NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems

Dr. Sanjay Garg

Presented at: ICM 2006, Anaheim, CA

Abstract With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Branch (CDB) at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. This presentation describes the current CDB activities in support of the NASA Aeronautics Research Mission, with an emphasis on activities under the Integrated Vehicle Health Management (IVHM) and Integrated Resilient Aircraft Control (IRAC) projects of the Aviation Safety Program. Under IVHM, CDB focus is on developing advanced techniques for monitoring the health of the aircraft engine gas path with a focus on reliable and early detection of sensor, actuator and engine component faults. Under IRAC, CDB focus is on developing adaptive engine control technologies which will increase the probability of survival of aircraft in the presence of damage to flight control surfaces or to one or more engines. The technology development plans are described as well as results from recent research accomplishments.

https://ntrs.nasa.gov/search.jsp?R=20070018154 2019-08-30T00:58:45+00:00Z

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Val

idat

ion

•Ex

pert

Sys

tem

•N

eura

l Net

wor

k•

Mod

el B

ased

Dia

gnos

tics

•Au

tom

ated

Rea

soni

ng•

Stat

istic

al C

orre

latio

n•

Sign

al P

roce

ssin

g

Mai

nten

ance

and

Insp

ectio

n A

dvis

orie

s, O

pera

ting

Adv

isor

ies

Mai

nten

ance

, Ove

rhau

l &

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ratin

g H

isto

ry

Dat

a Fu

sion

for P

ropu

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n H

ealth

Man

agem

ent

Dat

a Fu

sion

for P

ropu

lsio

n H

ealth

Man

agem

ent

Con

trols

and

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amic

s Bra

nch

at L

ewis

Fie

ldG

lenn

Res

earc

h C

ente

r

Engi

ne D

iagn

ostic

Dat

a / I

nfor

mat

ion

Fusi

onEn

gine

Dia

gnos

tic D

ata

/ Inf

orm

atio

n Fu

sion

(App

lied

to P

ratt

& W

hitn

ey F

117

Eng

ine

–C

17 A

ircra

ft)

High Level Fusion Module (Bayesian Networks)

Engin

eIns

trume

ntatio

n•G

as P

ath•V

ibrati

on•L

ubric

ation

Sys

tem•A

dvan

ced S

enso

rs–E

lectro

static

s–S

tress

Wav

e

Data Alignment Module

Mod

el /

Ana

lysi

s M

odul

e

Fuse

d D

iagn

ostic

Info

rmat

ion

(Lis

t of c

andi

date

fa

ults

with

co

nfid

ence

leve

ls)

Gas

-Pat

hA

naly

sis

Em

piric

alLu

bric

atio

n S

yste

mM

odel

NN

-Bas

ed

Ano

mal

y D

etec

tor

Vib

ratio

nA

naly

sis

Not U

sed U

nder

Cur

rent

Rese

arch

Effo

rt•M

ainten

ance

Inf

orma

tion

•FAD

EC F

ault C

odes

Com

bine

Ava

ilabl

eIn

form

atio

n/D

ata

Sour

ces

and

Dia

gnos

tic M

odul

es…

.

….T

o A

utom

ate

and

Enha

nce

Dia

gnos

tic S

yste

m In

fere

nce

Cap

abili

ties

Con

trols

and

Dyn

amic

s Bra

nch

at L

ewis

Fie

ldG

lenn

Res

earc

h C

ente

r

Alg

orith

mic

Fus

ion

for E

xten

ded

Gas

Pat

h A

naly

sis

Cap

abili

tyA

lgor

ithm

ic F

usio

n fo

r Ext

ende

d G

as P

ath

Ana

lysi

s C

apab

ility

eSTO

RM

Gas

Pat

hAD

Sens

orD

ata

Shor

t Ter

mFi

lter

Long

Ter

mFi

lter

Shor

t Ter

mFi

lter

Long

Ter

mFi

lter

Pers

iste

ncy

Logi

c

Pers

iste

ncy

Logi

c

eSTORM & GPAD Fusion &Fault Isolation & Accommodation Logic

Extra

cted

Feat

ures

Proc

esse

dFe

atur

es

Fuse

dD

iagn

ostic

Asse

ssm

ent

Arc

hite

ctur

e:•F

uses

Enh

ance

d Se

lf-Tu

ning

Onb

oard

Rea

l-tim

e M

odel

(eS

TOR

M)

and

Gas

Pat

h A

nom

aly

Det

ecto

r (G

PA

D)

