-
Ja
r
o
o
d
i,
a
n
d
S
.
Z
h
a
n
g
,
“
A
F
ra
m
e
w
o
rk
f
o
r
Us
in
g
Un
m
a
n
n
e
d
Ae
rial
V
e
h
icle
s
f
o
r
Da
ta
Co
ll
e
c
ti
o
n
in
L
in
e
a
r
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s,”
J
.
In
tell.
Ro
b
o
t
.
S
y
st.
,
v
o
l.
7
4
,
n
o
.
1
-
2
,
p
p
.
4
3
7
-
4
5
3
,
2
0
1
4
.
[1
4
]
V
.
C.
G
u
n
g
o
r,
G
.
P
.
Ha
n
c
k
e
,
a
n
d
S
.
M
e
m
b
e
r,
“
In
d
u
strial
W
irele
ss
S
e
n
so
r
Ne
tw
o
rk
s :
Ch
a
ll
e
n
g
e
s
,
De
sig
n
P
ri
n
c
ip
les
,
a
n
d
T
e
c
h
n
ica
l
A
p
p
ro
a
c
h
e
s,”
4
2
5
8
IE
EE
T
r
a
n
s.
I
n
d
.
El
e
c
tro
n
.
,
v
o
l.
5
6
,
n
o
.
1
0
,
p
p
.
4
2
5
8
-
4
2
6
5
,
2
0
0
9
.
[1
5
]
M
.
L
il
o
,
L
.
A
.
L
a
ti
ff
,
A
.
A
b
u
,
a
n
d
Y.
A
l
M
a
sh
h
a
d
a
n
y
,
“
W
irele
ss
F
a
u
lt
T
o
l
e
ra
n
c
e
s
D
e
c
isio
n
Us
in
g
A
rti
f
icia
l
In
telli
g
e
n
c
e
T
e
c
h
n
iq
u
e
,
”
J
.
T
h
e
o
r
.
Ap
p
l.
I
n
f.
T
e
c
h
n
o
l.
,
v
o
l.
8
7
,
n
o
.
2
,
p
p
.
3
2
4
-
3
3
5
,
2
0
1
6
.
[1
6
]
X
.
L
e
i,
P
.
L
u
,
a
n
d
F
.
L
iu
,
“
T
h
e
h
ig
h
p
e
rf
o
r
m
a
n
c
e
c
o
n
tro
l
f
o
r
s
m
a
ll
ro
tar
y
-
w
in
g
u
n
m
a
n
n
e
d
a
ircra
f
t
b
a
se
d
o
n
c
o
m
p
o
site c
o
n
tro
l
m
e
th
o
d
,
”
T
r
a
n
s.
In
st.
M
e
a
s.
C
o
n
tr
o
l
,
v
o
l.
3
6
,
n
o
.
8
,
p
p
.
1
0
3
3
-
1
0
4
0
,
2
0
1
4
.
[1
7
]
S
.
Yu
su
f
,
S
.
S
h
e
tt
y
,
N.
W
il
k
in
so
n
,
a
n
d
D.
J.
Bro
w
n
,
“
A
n
o
v
e
l
se
l
f
-
c
o
n
f
ig
u
rin
g
e
th
e
rn
e
t
-
b
a
se
d
sm
a
rt
s
e
n
so
r
a
p
p
li
c
a
ti
o
n
f
o
r
re
m
o
te co
n
d
it
i
o
n
m
o
n
it
o
rin
g
,
”
M
o
b
.
Emb
e
d
.
,
2
0
1
3
.
[1
8
]
S.
K.
Jh
a
,
K.
Ha
y
a
sh
i,
a
n
d
R.
D.
S
.
Ya
d
a
v
a
,
“
Ne
u
ra
l,
f
u
z
z
y
a
n
d
n
e
u
ro
-
f
u
z
z
y
a
p
p
ro
a
c
h
f
o
r
c
o
n
c
e
n
tratio
n
e
stim
a
ti
o
n
o
f
v
o
latil
e
o
rg
a
n
ic co
m
p
o
u
n
d
s b
y
su
rf
a
c
e
a
c
o
u
stic w
a
v
e
se
n
so
r
a
rra
y
,
”
M
e
a
su
re
me
n
t
,
v
o
l.
5
5
,
p
p
.
1
8
6
-
1
9
5
,
2
0
1
4
.
[1
9
]
A
.
S
.
W
e
d
d
e
ll
,
G
.
V
.
