Development Of Welding Defects Identifier Application On Radiographic Film Using Fuzzy C-Means (FCM)

8/9/2019 Development Of Welding Defects Identifier Application On Radiographic Film Using Fuzzy C-Means (FCM)

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INTERNATIONAL CONFERENCE ON EDUCATION ,

TECHNOLOGY, AND SCIENCESJl. Raden Mattaher No. 16 Jambi, Indonesia. Kampus UNJA Pasar, UNIVERI!" #$ JAM%I

&ebsite'ww w .icet s.u nja .a c .id Email '

1

Development Of Welding Defet! Identifie" Appli#tion

On R#diog"#p$i Film U!ing F%&&' C()e#n! *FC)+

#en#l A-idin

e+olah !ini !e+noloi Nu+lir-%A!AN, Jl. %abarsari "oa+arta, /aenala6)mail.(om

A$m#d F#"i! S.

e+olah !ini !e+noloi Nu+lir-%A!AN, a(hmad-0aris)mail.(om

)%$t#d#n

e+olah !ini !e+noloi Nu+lir-%A!AN, muhtadan)mail.(om

A-!t"#t /A !oft0#"e development fo" t$e

identifi#tion of 0eld defet !$#pe indi#to"

"#diog"#p$! $#! -een on!t"%ted. T$e

-#1g"o%nd of t$i! "e!e#"$ i! t$e "e#ding oft$e onvention#l "#diog"#p$i film t$#t t#1e! #

long time #nd !%-2etivit' t$#t #n t"igge"

di!!ent fello0 inte"p"ete". T$e p%"po!e of t$i!

"e!e#"$ i! to p"od%e Appli#tion! t$#t #n

identif' t$e fo"m of 0eld defet! in digit#l

im#ge p"oe!!ing "#diog"#p$i film -'

#ppl'ing im#ge en$#nement, !egment#tion

F%&&' C 3 )e#n! *FC)+, im#ge mo"p$olog',

#nd fe#t%"e e4t"#tion met$od! l#-eling. Im#ge

en$#nement p"oe!! #im! to "e#te # -ette"

im#ge 5%#lit', inl%ding ont"#!t !t"et$ing

te$ni5%e!, noi!e "ed%tion -' # medi#n filte",

#nd im#ge !$#"pening 0it$ l#pl#i#n filte". In #!ep#"#te defet of o-2et 0it$ # -#1g"o%nd

im#ge %!ing # l%!te"ing !egment#tion met$od

F%&&' C ( )e#n!. Fe#t%"e e4t"#tion met$od

%!ed in t$i! "e!e#"$ L#-eling -' "egionp"op!

omm#nd in )ATLA6 tool-o4. Re!%lt! of t$e

"e!e#"$ i! #n #ppli#tion t$#t $#! -een te!ted

#nd #-le to inte"p"et defet! fo"m 0it$ 78.9:;

!%e!! "#te of e'0o"d / "#diog"#p$i film, im#ge en$#nement,!egment#tion, F%&&' C()e#n!.

8. INTRODUCTIONRadioraphi( !estin R!2 is one o0 the most important

nondestru(ti3e testin te(hni4ues 0or &eldin inspe(tion. It

is based on the abilit o0 0oton 5-ra or ra2 to pass

throuh metal and other materials opa4ue to ordinar liht,

and produ(e photoraphi( re(ords b the transmitted

radiant ener 17-87. %e(ause di00erent materials absorb

either 0oton to di00erent e5tents, penetrated ras sho&

3ariations in intensit on the re(ei3in 0ilms. R! (an

e5amine the internal stru(ture o0 a &eld. !raditionall,

e5perien(ed interpreters e3aluate the &eld 4ualit based on

radioraph. It is a time and manpo&er (onsumin &or+.

In addition, human interpretation o0 &eld 4ualit based on

0ilm radioraph is 3er sub*e(ti3e, in(onsistent andsometimes biased. !here0ore, it is desirable to de3elop a

(omputer-aided sstem to assist interpretation o0 radioraphi(

imaes to in(rease the ob*e(ti3it, a((ura( and e00i(ien( o0

radioraphi( inspe(tion 17,87-97.