•Per

sist

ency

logi

c en

able

s sy

stem

to d

istin

guis

h be

twee

n fa

ults

and

noi

se•F

uzzy

logi

c fu

sion

ap

proa

ch c

ombi

nes

algo

rithm

out

puts

HPC

Fau

ltIn

ject

edP2

5 Se

nsor

Bia

s In

ject

edC

orre

ctD

perf

Estim

atio

n

Cor

rupt

edD

perf

Estim

atio

n

Alg

orith

mic

Fus

ion

Arc

hite

ctur

e

Sim

ulat

ion

Res

ults

:eS

TOR

M:

•Sen

sor f

aults

cor

rupt

eS

TOR

M’s

abilit

y to

acc

urat

ely

estim

ate

com

pone

nt h

ealth

Fuse

d eS

TOR

M +

GP

AD

:•S

enso

r fau

lts a

re a

utom

atic

ally

di

agno

sed

and

acco

mm

odat

ed•e

STO

RM

is a

ble

to a

ccur

atel

y es

timat

e co

mpo

nent

hea

lth in

th

e pr

esen

ce o

f a s

enso

r fau

lt

Con

trols

and

Dyn

amic

s Bra

nch

at L

ewis

Fie

ldG

lenn

Res

earc

h C

ente

r

Engi

ne H

ealth

Man

agem

ent I

ndus

try

Rev

iew

Engi

ne H

ealth

Man

agem

ent I

ndus

try

Rev

iew

•O

bjec

tive:

Pro

vide

pub

licly

ava

ilabl

e be

nchm

ark

diag

nost

ic

prob

lem

s an

d m

etric

s to

faci

litat

e th

e de

velo

pmen

t and

co

mpa

rison

of c

andi

date

dia

gnos

tic a

lgor

ithm

s•

Stat

us &

Pla

ns:

–E

stab

lishe

d as

a c

olla

bora

tive

proj

ect u

nder

The

Tec

hnic

al C

o-op

erat

ion

Pro

gram

(TTC

P) P

ropu

lsio

n &

Pow

er S

yste

ms

Pan

el–

Sub

-team

s ar

e fo

rmul

atin

g th

eme

prob

lem

s &

met

rics

in th

ree

EH

M

area

s:

•G

as P

ath

Dia

gnos

tics

•Vi

brat

ion

Dia

gnos

tics

•Li

fe U

sage

Mon

itorin

g–

Onc

e pr

oble

ms

are

com

plet

ed a

n in

vita

tion

will

be

exte

nded

to

acad

emic

/indu

stry

exp

erts

to p

rovi

de p

robl

em s

olut

ions

–A

con

fere

nce

to p

rese

nt re

sults

will

be

held

–R

esul

ts w

ill b

e do

cum

ente

d

EHM

R&

D a

ctiv

ities

hav

e si

gnifi

cant

ly in

crea

sed

in re

cent

yea

rsH

owev

er d

ue to

the

use

of d

iffer

ent t

erm

inol

ogie

s, m

etric

s, a

nd

appl

icat

ions

ther

e is

no

basi

s of

com

paris

on.

Them

e Pr

oble

ms

Dia

gnos

ticSo

lutio

ns

Engi

ne H

ealth

Man

agem

ent I

ndus

try

Rev

iew

Engi

ne H

ealth

Man

agem

ent I

ndus

try

Rev

iew

App

roac

hA

ppro

ach

Sens

ed P

aram

eter

His

torie

s

Faul

t occ

urs

()

()

21

1

2

2

1

*)

(

⎥⎥⎥⎥⎥ ⎦⎤

⎢⎢⎢⎢⎢ ⎣⎡

ΔΔ

⎟⎟ ⎠⎞⎜⎜ ⎝⎛

ΔΔ−

ΔΔ

=

∑

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m ik

m ik

kk

n

i

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Eval

uatio

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etric

s•A

ccur

acy

•Sen

sitiv

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obus

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iagn

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Solu

tions

Syst

em a

naly

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Info

rmat

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Dev

elop

men

t &Va

lidat

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Dat

aset

s

Blin

d Te

st C

ases

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hem

e pr

oble

ms:

Rel

evan

t pr

oble

ms

cons

truct

ed fr

om

publ

icly

ava

ilabl

e m

odel

s an

d da

tase

ts

2. S

olut

ion

prov

ider

s gi

ven:

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gnos

tic re

quire

men

ts•S

yste

m a

naly

tical

info

rmat

ion

•Dev

elop

men

t & v

alid

atio

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tase

ts•B

lind-

test

cas

es•E

xam

ple

solu

tions

3. E

valu

atio

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etric

s:

Def

ined

and

app

lied

to

prov

ide

a un

iform

as

sess

men

t of d

iagn

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so

lutio

ns

Doc

umen

tR

esul

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4. D

ocum

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fere

nce

held

to

pres

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esul

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roce

edin

gs p

ublis

hed

Con

trols

and

Dyn

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s Bra

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ente

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onom

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olog

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s Pr

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Red

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man

dep

ende

ncy

in th

e co

ntro

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ratio

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opul

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Self-

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Engi

ne C

ontr

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m•P

erfo

rms

auto

nom

ous

prop

ulsi

on s

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m m

onito

ring,

di

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, and

ada

ptin

g fu

nctio

ns•C

ombi

nes

info

rmat

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from

mul

tiple

dis

para

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sour

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g st

ate-

of-th

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t dat

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tech

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unic

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with

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man

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fligh

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timiz

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per

form

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Eng

ine

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form

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R

equi

rem

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Mod

el-B

ased

Fau

lt D

etec

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Fuzz

y B

elie

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etw

ork

Dat

a Fu

sion

p

FAD

EC

u

cont

rol

sign

als

Sens

orou

tput

PLA

Rea

l Eng

ine

Clo

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trol

NMPC

min

J

Opt

imiz

er

Stat

e/Pa

ram

eter

Est

.+ -

xP

ˆ ,

yy

vw Eng

. Mod

el

Eng

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el

REF

p

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u

cont

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sign

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l Eng

ine

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min

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Opt

imiz

er

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e/Pa

ram

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.+ -

xP

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vw Eng

. Mod

el

Eng

. Mod

el

REF

Con

trols

and

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s Bra

nch

at L

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lenn

Res

earc

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ente

r

Inte

llige

nt R

etro

fit A

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tect

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Inte

llige

nt R

etro

fit A

rchi

tect

ure

Con

trols

and

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amic

s Bra

nch

at L

ewis

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lenn

Res

earc

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ente

r

Ret

rofit

Arc

hite

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etro

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rchi

tect

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-- Ste

ady

Stat

e Ev

alua

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Stea

dy S

tate

Eva

luat

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Con

trols

and

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amic

s Bra

nch

at L

ewis

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ldG

lenn

Res

earc

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ente

r

•O

bjec

tive

–To

pro

vide

ada

ptiv

e en

gine

con

trol t

o m

axim

ize

the

prob

abili

ty o

f su

rviv

al to

dam

aged

airc

raft

•A

ppro

ache

s:–

Dam

aged

Eng

ine

Scen

ario

:•

dam

age

dete

ctio

n an

d is

olat

ion

•da

mag

e m

itiga

tion

and

parti

al p

ower

reco

very

–D

amag

ed A

ircra

ft Sc

enar

io:P

ast r

esea

rch

and

expe

rienc

e (e

g.

TOC

–Th

rust

onl

y C

ontro

l) sh

owed

that

pro

puls

ion

syst

ems

can

be v

ery

effe

ctiv

e to

ols

to s

ave

airp

lane

s fro

m a

dver

se c

ondi

tions

. Th

is c

apab

ility

can

be

furth

er e

nhan

ced

by:

•In

depe

nden

t eng

ine

thru

st c

ontro

l cap

abili

ty•

Ove

r-the

-lim

it en

gine

ope

ratio

n fo

r max

imum

thru

st a

nd

resp

onse

IRA

C

IRA

C ––

Res

ilien

t Pro

puls

ion

Con

trol

Res

ilien

t Pro

puls

ion

Con

trol

Con

trols

and

Dyn

amic

s Bra

nch

at L

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Fie

ldG

lenn

Res

earc

h C

ente

r

Typi

cal E

ngin

e Pr

otec

tion

Lim

itsTy

pica

l Eng

ine

Prot

ectio

n Li

mits

•FA

DE

C s

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m a

djus

ts fu

el fl

ow to

set

pow

er

man

agem

ent

-Spe

ed C

ontro

l lim

its-A

ccel

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ion/

Dec

eler

atio

n sp

eed

limits

-Fue

l Flo

w li

mits

-Pre

ssur

e C

ontro

l

Cor

eS

peed

PS

3Li

mits

Acc

el/

Dec

elFa

n

Acc

el/

Dec

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ore

Acc

el/

Dec

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S3

Fuel

Flow

Ove

rS

peed

Pow

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anag

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ched

ule

Fuel

Con

trol

Des

igne

d Li

mits

:B

urne

r Pre

ssur

e,

Tem

pera

ture

s,S

peed

Red

Lin

e

Man

y of

thes

e lim

its c

an b

e re

laxe

d to

en

hanc

e th

e pe

rfor

man

ce a

t the

cos

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shor

tene

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life.

Con

trols

and

Dyn

amic

s Bra

nch

at L

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Res

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xam

ple

: Thr

ust

S

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n Te

mpe

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re

S

usta

inab

le T

ime

Dur

atio

n S

tatio

n Te

mpe

ratu

re [°

F]

Scen

ario

R

equi

rem

ents

Thrust [lb]

40,0

00

45,0

00

55,0

00

60,0

00

65,0

00

70,0

00

75,0

00

Time before failure [min]

100

908070605040302010

3000

3500

4000

4500

Thru

st

Thru

st v

svsLi

fe T

rade

Life

Tra

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ffO

ff

Con

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Res

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Dam

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Ass

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ode

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pera

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Bey

ond

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Engi

ne S

tatu

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ine

Perf

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ance

Lim

its-P

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rman

ce/L

ife T

rade

-off

Cur

ve

110100

1000

1000

0

90%

100%

110%

120%

Flig

ht C

ontr

ol C

omm

ands

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ine

Ope

ratio

n M

ode

-Eng

ine

Perf

orm

ance

Req

uire

men

ts

Ada

ptiv

e Fl

ight

Con

trol

-Dec

isio

n B

ased

on

Dam

age,

Eng

ine

capa

bilit

ies,

Ris

ks

IRA

C

IRA

C ––

Airf

ram

e Pr

opul

sion

Con

trol

Inte

grat

ion

Airf

ram

e Pr

opul

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Con

trol

Inte

grat

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Con

trols

and

Dyn

amic

s Bra

nch

at L

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Fie

ldG

lenn

Res

earc

h C

ente

r

–E

xten

ded

Eng

ine

Con

trol D

evel

opm

ent:

•B

asel

ine

Eng

ine

and

Con

trol M

odel

s•

Hig

h Le

vel R

equi

rem

ents

•E

ngin

e M

odel

Impr

ovem

ents

•E

ngin

e D

ynam

ic M

odel

s•

Ope

rabi

lity

Stu

dy fo

r Ext

ende

d O

pera

tion

•Fa

ilure

Mod

e S

tudy

•Li

fe M

odel

ing

•E

nhan

ced

Eng

ine

Con

trol D

evel

opm

ent

•Fl

ight

Sim

ulat

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estin

g•

TOC

/PC

A T

estin

g

Res

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t Pro

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ion

Con

trol

R

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ent P

ropu

lsio

n C

ontr

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Res

earc

h Ta

sks

Res

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sks

Syst

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ic S

enso

r Sel

ectio

n St

rate

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4)Sy

stem

atic

Sen

sor S

elec

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Stra

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Mer

it A

lgor

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Engi

ne

Inv

Mod

el(P

aram

eter

Opt

)

Sele

ctio

n A

lgor

ithm

(C

ombi

nato

rial O

pt)

