Recei ed Decembe 8, 2020, accep ed Janua y 10, 2021, da e o publica ion Janua y 19, 2021, da e o cu en e sion Janua y 28, 2021.
Digi al Objec Iden i ie 10.1109/ACCESS.2021.3052864
Vessel Recogni ion in Induc ion Hea ing
Appliances—A Deep-Lea ning App oach
JORGE VILLA 1, (Membe , IEEE), DENIS NAVARRO 1, ALBERTO DOMINGUEZ 2,
JOSE I. ARTIGAS 1, AND LUIS A. BARRAGAN 1
1Depa men o Elec onic Enginee ing and Communica ions, I3A, Uni e si y o Za agoza, 50018 Za agoza, Spain
2Bosch and Siemens Home Appliances G oup, Depa men o Induc ion Technology o BSH Elec odomes icos, 50016 Za agoza, Spain
Co esponding au ho : Jo ge Villa (j illal@uniza .es)
This wo k was suppo ed in pa by he Spanish MICINN unde P ojec PID2019-103939RB-I00, in pa by he Spanish MICINN and AEI
unde P ojec RTC-2017-5965-6 and G an PTQ-17-09045, in pa by he EU h ough FEDER P og am, in pa by he DGA-FSE, and in
pa by he BSH Home Appliances G oup.
ABSTRACT The selec ion o a essel by an induc ion-hob use has a signi ican impac on he pe o mance
o he appliance. Due o he induc ion hea ing physical phenomena, he e exis many ac o s ha modi y
he equi alen impedance o induc ion hobs and, consequen ly, he ope a ional condi ions o he in e e .
In pa icula , he ype o essel, which is a sole decision o he use , s ongly a ec s hese pa ame e s.
Besides, he e omagne ic p ope ies o he di e en ma e ials he essels a e made wi h, a y di e en ly
wi h he exci a ion le el, and gi en ha mos o he domes ic induc ion hobs a e based on an ac-bus ol age
a angemen , he exci a ion le el con inuously a ies. The algo i hm p oposed in his wo k akes ad an age
o his ac o iden i y he equi alen impedance o he load and ecognize he po . This is accomplished
h ough a phase-sensi i e de ec o ha was al eady p oposed in he li e a u e and he applica ion o deep
lea ning. Di e en con olu ional neu al ne wo ks a e es ed on an augmen ed expe imen al-based da ase and
he p oposed algo i hm is implemen ed in an expe imen al p o o ype wi h a sys em-on-chip. The p oposed
implemen a ion is p esen ed as an e ec i e and accu a e me hod o cha ac e ize and disc imina e be ween
di e en po s ha could enable u he unc ionali ies in new gene a ions o induc ion hobs.
INDEX TERMS Con olu ional neu al ne wo k, home appliances, induc ion hea ing, neu al ne wo k
applica ions, sys em-on-chip (SoC).
I. INTRODUCTION
Induc ion hea ing is a con ac -less hea ing me hod ha has
been widely used in many applica ions [1]–[3]. The de el-
opmen o semiconduc o de ices o powe elec onics and
he con ac -less na u e o his hea ing echnology makes i
p e e ed o e o he hea ing me hods due o i s highe e i-
ciency. In he domes ic induc ion hea ing (DIH) case, i s
main ad an age compa ed o he esis i e cook ops is ha
while in he las ones he ho es componen is he esis o ,
in he o me , he ho es elemen is he bo om pa o he
po . Logically, his o e s highe e iciencies while a colde
cooking su ace leads o a sa e , easie - o-clean and mo e
du able home appliance [4].
Howe e , gi en he cha ac e is ics o he equi alen load,
he con ol o an induc ion hob is mo e complica ed han he
The associa e edi o coo dina ing he e iew o his manusc ip and
app o ing i o publica ion was Fanbiao Li .
one o a esis i e cook op. The al e na ing magne ic ield ha
hea s he bo om o he po due o induced cu en losses and
magne ic hys e esis [5], [6] is usually gene a ed wi h a hal -
b idge se ies esonan in e e . The equi alen impedance o
he load is modeled as a esis ance, R, connec ed in se ies
wi h an induc ance, L, [7], and he esonan beha io is
achie ed by adding a esonan capaci o , C , in se ies wi h he
load. To eed he in e e , he g id ol age, g id, is ull-wa e
ec i ied and il e ed wi h a bus capaci o , leading o a high-
ippled ol age called bus ol age, B, whose undamen al
equency is wice he one o g id. Gi en he low-cos con ex
o DIH, he swi ching equency, sw, which spans om 30 o
75 kHz, is usually gene a ed h ough insula ed ga e bipola
ansis o s (IGBTs). The lowe limi o sw is imposed by
he maximum equency o human hea ing, which is oughly
es ablished a 20 kHz, while he uppe limi o he swi ching
equency is se o educe he swi ching losses. Addi ionally,
in he inpu o he home appliance a il e is placed o imp o e
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J. Villa e al.: Vessel Recogni ion in Induc ion Hea ing Appliances—A Deep-Lea ning App oach
he elec omagne ic compa ibili y (EMC) wi h he g id. This
il e is mainly designed o comply wi h he s anda ds ha
limi he emissions o adio- equency dis u bances in he
equency ange om 9 kHz o 30 MHz.
One o he d awbacks bu also challenges o DIH is ha
he equi alen load a ies wi h many pa ame e s such as he
swi ching equency, he exci a ion le el, he cha ac e is ics
o he po (ma e ial, size, empe a u e), he misalignmen and
dis ance be ween he induc o and he po , e c. Besides, many
o hese pa ame e s depend exclusi ely on he use .