M
e
rre
tt
,
S
.
Ba
rro
w
,
a
n
d
B
.
M
.
A
l
-
Ha
sh
im
i,
“
V
i
b
ra
ti
o
n
-
p
o
w
e
re
d
se
n
sin
g
sy
s
tem
f
o
r
e
n
g
in
e
c
o
n
d
i
ti
o
n
m
o
n
it
o
r
in
g
,
”
in
IET
c
o
n
fer
e
n
c
e
Pu
b
li
c
a
t
io
n
s
,
2
0
1
2
.
[2
0
]
R.
K.
Ba
ra
i
a
n
d
K.
No
n
a
m
i,
“
L
o
c
o
m
o
ti
o
n
C
o
n
tr
o
l
o
f
a
Hy
d
ra
u
li
c
a
l
ly
A
c
tu
a
ted
He
x
a
p
o
d
R
o
b
o
t
b
y
Ro
b
u
st
A
d
a
p
ti
v
e
F
u
z
z
y
Co
n
tro
l
w
it
h
S
e
lf
-
T
u
n
e
d
A
d
a
p
tatio
n
G
a
in
a
n
d
De
a
d
Zo
n
e
F
u
z
z
y
P
re
-
c
o
m
p
e
n
sa
ti
o
n
,
”
J
.
In
te
ll
.
Ro
b
o
t.
S
y
st.
,
v
o
l.
5
3
,
n
o
.
1
,
p
p
.
3
5
-
5
6
,
2
0
0
8
.
[2
1
]
A
.
M
o
u
sm
i,
A
.
A
b
b
o
u
,
a
n
d
Y.
El
Ho
u
m
,
“
Re
a
l
-
ti
m
e
im
p
le
m
e
n
tatio
n
o
f
a
n
o
v
e
l
h
y
b
rid
f
u
z
z
y
slid
in
g
m
o
d
e
c
o
n
tro
l
o
f
a
BL
DC
m
o
to
r,
”
In
t.
J
.
Po
we
r
El
e
c
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
1
0
,
n
o
.
3
,
p
.
1
1
6
7
,
2
0
1
9
.
[2
2
]
N.
F
a
ra
h
,
M
.
H.
N.
T
a
li
b
,
Z.
I
b
ra
h
im
,
J.
M
.
L
a
z
i,
a
n
d
M
.
A
z
ri,
“
S
e
lf
-
tu
n
in
g
F
u
z
z
y
L
o
g
ic
Co
n
tro
ll
e
r
Ba
se
d
o
n
T
a
k
a
g
i
-
S
u
g
e
n
o
A
p
p
li
e
d
to
I
n
d
u
c
ti
o
n
M
o
t
o
r
Driv
e
s,”
In
t.
J
.
Po
w
e
r
El
e
c
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
9
,
n
o
.
4
,
p
.
1
9
6
7
,
2
0
1
8
.
[2
3
]
W
.
I.
Ha
m
e
e
d
,
B.
A
.
S
a
w
a
d
i,
a
n
d
A
.
M
u
a
y
e
d
,
“
V
o
lt
a
g
e
T
ra
c
k
in
g
Co
n
tr
o
l
o
f
DC
-
DC
Bo
o
st
C
o
n
v
e
rter
Us
in
g
F
u
z
z
y
Ne
u
ra
l
Ne
tw
o
rk
,
”
In
t.
J
.
Po
we
r E
lec
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
9
,
n
o
.
4
,
p
.
1
6
5
7
,
2
0
1
8
.
[2
4
]
S
.
R.
Re
d
d
y
,
P
.
V
.
P
ra
sa
d
,
a
n
d
G
.
N.
S
rin
iv
a
s,
“
De
sig
n
o
f
P
I
a
n
d
F
u
z
z
y
L
o
g
ic
Co
n
tro
ll
e
rs
f
o
r
Di
strib
u
ti
o
n
S
tatic
Co
m
p
e
n
sa
to
r,
”
In
t.
J
.
Po
we
r E
lec
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
9
,
n
o
.
2
,
p
.
4
6
5
,
2
0
1
8
.
[2
5
]
A
.
J.
A
li
,
Z.
F
a
re
j,
a
n
d
N.