Stat

istic

al

Eval

uatio

n A

lgor

ithm

Mer

it Fu

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n

Pred

icte

d St

ates

Targ

eted

Fau

lt Sc

enar

ios

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Fa

ults

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st

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ates

Faul

t Ris

ks +

Det

ectio

n Li

mits

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dida

te

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orsCan

dida

te

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ors

List

Evol

ved

Sens

or

Suite

s

Yes

No

Evol

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n C

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Opt

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Se

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iteGoo

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ites

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s

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it Va

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ne

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Opt

)

Sele

ctio

n A

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pt)

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istic

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n A

lgor

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Mer

it Fu

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n

Pred

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d St

ates

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eted

Fau

lt Sc

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Fa

ults

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st

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ates

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ks +

Det

ectio

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mits

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orsCan

dida

te

Sens

ors

List

Evol

ved

Sens

or

Suite

s

Yes

No

Evol

utio

n C

ompl

ete

Opt

imal

Se

nsor

Su

iteGoo

d Se

nsor

Su

ites

Evol

ved

Sens

or S

uite

s

Mer

it Va

lues

Bac

kgro

und:

Dev

elop

ed u

nder

NA

SA

Spa

ce IV

HM

effo

rtsA

ppro

ach:

•Sel

ects

sen

sors

(typ

e/lo

catio

n) to

opt

imiz

e th

e fid

elity

and

resp

onse

of

eng

ine

heal

th d

iagn

ostic

s•T

arge

ts h

igh

risk

engi

ne a

nom

aly

type

s/cl

asse

s at

det

ectio

n th

resh

olds

and

ass

igns

qua

ntita

tive

sens

or s

uite

val

ue b

ased

on

–Ove

rall

risk

redu

ctio

n–D

iagn

ostic

spe

ed–P

roba

bilit

y of

cor

rect

type

/cla

ss is

olat

ion

•Acc

omm

odat

es v

ario

us ty

pes

of m

odel

s/ph

ysic

al in

puts

Syst

emat

izes

Use

of D

esig

n an

d H

erita

ge E

xper

ienc

e B

ase:

•Use

s cr

itica

l FM

EA

iden

tifie

d m

odes

and

risk

ass

essm

ents

•Con

side

rs s

enso

r res

pons

e an

d sy

stem

/sig

nal n

oise

effe

cts

•Acc

omm

odat

es fa

ult s

cena

rios

from

cor

rela

ted

test

dat

a an

d/or

mod

el s

imul

atio

ns

Con

trols

and

Dyn

amic

s Bra

nch

at L

ewis

Fie

ldG

lenn

Res

earc

h C

ente

r

•Con

trols

and

hea

lth m

anag

emen

t tec

hnol

ogie

s pl

ay a

cr

itica

l rol

e in

mak

ing

“Inte

llige

nt E

ngin

es”a

real

ity.

•NA

SA

has

a w

ell d

efin

ed re

sear

ch p

rogr

am to

adv

ance

th

e st

ate-

of-th

e-ar

t in

airc

raft

engi

ne c

ontro

l and

di

agno

stic

s to

ena

ble:

–S

afer

airc

raft

oper

atio

n th

roug

h en

hanc

ed e

ngin

e ca

pabi

litie

s an

d hi

gher

con

fiden

ce fa

ult d

etec

tion

and

isol

atio

n–

Red

uced

life

cyc

le c

ost t

hrou

gh im

prov

ed d

iagn

ostic

s an

d pr

ogno

stic

s re

sulti

ng in

con

ditio

n-ba

sed

mai

nten

ance

and

in

crea

sed

on-w

ing

engi

ne li

fe.

•A m

ultid

isci

plin

ary

cros

s-or

gani

zatio

nal c

olla

bora

tive

appr

oach

is e

ssen

tial f

or s

ucce

ssfu

l dev

elop

men

t and

de

mon

stra

tion

of In

telli

gent

Eng

ine

tech

nolo

gies

–N

ASA

is w

orki

ng c

olla

bora

tivel

y w

ith in

dust

ry/a

cade

mia

/DoD

•It i

s es

sent

ial t

hat t

he c

ontro

ls a

nd d

iagn

ostic

s ex

perti

se

be in

tegr

ated

ear

ly in

to th

e sy

stem

con

cept

dev

elop

men

t to

ena

ble

syst

em in

telli

genc

e in

the

desi

gn.

Con

clus

ion

Con

clus

ion