:urrentl there are reat deals o0 &or+ and resear(h on thede3elopment o0 automated sstems 0or inspe(tion and analsis

o0 radioraphs. In our 3ie&, the ma*or steps o0 an automati(

dete(tion sstem are the 0ilm diiti/ation stae, pre-pro(essin

o0 imaes, and identi0i(ation o0 de0e(ts. !hese de3elopments rel

mostl on te(hni4ues su(h as imae pro(essin, 0eature

e5tra(tion, and pattern re(onition. !he pattern (lassi0i(ation

stae is one o0 the most important steps in the implementation o0

an automated radioraphi( inspe(tion sstem 6,;7. Means $:M2, imae

morpholo, and 0eature e5tra(tion methods labelin.

?. )ETHOD

?.8.I)@ROED DIGITAL I)AGEImae enhan(ement aims to impro3e the 4ualit o0 the displa

imae to 3ie& humans or to (on3ert an imae in order to ha3e

a better 0ormat so that the imae be(omes more easil

pro(essed b (omputers67. #peration that repairs imae in this

stud in(ludes three pro(esses, namel' (ontrast stret(hin,

noise redu(tion b a median 0ilter, and imae enhan(ement

usin the =apla(ian 0ilter.

?.?. I)AGECLUSTERING:lusterin is an unsuper3ised (lassi0i(ation not trained2 to a

pattern data, 0eature 3e(tors2 into roups or (lusters based

bebearap resemblan(e. Intuiti3el, a di00erent pattern is true

&ithin a (luster &ill be more similar to ea(h other &hen

(ompared &ith the pattern that is on a di00erent (luster. It (an be

de0ined as the pro(ess o0 de0inin a mappin or mappin 0' the 3alue (an be sear(hed b the 0ollo&in

0ormula.

Roundness?

Indi(ations o0 irreular shape ?

lenth&ise ?

round ? eccentricity G.;

B. Means !his is an appli(ation-based

raphi(al User Inter0a(e UI2. !he use o0 UI

intended that the resultin appli(ations are to be user0riendl and eas to use, be(ause the appli(ation is

e5pe(ted to be the de(ision support 0or an interpreter in

interpretin radioraphi( &eld de0e(t shape on a

radioraph.

. RESULTS AND DISCUSSIONS

.8. DIGITALI)AGEDATAIN@UT

RADIOGRA@H!he data input is the appli(ation o0 diital radioraphi(

imae o0 %A!AN standard IIC2. Radioraph (an be &ith

the de0e(t and non-de0e(t, there are eometri( shapes

de0e(t indi(ations, namel a2 bran(hed strin, b2

lonitudinal, (2 spheri(al, and d2 irreular as in $i. 1.

.?. CUTTINGI)AGE!o a3oid imae pro(essin on the identi0i(ation pro(ess,

that is not use0ul and to redu(e the (omputin time, the

imae needs to be (ut into smaller si/es. !he (ommand to

do a diital imae &hi(h (uts (rop ? im(rop 02, &here 0 is

the imae that &ill be (ut, &hile the (rop is the result o0

(uttin. !his appli(ation &ill as+ the operator user to

(hoose the lo(ation o0 the imae that &ill be (ut a((ordin

to the needs.

o& to et a pie(e o0 the imae is b drain the mouse(ursor &ith a OQ to 0orm a bo5 &ith the desired si/e and

then (li(+ed times. !he imae &ill be (ropped automati(all

and &ill be pro(essed in the pre > pro(essin. !his pro(ess is

sho&n in $i. .

a2

(b)

(c)

(d)$i. 1. Imae data

$i. !he pro(ess o0 (uttin the imae

.B. DIGITALI)AGEENHANCE)ENTImae enhan(ement pro(ess is done a0ter the (uttin pro(ess o0

the imae (roppin2, this stud in(ludes stret(hin (ontrast

(ontrast stret(hin2 redu(tion in noise noise2, and sharpenin.

!he pro(ess o0 noise redu(tion per0ormed usin a median 0ilter

&ith a +ernel si/e o0 858.