Such a ia ion o he load o ces he con ol sys em o
change and moni o he ope a ional condi ions o he in e e
o gua an ee he maximum pe o mance and a sa e ope a ion
o he elec onics. Fo his eason, much e o has been
ocused on iden i ying he equi alen load and so is e lec ed
in he li e a u e [8]–[15]. While hese me hods y o cap u e
he equi alen impedance o he load, hey a e no able o
classi y di e en po s and disc imina e be ween hem, i.e., i
a use has en di e en po s, o be able o ecognize which
one o hose en po s is used a a ime. Al hough some yea s
ago his could be seen as an idealis ic unc ionali y, wi h he
inc easing compu a ional capaci y o new sys em-on-chips
(SoCs) and p ocesso s and he de elopmen o he in e ne -
o - hings (many induc ion home appliances a e connec ed o
he in e ne nowadays) hese unc ions a e ge ing close and
close o a eal implemen a ion.
The ecogni ion o he po could imp o e he use expe i-
ence by enabling u he unc ionali ies such as he de ec ion
o commonly used po s, a be e de ec ion o he sui abili y o
a po o induc ion hea ing, he wa ning o a misaligned po ,
he con ol o he use and ageing o a speci ic po , e c. Mo e-
o e , mo e accu a e he mal models could be achie ed [16]
which would ul ima ely lead o a be e es ima ion o he
empe a u e and he cooking p ocess. Besides, he appli-
ance could use in o ma ion om p e ious cookings such as
an app oxima ion o he powe -swi ching equency ans e
unc ion, which po s a e used o which ypes o cooking p o-
cesses and o how long, e c. This in o ma ion could simpli y
he algo i hms ha dis ibu e he powe be ween di e en
induc o s, lead o as e esponses o a change in he powe
a ge and enable ad anced ea u es in new gene a ions o
home appliances, e.g.: imagine placing a co ee po on he
cooking su ace and he appliance au oma ically ecognizing
ha his is you co ee po and ha you a e going o make a
co ee, jus because you ha e done so in p e ious days.
Howe e , o ob ain his in o ma ion, an accu a e iden i i-
ca ion ha could se e as a inge p in o each po would
be ce ainly help ul. In [17], he equi alen impedance o
he load is analyzed om he pe spec i e o he elec omag-
ne ic p ope ies o he ma e ial o he po . Apa om o he
pa ame e s, he equi alen impedance depends on he elec i-
cal conduc i i y and magne ic pe meabili y o he ma e ial.
Besides, he magne ic pe meabili y a ies wi h he exci a ion
le el and, o una ely, di e en ma e ials espond di e en ly
o ha a ia ion o he exci a ion le el. Mo eo e , gi en he
high ipple o he bus ol age, he exci a ion le el applied
o he po a ies con inuously e en i a cons an swi ching
equency is applied.
The me hods p oposed in [8]–[14] whe he calcula e a
single and a e aged alue o he equi alen impedance pe
bus cycle (o o many swi ching cycles) o base hei wo k
on a dc-bus ol age a angemen , meaning ha hey can only
ex ac in o ma ion abou he a e age induc i eness o esis-
i eness o he loads. None heless, no unde lying in o ma ion
abou he ma e ials, ex ac ed om he a ia ion o hei
elec omagne ic p ope ies due o he a ia ion o he exci-
a ion le el, can be ob ained. On he con a y, in [15] his
in o ma ion is p o ided hanks o an algo i hm ha acks he
a ia ion o he equi alen impedance wi h he exci a ion le el
along he en i e bus pe iod. Howe e , al hough he impedance
di e ence be ween po s ha a e made o di e en ma e ials
is shown, no au oma ic ecogni ion o po s is p oposed.
On he o he hand, deep lea ning has also been used o
he iden i ica ion o ce ain pa ame e s in induc ion hobs.
Fo ins ance, in [18] a con olu ional neu al ne wo k based
on he a e age powe , ms cu en and quali y ac o o he
load is p oposed o es ima e he o e lap a ea be ween he po
and he induc o s (a lexible induc ion hob is used, whe e
many small induc o s lead o a lexible cooking a ea). In [19]
he au ho s calcula e he powe ac o and he absolu e alue
o he impedance, |Z|, o he i s ou ha monics o he
swi ching equency and apply a neu al ne wo k o es ima e
he size o he essel placed abo e he induc o . In his case,
he algo i hm is implemen ed in a simple induc ion hob wi h
a single induc o and a single-swi ch in e e .
Likewise, in [20] a me hod o classi y di e en ypes o
po s (o ma e ials) is p oposed. They use he same in o ma-
ion as in [19], bu hey make su e he impedance |Z|and
he powe ac o a e calcula ed a a bus ol age o 100 V.
Then, di e en machine lea ning algo i hms a e es ed and
p oposed. Howe e , al hough he au ho s a e awa e o he
a ia ion o he equi alen impedance wi h he exci a ion le el
( his is why hey make su e he iden i ica ion is applied a
a cons an bus ol age), hey do no ake ad an age o his
phenomenon o ex ac mo e in o ma ion abou he ma e ials.
In his pape , a me hod o iden i y he po ha is placed
abo e he induc o is p oposed. The induc o is used as a
sma senso so ha , compa ed o a adi ional induc ion hob,
no addi ional ha dwa e is equi ed. Fu he mo e, no limi a-
ions nei he on he swi ching equency (as long as i is con-
s an du ing he en i e bus pe iod) no on he bus ol age a e
imposed. The iden i ica ion o he equi alen impedance is
ob ained wi h he algo i hm sugges ed in [15], and he ecog-
ni ion o he essel is achie ed by means o a con olu ional
neu al ne wo k (CNN) whose only inpu s a e wo ec o s
which con ain he alues o Rand Ldu ing a bus pe iod. The
neu al ne wo k is ained and alida ed o line, and inally
implemen ed in o a p o o ype wi h sys em-on-chip (SoC).
This pape is o ganized as ollows. In Sec ion II he me hod
o iden i y he equi alen impedance as well as he da a acqui-
si ion p ocess a e b ie ly explained. The p oposed neu al
ne wo k, he da a augmen a ion and aining p ocesses and
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FIGURE 1. Simpli ied schema ic o he induc ion hob and i s main wa e o ms. g id is ec i ied and he small bus capaci o leads o a
e y high ippled bus ol age which di ec ly eeds he in e e . Swi ches QHand QLgene a e he al e na ing cu en and snubbe
capaci o s a e included o educe he swi ching losses.
he main esul s a e desc ibed in Sec ion III. Then, he imple-
men a ion o he whole sys em in a p o o ype is p esen ed in
Sec ion IV. Finally, Sec ion Vconcludes his a icle.