S
u
lt
a
n
,
“
P
e
rf
o
rm
a
n
c
e
e
v
a
lu
a
ti
o
n
o
f
a
h
y
b
rid
f
u
z
z
y
lo
g
ic
c
o
n
tro
ll
e
r
b
a
se
d
o
n
g
e
n
e
ti
c
a
lg
o
rit
h
m
f
o
r
th
re
e
p
h
a
se
in
d
u
c
ti
o
n
m
o
to
r
d
r
iv
e
,
”
In
t.
J
.
P
o
we
r E
lec
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
1
0
,
n
o
.
1
,
p
.
1
1
7
,
2
0
1
9
.
[2
6
]
E.
T
.
Esfa
h
a
n
i,
S
.
W
a
n
g
,
a
n
d
V.
S
u
n
d
a
ra
ra
jan
,
“
M
u
lt
ise
n
so
r
w
irele
ss
s
y
ste
m
f
o
r
e
c
c
e
n
tri
c
it
y
a
n
d
b
e
a
rin
g
f
a
u
lt
d
e
tec
ti
o
n
in
i
n
d
u
c
ti
o
n
m
o
to
rs,”
IE
EE
/A
S
M
E
T
r
a
n
s.
M
e
c
h
a
tro
n
ics
,
v
o
l.
1
9
,
n
o
.
3
,
p
p
.
8
1
8
-
8
2
6
,
2
0
1
4
.
[2
7
]
C.
P
a
p
a
c
h
risto
s,
K.
A
lex
is,
a
n
d
A
.
T
z
e
s,
“
Du
a
l
-
A
u
th
o
rit
y
T
h
ru
st
-
V
e
c
to
ri
n
g
o
f
a
T
ri
-
T
il
tRo
to
r
e
m
p
lo
y
in
g
M
o
d
e
l
P
re
d
ictiv
e
Co
n
tr
o
l,
”
J
.
I
n
tell.
Ro
b
o
t.
S
y
st.
,
2
0
1
5
.
[2
8
]
M
.
Ya
ich
i,
M
.
K.
F
e
ll
a
h
,
a
n
d
A
.
M
a
m
m
e
ri,
“
A
n
e
u
ra
l
n
e
t
w
o
rk
b
a
se
d
M
P
P
T
tec
h
n
i
q
u
e
c
o
n
tro
l
ler
fo
r
p
h
o
to
v
o
lt
a
ic
p
u
m
p
in
g
sy
ste
m
,
”
In
t.
J
.
Po
we
r E
lec
tro
n
.
Dr
ive
S
y
st.
,
v
o
l.
4
,
n
o
.
2
,
p
p
.
2
4
1
-
2
5
5
,
2
0
1
4
.
[2
9
]
A
.
Be
n
k
a
d
a
,
H.
Ch
a
ik
h
y
,
a
n
d
M
.
M
o
n
k
a
d
e
,
“
M
P
P
T
C
o
n
tr
o
l
f
o
r
W
in
d
En
e
rg
y
Co
n
v
e
rsio
n
S
y
ste
m
Ba
se
d
o
n
a
T
-
S
F
u
z
z
y
,
”
In
t.
J
.
Po
we
r E
lec
tro
n
.
D
riv
e
S
y
st.
,
v
o
l.
9
,
n
o
.
2
,
p
.
8
1
1
,
2
0
1
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
9
,
No
.
3
,
Sep
t
e
m
b
er
20
20
:
5
4
5
–
5
52
552
[3
0
]
X
.
L
iu
,
H.
Hu
a
n
g
,
a
n
d
J.
X
ian
g
,
“
A
P
e
rso
n
a
li
z
e
d
Dia
g
n
o
sis
M
e
th
o
d
to
De
te
c
t
F
a
u
lt
s
in
a
B
e
a
rin
g
Ba
se
d
o
n
A
c
c
e
lera
ti
o
n
S
e
n
so
rs
a
n
d
a
n
F
E
M
S
im
u
latio
n
Driv
in
g
S
u
p
p
o
rt
V
e
c
to
r
M
a
c
h
i
n
e
,
”
S
e
n
so
rs
,
v
o
l.
2
0
,
n
o
.
2
,
p
.
4
2
0
,
2
0
2
0
.
[3
1
]
O.
Av
c
i,
O.
A
b
d
e
lj
a
b
e
r,
S
.
Kira
n
y
a
z
,
a
n
d
D.
In
m
a
n
,
“
Co
n
v
o
lu
ti
o
n
a
l
Ne
u
ra
l
Ne
t
w
o
rk
s
f
o
r
Re
a
l
-
ti
m
e
a
n
d
W
irele
s
s
Da
m
a
g
e
De
te
c
ti
o
n
,
”
Dy
n
.