In (ontrast stret(hin, the user (an sele(t the auto or manual. !o

use the auto option stret(hlim (ommand &hile the user manual,

it (an determine the 3alue o0 the lo& ins, hih in, lo& out and

hih out a((ordin to need. $i. 8 sho&ed the result o0 (ontrast

stret(hin pro(ess 0or settin the (ontrast auto and manual

settins b settin a lo& 3alue in G.1, in the hih G., lo& out o0

G., and hih out o0 G.9 imae o0 (uttin (roppin2.

(7

(8)

(9

(10
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a2auto b2 manual

$i.8.


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$i. D. Results indi(ation spheri(al shape de0e(ts

parameter 3alues o0 the de0e(t is

T e((entri(it ? G.6GT !i ? G.DGFF

T :ompma*min ? G.9F;1o the parameter is a label imae &ith rounded shapede0e(ts.

.. TESTINGI)AGELA6ELING!he test proram &as (ondu(ted b anal/in (omparati3e

indi(ation o0 the shape de0e(t indi(ated on the panel &ith

a 3isual indi(ation b the user. G input imaes are an

indi(ation o0 the 0orm o0 the 6G imaes obtained 0rom the

labelin pro(ess. In this stud indi(ated there are 8

imaes ha3in an elonated shape de0e(t, imaes 0orindi(ations o0 a round shape, and 19 imaes 0or indi(ations

o0 de0e(ts shape are irreular.

Results o0 the testin sho&ed the imae o0 the label - the

0ollo&in' 0or the indi(ation o0 de0e(ts elonated shape has

an error rate o0 D.6F or ha3e a su((ess rate o0 F1.81.

$or an indi(ation o0 the 0orm o0 spheri(al de0e(ts ha3e the

su((ess rateFG.F1 and 0or indi(ations o0 irreular shape

de0e(ts ha3e a su((ess rate o0 F8.88. !his means that

based on the simulation and tests per0ormed sstem has an

a3erae su((ess rate o0 F1.D9. $i. F is an imae o0 the

o3erall results o0 the testin (ondu(ted labels.

$i. F. !he results o0 testin o0 the &eld de0e(t shaperadioraph interpretation

In addition to the 4ualit o0 the input imae, espe(iall the

imae enhan(ement pro(esses, the sele(tion o0 test points

on the imae that is deemed de0e(ti3e radioraph also

a00e(t the le3el o0 su((ess in the interpretation. ele(tion o0

pi5els dots that 0it testin &ith tareted disabilities &ill

in(rease the su((ess rate on the test simulation and the

a(tual pro(ess o0 interpretation.

:. CONCLUSION

!his proram (an produ(e imaes that ha3e better imae 4ualitusin imae enhan(ement in(ludes stret(hin (ontrast, the use o0

the median 0ilter to redu(e noise, to enhan(e the imae intensit

and imae enhan(ement to pro3ide a sharper imae, espe(iall at

the edes o0 the ob*e(t are (onsidered disabled &elds on the

diital radioraph imae.

Appli(ations de3eloped 0rom this resear(h in the 0orm o0

so0t&are-based raphi(al User Inter0a(e UI2 that (an separatethe de0e(ti3e ob*e(t &ith the ba(+round imae sementation

usin (lusterin $u// : - Means and interpret the de0ormed

shape o0 the &eld de0e(t parti(ularl elonated shape, round, and

not irreular that (an be used as an analsis and de(ision support

interpreters interpretin radioraphs in industrial radioraphi(

&eld de0e(t tpes.


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=e(turer sin(e 1FDD, (hairman o0 departmen o0 Nu(lear

phsi(s

!ea(hin e5perien(e'

Nu(lear !e(hnolo, a0et, N
http://www.icets.unja.ac.id/http://www.icets.unja.ac.id/http://www.icets.unja.ac.id/http://www.icets.unja.ac.id/http://www.icets.unja.ac.id/http://www.icets.unja.ac.id/mailto:[email protected]

Development Of Welding Defects Identifier Application On Radiographic Film Using Fuzzy C-Means (FCM)

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