II. IDENTIFICATION METHOD AND EXPERIMENTAL
DATA ACQUISITION
In Fig. 1a simpli ied schema ic o he hal -b idge se ies
esonan in e e is shown. The iden i ica ion o he equi -
alen impedance o he load is based on he me hod p oposed
in [15] because i is he one (among [8]–[15]) ha ex ac s
mo e in o ma ion abou he load: i p o ides he alues o he
R−Lequi alen impedance and i s a ia ion wi h he exci-
a ion le el, wha in insically shows how he e omagne ic
p ope ies o he ma e ials o he po s a y.
To accu a ely ob ain he equi alen impedance wi h his
me hod, i is necessa y o measu e he ol age d op o he
load, L, and he cu en ha lows h ough he induc o , iL.
The ol age Lis indi ec ly calcula ed om he sub ac ion o
he ou pu ol age o he in e e , o, and he esonan capac-
i o ol age, c, ( L= o− c) and iLis usually measu ed
wi h a cu en ans o me . The iden i ica ion me hod is based
on a phase-sensi i e de ec o (PSD), which gene a es he
sinusoidal signals ha a e synch onized wi h he in e e sig-
nals. A e some ope a ions and low-pass il e ing, he cosine
and sine i s -ha monic componen s o Land iL, which a e
deno ed as VL,c,VL,s,IL,c, and IL,s(subindex ‘‘1h’’ e e ing
o i s ha monic is d opped ou o no a ion simplici y), a e
ob ained and, wi h hese alues, and he angula swi ching
equency, ωsw, he i s -ha monic equi alen impedance is
ob ained as:
R≈R1h=VL,cIL,c+VL,sIL,s
I2
L,c+I2
L,s
L≈L1h=VL,cIL,s−VL,sIL,c
ωsw(I2
L,c+I2
L,s),(1)
whe e i is assumed ha he phaso s o he load ol age and
he cu en a e gi en by VL,1h=VL,c−jVL,sand IL,1h=
IL,c−jIL,s, espec i ely. Fo mo e speci ic in o ma ion abou
his iden i ica ion me hod, one may e e o [15].
Fo an app op ia e s udy o he p esen ed p oblem, a la ge
expe imen al da ase ha includes a wide a ie y o po s is
equi ed and, o eco d i , an expe imen al p o o ype wi h
an au oma ic da a acquisi ion unc ionali y would be manda-
o y. Fo his eason, he da a acquisi ion in he expe imen al
p o o ype was ully au oma ed. To ob ain he da ase he
esea che only has o place a po illed wi h wa e on he
induc o and launch he au oma ic p ocess ha is explained
in Algo i hm 1, which mus be epea ed as many imes as
he numbe o po s o be iden i ied. This was accomplished
hanks o a Di ec Memo y Access (DMA) con olle , which,
o e e y swi ching equency, ans e s he alues o VL,c,
VL,s,IL,c,IL,sand ωsw du ing a bus pe iod o he Double
Da a Ra e Synch onous Dynamic Random-Access Memo y
(DDR-SDRAM) a ailable in he p o o ype (mo e in o ma ion
will be p o ided in Sec ion IV). This ansac ion is synch o-
nized wi h he ze o-c ossing o he g id ol age and, o a
g id pe iod o 50 Hz, a o al o 868 alues (pe swi ching e-
quency) o he men ioned a iables a e sa ed. Addi ionally,
hanks o his implemen a ion i would be possible o c ea e
a eposi o y o s o age a ack eco d o old and new essels
ha a e launched on o he ma ke .
Then, he impedance alues a e calcula ed o line wi h (1),
ob aining 868 alues o Rand L o e e y swi ching e-
quency. Since o he cu en implemen a ion o Algo i hm 1,
1 sw =500 Hz, sw,max =75 kHz and he maximum powe
o mos o he po s is eached a sw,@maxPowe below 40 kHz,
a leas 70 cu es o R−La e eco ded; ha is mo e han
60 housand alues o Rand L o e e y po . The whole
p ocess shown in Algo i hm 1 akes less han wo seconds
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Algo i hm 1 Au oma ic Da a Acquisi ion
sw ← sw,@maxPowe
while sw ≤ sw,max do
Launch DMA ansac ion (sa e ωsw and ec o s VL,c,
VL,s,IL,cand IL,s)
wai un il DMA ansac ion is comple ed
sw ← sw +1 sw
end while
Send da a o lap op
FIGURE 2. Resul o he au oma ic iden i ica ion algo i hm o an
enameled po . E e y cu e co esponds o he R−L alues du ing a bus
pe iod a a speci ic swi ching equency. The c es o he bus pe iod is a
5 ms. (a) Resis ance. (b) Induc ance.
pe po . An example o he da a ob ained o one po is shown
in Fig. 2.
III. THE NEURAL NETWORK
Deep lea ning is a widesp ead echnique ha has been
inc easingly used du ing he las yea s. This is mo i a ed by
i s abili y o sol e e y complica ed and non-linea p ob-
lems by lea ning complex pa e ns om la ge da ase s [21],
[22]. Mo eo e , unlike o he adi ional me hods, i does no
equi e nei he he use o ex emely complex ma hema ical
exp essions no a deep expe ise in he physics behind he
p oblem o be sol ed.