Civ.
S
tru
c
t.
,
v
o
l
.
2
,
p
p
.
1
2
9
-
1
3
6
,
2
0
2
0
.
[3
2
]
A
.
D.
S
p
a
c
e
k
,
O.
H.
A
.
Ju
n
io
r,
J.
M
.
Ne
to
,
V
.
L
.
Co
e
lh
o
,
M
.
O.
Oliv
e
ira,
V
.
G
ru
b
e
r,
a
n
d
L
.
S
c
h
a
e
ffe
r,
“
M
a
n
a
g
e
m
e
n
t
o
f
M
e
c
h
a
n
ica
l
V
ib
ra
ti
o
n
a
n
d
T
e
m
p
e
ra
tu
re
in
S
m
a
ll
W
in
d
T
u
rb
in
e
s
Us
in
g
Z
ig
b
e
e
W
irele
ss
Ne
tw
o
rk
,
”
IL
AT
IN
Am.
T
ra
n
s.
IE
EE
,
v
o
l.
1
1
,
n
o
.
1
,
p
p
.
5
1
2
-
5
1
7
,
2
0
1
3
.
[3
3
]
A
.
S
a
b
a
to
a
n
d
M
.
F
e
n
g
,
“
F
e
a
sib
il
it
y
o
f
F
re
q
u
e
n
c
y
-
M
o
d
u
late
d
W
irele
ss
T
ra
n
s
m
issio
n
f
o
r
a
M
u
lt
i
-
P
u
rp
o
se
M
EM
S
-
Ba
se
d
Ac
c
e
lero
m
e
ter,”
S
e
n
so
rs
,
v
o
l.
1
4
,
p
p
.
1
6
5
6
3
-
1
6
5
8
5
,
2
0
1
4
.
[3
4
]
C.
P
a
rk
,
R.
Ba
e
k
,
W
.
Ho
e
,
B.
Ki
m
,
a
n
d
H.
L
e
e
,
“
E
ff
icie
n
t
W
ir
e
le
ss
V
ib
ra
ti
o
n
Da
ta
S
e
n
sin
g
a
n
d
S
i
g
n
a
l
P
ro
c
e
ss
in
g
T
e
c
h
n
iq
u
e
Ba
se
d
o
n
t
h
e
A
n
d
ro
i
d
P
latf
o
rm
,
”
In
t.
J
.
Distri
b
.
S
e
n
s.
N
e
two
rk
s
,
2
0
1
4
.
[3
5
]
P
.
L
i,
L
.
L
i,
G
.
S
o
n
g
,
a
n
d
Y.
Yu
,
“
W
irele
ss
S
e
n
sin
g
a
n
d
V
i
b
ra
ti
o
n
C
o
n
tro
l
W
it
h
In
c
re
a
se
d
Re
d
u
n
d
a
n
c
y
a
n
d
Ro
b
u
st
n
e
ss
De
sig
n
,
”
iee
e
,
T
ra
n
s.
Cy
b
e
rn
.
,
v
o
l.
4
4
,
n
o
.
1
1
,
p
p
.
2
0
7
6
-
2
0
8
7
,
2
0
1
4
.
[3
6
]
J.
Ne
u
z
il
,
O
.
Kre
ib
ich
,
a
n
d
R.
S
m
id
,
“
A
Distrib
u
ted
F
a
u
lt
De
tec
ti
o
n
S
y
ste
m
Ba
se
d
o
n
IW
S
N
f
o
r
M
a
c
h
in
e
Co
n
d
it
io
n
M
o
n
it
o
ri
n
g
,
”
IEE
T
ra
n
s.
In
d
.
In
fo
rm
a
ti
c
s
,
v
o
l.
1
0
,
n
o
.
2
,
p
p
.
1
1
1
8
-
1
1
2
3
,
2
0
1
4
.
[3
7
]
M
.
A
.
L
il
o
,
L
.
A
.
L
a
ti
ff
,
A
.
Bin
,
H.
A
b
u
,
a
n
d
Y.
I
.
A
l
M
a
sh
h
a
d
a
n
y
,
“
V
ib
ra
ti
o
n
F
a
u
lt
De
tec
ti
o
n
a
n
d
C
las
sif
a
c
ti
o
n
Ba
se
d
o
n
t
h
e
F
F
T
A
n
d
F
u
z
z
y
L
o
g
ic,”
AR
PN
J
.
En
g
.
A
p
p
l.
S
c
i.
,
v
o
l
.
1
1
,
n
o
.
7
,
p
p
.
4
6
3
3
-
4
6
3
7
,
2
0
1
6
.
[3
8
]
H.
Lee
,
S
.
M
e
m
b
e
r,
Y.
Ch
a
n
g
,
a
n
d
Y.
Hu
a
n
g
,
“
A
R
e
li
a
b
le
W
irele
ss
S
e
n
so
r
S
y
ste
m
f
o
r
M
o
n
it
o
r
in
g
M
e
c
h
a
n
ica
l
W
e
a
r
-
Ou
t
o
f
P
a
rts,
”
T
ra
n
s
.
In
str
u
m.
M
e
a
s.
,
v
o
l.
6
3
,
n
o
.
1
0
,
p
p
.
1
-
1
0
,
2
0
1
4
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
A
s
s.
P
ro
f
.
Dr.
M
o
n
e
e
r
A
li
L
il
o
w
a
s
b
o
rn
in
Ira
q
,
in
1
9
7
2
,
re
c
e
iv
e
d
B.
S
C.
o
f
El
e
c
tro
n
ic
En
g
in
e
e
rin
g
in
1
9
9
5
,
Un
iv
e
rsit
y
o
f
Tec
h
n
o
lo
g
y
-
Ba
g
h
d
a
d
-
Ira
q
.
T
h
e
M
a
ste
r
d
e
g
re
e
in
El
e
c
tro
n
ic
En
g
in
e
e
rin
g
f
ro
m
Un
iv
e
rsit
y
o
f
T
e
c
h
n
o
l
o
g
y
-
Ba
g
h
d
a
d
-
Ira
q
(2
0
0
4
).
P
h
.
D.
i
n
2
0
17
f
ro
m
th
e
Ra
z
a
k
S
c
h
o
o
l
o
f
En
g
in
e
e
rin
g
a
n
d
A
d
v
a
n
c
e
d
T
e
c
h
n
o
l
o
g
y
,
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
lay
sia
in
Ku
a
la
lu
m
p
u
r
-
M
a
la
y
sia
.
He
is
c
u
rre
n
tl
y
a
lec
tu
re
r
a
t
th
e
En
g
i
n
e
e
rin
g
c
o
ll
e
g
e
,
A
l
M
u
th
a
n
n
a
Un
iv
e
rsit
y
,
Ira
q
.
His
re
s
e
a
rc
h
e
s
in
tere
sts
d
e
sig
n
a
n
d
im
p
le
m
e
n
t
w
irele
ss
s
y
ste
m
f
o
r
f
a
u
lt
d
e
tec
ti
o
n
.
Dr.
M
a
a
th
Ja
se
m
M
a
h
a
m
m
a
d
o
b
tai
n
e
d
B.
S
C
.
o
f
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
in
1
9
9
3
f
ro
m
Al
-
M
u
sta
n
su
ria
Un
iv
e
rsity
,
Ba
g
h
d
a
d
-
Ira
q
,
M
.
S
C.
El
e
c
tro
-
tec
h
n
i
c
a
l
c
o
m
p
lex
a
n
d
s
y
ste
m
s
o
f
m
in
in
g
-
e
n
terp
rise
s
in
2
0
0
2
f
ro
m
Irk
u
tsk
S
tate
T
e
c
h
n
o
l
o
g
y
Un
iv
e
rsit
y
,
Ru
ss
ia,
P
h
.
D
i
n
2
0
0
9
S
y
st
e
m
A
n
a
l
y
sis,
Co
n
tro
l
a
n
d
I
n
f
o
rm
a
ti
o
n
P
ro
c
e
ss
in
g
(In
f
o
rm
a
t
io
n
a
n
d
T
e
c
h
n
ica
l
S
y
ste
m
s)
Ku
b
a
n
S
tate
Un
i
v
e
rsity
o
f
Tec
h
n
o
lo
g
y
,
Kra
sn
o
d
a
r
-
Ru
ss
ia.
He
is
c
u
rre
n
tl
y
a
lec
tu
re
r
a
t
th
e
De
p
a
rtme
n
t
o
f
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
,
Un
iv
e
rsity
o
f
A
n
b
a
r,
Ira
q
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
c
o
n
tro
l
a
n
d
a
u
t
o
m
a
ti
o
n
sy
ste
m
s.
Evaluation Warning : The document was created with Spire.PDF for Python.