The e exis many ypes o neu al ne wo ks; one o hem,
known as ully connec ed neu al ne wo k, connec each
neu on in a laye o all he neu ons in he nex laye , wha
exponen ially inc eases i s size and compu a ional complex-
i y wi h he ne wo k dep h. On he o he hand, con olu-
ional neu al ne wo ks ake ad an age o hie a chical pa e ns
in da a o combine ha in o ma ion in o smalle and sim-
ple pa e ns ha a e successi ely educed in he ollowing
laye s. This educes he compu a ional complexi y and he
numbe o coe icien s o be lea ned by he ne wo k, which
a e wo c ucial aspec s o a easible eal- ime implemen-
a ion in an embedded sys em (limi ed memo y and limi ed
compu a ional capaci y). Fu he mo e, con olu ional neu al
ne wo ks ha e been success ully applied o a wide a ie y
o applica ions such as image ecogni ion o indus y [23]
and medicine [24], speech ecogni ion [25], aul diagnosis
in mechanical componen s [26], e c.
A CNN is usually made o con olu ional laye s and pool-
ing laye s. In he con olu ional laye , he inpu , in ou case
he R−L ec o s, is con ol ed wi h a ke nel o il e which
ex ac s he ea u es. Then, an ac i a ion unc ion is applied
o ob ain nonlinea ans o ma ions. The nex ype o laye s,
he pooling laye s, educes he dimension o he da a by
ex ac ing he dominan ea u es. This p ocess is applied as
many imes as he numbe o le els (dep h) he ne wo k has.
Finally, a ully connec ed laye is applied o he esul o he
las laye , which compu es he class sco es and ou pu s he
inal esul .
Apa om he low compu a ional complexi y o CNNs,
he e is ano he eason o choose his ype o ne wo ks o his
applica ion: i akes in o accoun he local connec i i y o he
da a hanks o he connec ion be ween neu ons (a neu on in
one laye is connec ed o some egions o he p e ious laye
h ough he ke nel o he il e bank). This local connec i i y
and neighbo ing ela ionship is also one o he easons why
his ype o neu al ne wo ks pe o ms e y well in compu e
ision applica ions [23], [24].
In his wo k, he ac i a ion unc ion which p o ides he
nonlinea ans o ma ion is he ec i ied linea uni (ReLU)
and i is de ined as:
ReLU : (x)=max{0,x},(2)
whe e xis he ou pu om he p e ious con olu ional laye .
A. DATA AUGMENTATION AND TRAINING
The expe imen al da a was ob ained o 19 di e en po s
(di e en diame e s, ma e ials, manu ac u e s and b ands).
These po s whe e placed on he induc o while ying o align
he induc o and he po as good as possible and making su e
he wa e was boiling when he au oma ic da a acquisi ion
was launched (jus o s anda dizing he acquisi ion o da a).
Besides, o 4 o hese 19 po s addi ional expe imen al da a
was cap u ed a di e en empe a u es ( om ambien em-
pe a u e o 100 ◦C) and a di e en posi ions (po aligned
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wi h he induc o and wi h a adial ho izon al displacemen
induc o -po o 4 and 8 cen ime e s).
The pu pose o his se o measu emen s is o es i
he con olu ional neu al ne wo k is able, apa om dis-
c imina ing be ween di e en po s, o de ec i a po is no
p ope ly aligned wi h he induc o (no ma e he empe a-
u e) o , wha is equi alen om he poin o iew o he
load, i a oo small po is used. This is an impo an issue
in induc ion hobs because when a po is no well aligned
wi h he induc o he esis ance dec eases and, o supply he
same powe , he cu en iLwould each such le els ha a e
no wi hs ood by he powe elec onic de ices. I is wo h
men ioning ha a adi ional esis i e cook op p o ides a
cons an powe and i he po is smalle han he esis ance,
he hea supplied o he po is au oma ically educed because
o he smalle a ea o in e ac ion. Howe e , induc ion hobs
need a mo e sophis ica ed con ol ha is able o educe
he powe when hese smalle po s a e de ec ed. O he wise,
he use would pe cei e ha smalle (o misaligned) po s a e
o e hea ed.
To sum up, aking in o accoun he 19 di e en po s and
he addi ional measu emen s o 4 o hem, ha gi es us a
o al o 27 di e en ags o iden i ie s (because o he mis-
alignmen s) o be ecognized by he neu al ne wo k. A o al
o 300 sweeps we e pe o med, and conside ing ha in e e y
sweep app oxima ely 70 swi ching equencies a e analyzed,
ha gi es us a o al o 20790 cu es o R−L o he whole
se o po s.
Since du ing he aining p ocess o he neu al ne wo k,
he coe icien s o he ke nel ha e o be adjus ed, la ge
da ase a e equi ed, so ha he p obabili y o o e - i ing
is educed. The need o a la ge and di e se da ase is in
ac one o he challenges o he success o neu al ne -
wo ks. Al hough 20790 cu es migh be seen as a decen ly
la ge da ase , da a augmen a ion is ca ied ou in his wo k.
This is a commonly used echnique, which has al eady
been used in o he applica ions [27], [28], when he amoun
o expe imen al da a is no conside ed la ge o di e se
enough.
Fu he mo e, in he eal applica ion small de ia ions and
noise could appea in he iden i ica ion, and his is some hing
ha should be conside ed in he aining s age o he ne wo k.
Thus, e e y R−L ec o is mul iplied by a andom ac o
in he ange [0.9, 1.1], hen, a andom o se in he ange
[0.9, 1.1] o he a e age alue o he ec o is added, and a
andom noise o ±1% is added o e e y sample in he ec o .
Fu he mo e, conside ing ha he ze o-c ossing synch oniza-
ion o g id in he eal hob migh no be ideal, a ci cula
shi o a andom numbe o samples in he ange [-10, 10]
is applied o he ec o s. An example o he esul o his
p ocess is shown in Fig 3. This p ocess is applied many imes
o he da a sa ed o e e y po un il he e o a e ob ained
o he aining da ase equals he one o he es ing da ase .
Mo eo e , he da a augmen a ion algo i hm makes su e ha
he same numbe o cu es a e gene a ed o e e y po , e en
i in he expe imen al da a acquisi ion his condi ion did no
FIGURE 3. Example o da a augmen a ion p ocess (only esis ance is
shown).
hold. This assu es ha he ecogni ion o all he po s will
be simila ly weigh ed du ing he op imiza ion o he aining
p ocess. The inal da ase is di ided in o wo equally sized
se s o 653400 cu es.
B. THE PROPOSED NEURAL NETWORK
Be o e implemen ing he CNN in o he p o o ype, se e al
ne wo ks we e ained and es ed o line. To do so, an exhaus-
i e s udy changing he numbe o con olu ional laye s (#C),
he s ide, he ke nel (K) size, he numbe o ke nels (#K)
and he size o he pooling laye s was pe o med. Gi en ha
he inal goal is he implemen a ion in an embedded de ice,
he numbe o coe icien s was limi ed o a maximum alue
o app oxima ely 20k. The numbe o il e s, n il,1, and ke nel
size, ksize,1, o he i s con olu ional laye we e ob ained as:
n il,1=2#K ksize,1=size(K) (3)
Likewise, o he second con olu ional laye , n il,2and
ksize,2we e calcula ed as:
n il,2=2#K2ksize,2= bsize(K)/S idec,(4)
Con olu ional neu al ne wo ks wi h one and wo con o-
lu ional laye s we e conside ed because he es accu acy
ob ained wi h wo laye s was al eady g ea . The aining and
es ing we e pe o med wi h Tenso Flow and Ma lab using
an NVIDIA GTX1085Ti GPU. The esul s o he pa ame ic
s udy a e shown in Table 1, whe e he numbe o coe i-
cien s (#Coe .), he equi ed mul iply-accumula e ope a ions
(#MAC) and he e o s a e gi en o each es ed ne wo k.
No e ha in CNNs wi h a single con olu ional laye no
pooling laye s a e used.
Apa om CNNs, long sho - e m memo y (LSTM) and
ga ed ecu en uni (GRU) ne wo ks we e also es ed, bu
hei esul s a e no discussed in his a icle because hey
unde pe o med mos o he analyzed CNNs.
Finally, he CNN ha o e ed he lowes e o in he es
(see Table 1) was selec ed as he bes candida e o he eal-
ime implemen a ion. I is a CNN wi h wo con olu ional
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J. Villa e al.: Vessel Recogni ion in Induc ion Hea ing Appliances—A Deep-Lea ning App oach
FIGURE 4. Con usion ma ix o he selec ed wo-laye CNN (numbe 17 in Table 1). The i s le e in he ag is he iden i ie o he b and/ ype o
he po (whe he i is enameled, sandwich, mul ilaye , e c.), he nex numbe iden i ies di e en po s o a gi en b and/ ype, he numbe
be ween he hyphens is he diame e o he po in cen ime e s, and he numbe a e he ‘‘M’’ le e is he adial misalignmen wi h espec o
he induc o in cen ime e s.
TABLE 1. Pa ame ic s udy o CNNs.
laye s whose de ailed s uc u e, he size o he da a be ween
laye s and he numbe o pa ame e s o each ke nel a e sum-
ma ized in Table 2.
The con usion ma ix o he selec ed ne wo k is shown
in Fig. 4. I is wo h men ioning ha o he o iginal da a
TABLE 2. In e nal s uc u e o he selec ed wo-laye CNN.
(wi hou da a augmen a ion) he con usion ma ix showed
no e o s. In Fig. 4i can be obse ed ha he CNN is
able o ecognize he po mos o he imes and i a ely
mis akes po s o di e en b ands o ypes. Some mis akes a e
obse ed when he CNN ies o de ec a misalignmen (see
D3-22-M0 and D3-22-M4) o when wo di e en po s o he
same b and/ ype wi h he same diame e a e aligned wi h he
induc o (see E1-22-M0 and E3-22-M0).
Mo eo e , i can be no iced ha o a gi en ype o po , le ’s
say ype ‘‘E’’, i a big po is misaligned 4 cm (E3-22-M4),
he CNN some imes mis akes i o an aligned bu smalle po
(E2-17.5-M0). In ac , his was an expec ed beha io because
om he poin o iew o he load, hose si ua ions migh be
seen as equi alen .
IV. IMPLEMENTATION
The expe imen al p o o ype is made o some pa s o a
comme cial induc ion hob and wo p in ed ci cui boa ds
16058 VOLUME 9, 2021
J. Villa e al.: Vessel Recogni ion in Induc ion Hea ing Appliances—A Deep-Lea ning App oach
FIGURE 5. Expe imen al p o o ype.
(PCBs) ha we e designed o esea ch pu poses. One o
he PCBs moun s he powe elec onics ci cui y and he
o he one, which can be connec ed o he o me , moun s
he condi ioning and acquisi ion ci cui s. Besides, he second
PCB is compa ible wi h he ca ie boa d TE0703 om T enz
Elec onics, which is connec ed o he sys em-on-module
(SoM) TE0720 (also om T enz Elec onics) which, in u n,
includes he sys em-on-chip Zynq-7020. This SoC includes
in a single chip he ield-p og ammable ga e a ay (FPGA)
ab ic and a dual co e ARM Co ex-A9 p ocesso . Besides,
he SoM also includes a 1 GB DDR-SDRAM.
The acquisi ion o he elec ical signals o, c,iLand g id
( his las a iable is used o he synch oniza ion wi h he
ze o-c ossing o he g id ol age) is accomplished h ough
12-bi LTC-2315-12 analog- o-digi al con e e s (ADCs)
whose sampling equency is se a 2.78 Msps. These ADCs
a e con olled h ough a se ial pe iphe al in e ace (SPI)
p o ocol.
The modula o ha con ols he IGBTs, he iden i ica ion
o he load [15], he con ol o he ADCs and he con-
olle o he DMA ansac ions a e implemen ed on he
FPGA ab ic whose clock equency is se a 100 MHz.
The signals VL,c,VL,s,IL,c,IL,sand ωsw a e sen o he
DMA con olle h ough he Ad anced eX ensible In e ace 4
(AXI4)-S eam p o ocol. Finally, he DMA con olle , which
is con igu ed in s eam o memo y-map mode, w i es he da a
in he DDR-SDRAM whene e he ARM (co e 1) p ocesso
eques s i .
A he same ime he ARM (co e 0), which uns he ope -
a ing sys em Pe alinux, is in cha ge o he communica ion
wi h a g aphical use in e ace (GUI) p og ammed in Ma lab
and unning in a lap op. This communica ion is es ablished
o e E he ne h ough a TCP/IP p o ocol and was o g ea
impo ance o he au oma ic da a acquisi ion explained in
Sec ion II.
The con olu ional neu al ne wo k is implemen ed in loa -
ing poin (single p ecision) in he co e 1 o he ARM p o-
cesso . To do so, an in e up is gene a ed wi h one o he
iple ime coun e s (TTCs), whose in e up handle launches
a DMA ansac ion which sa es he ec o s VL,c,VL,s,IL,c,
IL,sand ωsw o a bus pe iod in he DDR-SDRAM. When he
ansac ion inishes, an in e up is gene a ed, and a e com-
pu ing (1) o each o he 868 samples, he CNN is execu ed.
This p ocess is execu ed 10 imes pe second, lea ing ime
o he ARM (co e 1) o un o he asks such as con ol o
powe , moni o ing o a iables, e c. The clock equency o
he ARM is 667 MHz. I is wo h men ioning ha in he inal
applica ion, depending on he equi emen s o he induc ion
hob and he ea u es o i s SoC, i migh no be necessa y o
ecognize he po con inuously o a leas no a such a as
a e.
The en i e code, once p og ammed in C, equi es 130 kB o
memo y including he mo e han 85 kB o coe icien s. The
execu ion o he con olu ional neu al ne wo k oge he wi h
he calcula ion o he R−L alues (1) akes abou 2.55 ms
in he ARM. I is wo h no ing ha he CNN is execu ed only
once e e y 100 ms. A simpli ied block diag am o he sys em
is shown in Fig 6.
A ideo is a ached wi h his wo k whe e he pe o mance
o he eal- ime implemen a ion in he p o o ype is shown.
In his ideo, di e en po s a di e en misalignmen s a e
FIGURE 6. Simpli ied block diag am o he sys em. Subindex ‘‘dig’’ e e s o digi al and has only been added o di e en ia e
be ween analog and digi al signals.
VOLUME 9, 2021 16059
J. Villa e al.: Vessel Recogni ion in Induc ion Hea ing Appliances—A Deep-Lea ning App oach
placed on he induc o while he SoC execu es he p oposed
algo i hm and p in s he ag o he p edic ed po h ough a
e minal.
V. CONCLUSION
Deep lea ning has been e ol ing du ing he las yea s due o
he con inuously inc easing compu a ional capaci y o new
echnologies and i s amazing abili y o lea n complex pa e ns
om la ge da ase s.
In his wo k, a con olu ional neu al ne wo k is applied
o ecognize he po ha is hea ed in a domes ic induc ion
hob. The inpu da a o he neu al ne wo k a e wo ec o s
o 868 alues each which con ain he a ia ion o he equi a-
len esis ance and induc ance o he load du ing a bus pe iod.
To ain he neu al ne wo k, he equi alen impedance o
se e al po s was iden i ied du ing a bus cycle o di e -
en swi ching equencies, empe a u es and misalignmen s.
Th ough da a augmen a ion, a la ge da ase was ob ained,
wi h which he neu al ne wo k was ained. Se e al ypes o
neu al ne wo ks we e es ed o line by a ying he numbe
o laye s, he s ide, he il e size and he numbe o il e s
o each laye . The esul s ob ained du ing he es ing p ocess
show ha he p oposed CNN is able o success ully ecognize
he po s wi h an a e age e o a e o 0.7819%. Besides,
he expe imen al esul s show ha he p oposed solu ion is
also able o es ima e i , and how much, a po is misaligned
wi h he induc o e en when he equi alen impedance is
iden i ied a di e en po empe a u es.
Mo eo e , wi h he p oposed me hod, he induc o is used
as a sma -senso , so ha no ex a-ha dwa e is equi ed, p e-
se ing he low-cos na u e o DIH and aking ad an age o
he inc easingly highe compu a ional complexi y a ailable
in embedded sys ems.
Finally, he p oposed CNN was implemen ed in an expe -
imen al p o o ype o show i s eal- ime pe o mance and he
easibili y o i s inclusion in a eal hob. This is he i s imple-
men a ion o a po iden i ie based on con olu ional neu al
ne wo ks and he in o ma ion o he a ia ion o he equi -
alen impedance wi h he exci a ion le el, which will help
b oadening he esea ch and de elopmen a eas in domes ic
induc ion hea ing and will enable new unc ionali ies in u u e
gene a ions o induc ion hobs.
REFERENCES
[1] N. A. Ahmed, ‘‘High- equency so -swi ching AC con e sion ci cui wi h
dual-mode PWM/PDM con ol s a egy o high-powe IH applica ions,’’
IEEE T ans. Ind. Elec on., ol. 58, no. 4, pp. 1440–1448, Ap . 2011.
[2] V. Es e e, J. Jo dan, E. Sanchis-Kilde s, E. J. Dede, E. Mase , J. B. Ejea,
and A. Fe e es, ‘‘Enhanced pulse-densi y-modula ed powe con ol o
high- equency induc ion hea ing in e e s,’’ IEEE T ans. Ind. Elec on.,
ol. 62, no. 11, pp. 6905–6914, No . 2015.
[3] J. Ace o, J. Bu dío, L. Ba agán, D. Na a o, R. Alonso, J. Ga cía,
F. Mon e de, P. He nández, and S. L. I. Ga de, ‘‘Domes ic induc ion
appliances,’’ IEEE Ind. Appl. Mag., ol. 16, no. 2, pp. 39–47, Ma . 2010.
[4] O. Lucia, J. Ace o, C. Ca e e o, and J. M. Bu dio, ‘‘Induc ion hea ing
appliances: Towa d mo e lexible cooking su aces,’’ IEEE Ind. Elec on.
Mag., ol. 7, no. 3, pp. 35–47, Sep. 2013.
[5] J. Ace o, C. Ca e e o, R. Alonso, and J. M. Bu dio, ‘‘Quan i a i e e alu-
a ion o induc ion e iciency in domes ic induc ion hea ing applica ions,’’
IEEE T ans. Magn., ol. 49, no. 4, pp. 1382–1389, Ap . 2013.
[6] H. Ku ose, D. Miyagi, N. Takahashi, N. Uchida, and K. Kawanaka,
‘‘3-D eddy cu en analysis o induc ion hea ing appa a us conside ing hea
emission, hea conduc ion, and empe a u e dependence o magne ic cha -
ac e is ics,’’ IEEE T ans. Magn., ol. 45, no. 3, pp. 1847–1850, Ma . 2009.
[7] J. Ace o, O. Lucia, I. Millan, L. A. Ba agan, J.-M. Bu dio, and R. Alonso,
‘‘Iden i ica ion o he ma e ial p ope ies used in domes ic induc ion hea -
ing appliances o sys em-le el simula ion and design pu poses,’’ in P oc.
25 h Annu. IEEE Appl. Powe Elec on. Con . Expo. (APEC), Feb. 2010,
pp. 439–443.
[8] B. A. Nguyen, Q. D. Phan, D. M. Nguyen, K. L. Nguyen, O. Du ieu, and
P. Maussion, ‘‘Pa ame e iden i ica ion me hod o a h ee-phase induc ion
hea ing sys em,’’ IEEE T ans. Ind. Appl., ol. 51, no. 6, pp. 4853–4860,
No . 2015.
[9] A. Dominguez, A. O in, I. U iza, L. A. Ba agan, D. Na a o, and
J. I. A igas, ‘‘Load iden i ica ion o domes ic induc ion hea ing based
on pa icle swa m op imiza ion,’’ in P oc. IEEE 15 h Wo kshop Con ol
Modeling Powe Elec on. (COMPEL), Jun. 2014, pp. 1–6.
[10] O. Jimenez, L. A. Ba agan, I. U iza, O. Lucia, D. Na a o, and
J. I. A igas, ‘‘FPGA-based eal- ime ha monic impedance measu emen
o se ies esonan loads by using lock-in algo i hm,’’ in P oc. 37 h Annu.
Con . IEEE Ind. Elec on. Soc. (IECON), No . 2011, pp. 2808–2813.
[11] O. Jimenez, O. Lucia, I. U iza, L. A. Ba agan, and D. Na a o, ‘‘Analysis
and implemen a ion o FPGA-based online pa ame ic iden i ica ion algo-
i hms o esonan powe con e e s,’’ IEEE T ans. Ind. In o ma ., ol. 10,
no. 2, pp. 1144–1153, May 2014.
[12] V. T. Kilic, E. Unal, N. Yilmaz, and H. V. Demi , ‘‘All-su ace induc ion
hea ing wi h high e iciency and space in a iance enabled by a aying
squi cle coils in squa e la ice,’’ IEEE T ans. Consum. Elec on., ol. 64,
no. 3, pp. 339–347, Aug. 2018.
[13] D. Puyal, C. Be nal, J. M. Bu dio, J. Ace o, and I. Millan, ‘‘Ve sa ile high-
equency in e e module o la ge-signal induc i e loads cha ac e iza ion
up o 1.5 MHz and 7 kW,’’ IEEE T ans. Powe Elec on., ol. 23, no. 1,
pp. 75–87, Jan. 2008.
[14] H. Sa nago, O. Lucia, and J. M. Bu dio, ‘‘FPGA-based esonan load
iden i ica ion echnique o lexible induc ion hea ing appliances,’’ IEEE
T ans. Ind. Elec on., ol. 65, no. 12, pp. 9421–9428, Dec. 2018.
[15] J. Villa, L. A. Ba agan, J. I. A igas, D. Na a o, A. Dominguez Vicen e,
and T. Cabeza, ‘‘SoC-based in-cycle load iden i ica ion o induc ion hea -
ing appliances,’’ IEEE T ans. Ind. Elec on., ea ly access, Jul. 10, 2020,
doi: 10.1109/TIE.2020.3007083.
[16] C. F anco, J. Ace o, R. Alonso, C. Sagues, and D. Paesa, ‘‘Induc i e senso
o empe a u e measu emen in induc ion hea ing applica ions,’’ IEEE
Senso s J., ol. 12, no. 5, pp. 996–1003, May 2012.
[17] J. Se ano, J. Ace o, I. Lope, C. Ca e e o, J. M. Bu dio, and R. Alonso,
‘‘Modeling o domes ic induc ion hea ing sys ems wi h non-linea sa -
u able loads,’’ in P oc. IEEE Appl. Powe Elec on. Con . Expo. (APEC),
Ma . 2017, pp. 3127–3133.
[18] O. Lucia, D. Na a o, P. Guillen, H. Sa nago, and S. Lucia, ‘‘Deep
lea ning-based magne ic coupling de ec ion o ad anced induc ion hea -
ing appliances,’’ IEEE Access, ol. 7, pp. 181668–181677, 2019.
[19] A. Bono-Nuez, C. Be nal-Ruíz, B. Ma ín-del-B ío, F. J. Pé ez-Cebolla,
and A. Ma ínez-I u be, ‘‘Recipien size es ima ion o induc ion hea ing
home appliances based on a i icial neu al ne wo ks,’’ Neu al Compu .
Appl., ol. 28, no. 11, pp. 3197–3207, No . 2017. [Online]. A ailable:
h p://link.sp inge .com/10.1007/s00521-016-2227-6
[20] A. Bono-Nuez, B. Ma in-del-B io, C. Be nal-Ruiz, F. J. Pe ez-Cebolla,
A. Ma inez-I u be, and I. Sanz-Go acha egui, ‘‘The induc o as a sma
senso o ma e ial iden i ica ion in domes ic induc ion cooking,’’ IEEE
Senso s J., ol. 18, no. 6, pp. 2462–2470, Ma . 2018.
[21] Y. LeCun, Y. Bengio, and G. Hin on, ‘‘Deep lea ning,’’ Na u e,
ol. 521, no. 7553, pp. 436–444, May 2015. [Online]. A ailable:
h p://www.na u e.com/a icles/na u e14539
[22] R. C. Gonzalez, ‘‘Deep con olu ional neu al ne wo ks [Lec u e No es],’’
IEEE Signal P ocess. Mag., ol. 35, no. 6, pp. 79–87, No . 2018.
[23] X. Tao, D. Zhang, Z. Wang, X. Liu, H. Zhang, and D. Xu, ‘‘De ec ion o
powe line insula o de ec s using ae ial images analyzed wi h con olu-
ional neu al ne wo ks,’’ IEEE T ans. Sys ., Man, Cybe n. Sys ., ol. 50,
no. 4, pp. 1486–1498, Ap . 2020.
[24] A. H. Abdi, C. Luong, T. Tsang, G. Allan, S. Nou anian, J. Jue, D. Hawley,
S. Fleming, K. Gin, J. Swi , R. Rohling, and P. Abolmaesumi, ‘‘Au o-
ma ic quali y assessmen o echoca diog ams using con olu ional neu al
ne wo ks: Feasibili y on he apical ou -chambe iew,’’ IEEE T ans. Med.
Imag., ol. 36, no. 6, pp. 1221–1230, Jun. 2017.
16060 VOLUME 9, 2021
J. Villa e al.: Vessel Recogni ion in Induc ion Hea ing Appliances—A Deep-Lea ning App oach
[25] Y. Qian, M. Bi, T. Tan, and K. Yu, ‘‘Ve y deep con olu ional neu al
ne wo ks o noise obus speech ecogni ion,’’ IEEE/ACM T ans. Audio,
Speech, Lang. P ocess., ol. 24, no. 12, pp. 2263–2276, Dec. 2016.
[26] G. Jiang, H. He, J. Yan, and P. Xie, ‘‘Mul iscale con olu ional neu al
ne wo ks o aul diagnosis o wind u bine gea box,’’ IEEE T ans. Ind.
Elec on., ol. 66, no. 4, pp. 3196–3207, Ap . 2019.
[27] Z. Meng, X. Guo, Z. Pan, D. Sun, and S. Liu, ‘‘Da a segmen a ion and
augmen a ion me hods based on aw da a using deep neu al ne wo ks
app oach o o a ing machine y aul diagnosis,’’ IEEE Access, ol. 7,
pp. 79510–79522, 2019.
[28] J. Salamon and J. P. Bello, ‘‘Deep con olu ional neu al ne wo ks and
da a augmen a ion o en i onmen al sound classi ica ion,’’ IEEE Signal
P ocess. Le ., ol. 24, no. 3, pp. 279–283, Ma . 2017.
JORGE VILLA (Membe , IEEE) ecei ed he
M.Sc. deg ee in indus ial enginee ing om he
Uni e si y o Za agoza, Za agoza, Spain, in 2016,
whe e he is cu en ly pu suing he Ph.D. deg ee in
elec onic enginee ing.
His main esea ch in e es s include esonan
con e e s and digi al con ol o induc ion hea ing
applica ions.
M . Villa is a membe o he A agon Ins i u e
o Enginee ing Resea ch (I3A), G oup o Powe
Elec onics and Mic oelec onics (GEPM).
DENIS NAVARRO ecei ed he M.Sc. deg ee in
mic oelec onics om he Uni e si y o Mon pel-
lie , F ance, in 1987, and he Ph.D. deg ee om he
Uni e si y o Za agoza, in 1992.
Since Sep embe 1988, he has been wi h he
Depa men o Elec onic Enginee ing and Com-
munica ions, Uni e sidad de Za agoza, whe e he
is cu en ly a P o esso . In 1993, he designed
he i s SPARC mic op ocesso in Eu ope. His
cu en esea ch in e es s include CAD o VLSI,
low-powe ASIC design, and modula ion echniques o powe con e e s.
He is in ol ed in he implemen a ion o new applica ions o in eg a ed
ci cui s.
D . Na a o is a membe o he A agon Ins i u e o Enginee ing
Resea ch (I3A).
ALBERTO DOMINGUEZ ecei ed he Ph.D.
deg ee in elec onic enginee ing om he Uni e -
si y o Za agoza, Spain, in 2017.
Since 2017, he has been wo king wi h BSH
Home Appliances in he de elopmen o new
domes ic induc ion cook ops. His main esea ch
in e es s include modeling, con ol, and op imiza-
ion o cons ained sys ems, especially de o ed o
esonan in e e s in domes ic induc ion hea ing.
JOSE I. ARTIGAS ecei ed he M.Sc. and Ph.D.
deg ees in elec ical enginee ing om he Uni e -
si y o Za agoza, Za agoza, Spain, in 1989 and
1996, espec i ely.
He has been wi h he Depa men o Elec onic
Enginee ing and Communica ions, Uni e si y o
Za agoza, whe e he is cu en ly a P o esso . He has
been in ol ed in di e en esea ch and de elop-
men p ojec s. His main esea ch in e es s include
signal acquisi ion, digi al con ol, and modula ion
s a egies applied o powe con e e s.
D . A igas is a membe o he A agon Ins i u e o Enginee ing Resea ch
(I3A), G oup o Powe Elec onics and Mic oelec onics (GEPM).
LUIS A. BARRAGAN ecei ed he M.Sc. and
Ph.D. deg ees in physics om he Uni e si y o
Za agoza, Za agoza, Spain, in 1988 and 1993,
espec i ely.
He is cu en ly a P o esso wi h he Depa men
o Elec onic Enginee ing and Communica ions,
Uni e si y o Za agoza. He has been in ol ed in
di e en esea ch and de elopmen p ojec s on
induc ion-hea ing sys ems o home appliances.
His esea ch in e es s include modeling and digi al
con ol applied o domes ic induc ion hea ing.
D . Ba agan is a membe o he A agon Ins i u e o Enginee ing Resea ch
(I3A), G oup o Powe Elec onics and Mic oelec onics (GEPM).
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