• Non ci sono risultati.

ANALYSIS OF DIESEL ENGINE COMBUSTION USING IMAGING AND BLIND SOURCE SEPARATION

N/A
N/A
Protected

Academic year: 2021

Condividi "ANALYSIS OF DIESEL ENGINE COMBUSTION USING IMAGING AND BLIND SOURCE SEPARATION"

Copied!
35
0
0

Testo completo

(1)

ANALYSIS OF DIESEL ENGINE COMBUSTION USING IMAGING AND BLIND SOURCE

SEPARATION

K. Bizon1, S. Lombardi1, G. Continillo1,2, E. Mancaruso2, B. M. Vaglieco2

1 Università del Sannio, Benevento, Italy

2 Istituto Motori C.N.R, Naples, Italy

(2)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(3)

OBJECTIVE OF THE WORK

First attempt of application of independent

component analysis (ICA) to 2D images of combustion- related luminosity acquired from an optically accessible Diesel engine

Identification of the leading independent structures (independent components, ICs) and:

study of the transient behavior of the flame during a single cycle

analysis of the cycle-to-cycle variability

Assessment of the alternative decompositions (e.g.

proper orthogonal decomposition, POD)

(4)

INTRODUCTION

The fast development of optical systems has made

available measurements of distributed in-cylinder variables but the measurements interpretation is not always easy due to the huge amount of data, and to the variety of

coupled phenomena taking place in the combustion chamber

This has lead to the increasing interest in the application of sophisticated mathematical tools, e.g. proper orthogonal decomposition (POD) has become a popular reduction and analysis tool. It has contributed to the knowledge of many physical phenomena, but it cannot separate

independent structures, i.e. all POD modes contain some element of all structures found in all of the fields

Alternative decompositions can be considered, e.g.

independent component analysis (ICA) can be expected

to provide a more powerful insight with respect to POD

(5)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(6)

EXPERIMENTAL ENGINE

Direct injection four-stroke diesel engine with a single cylinder and a multi-valve production head

The research engine features only two valves and utilizes a classic extended piston with a UV grade crown window

Single cylinder diesel engine

Engine type 4-stroke

Bore 8.5 cm

Stroke 9.2 cm

Swept volume 522 cm3

CC volume 21 cm3

Compression ratio 17,7:1 Common rail injection system Injector type Solenoid driven Nozzle Microsac, single

guide Holes

number 6

Cone angle 148°

Hole

diamete r

0.145 mm

Rated flow 400 cm3/30 s

(7)

OPTICAL SETUP

High-speed digital complementary metal oxide semiconductor (CMOS)

camera, controlled by a trigger signal generated by a delay unit linked to

the engine encoder, in combination with a 45° UV/visible mirror located

inside the piston

(8)

EXPERIMENTAL PROCEDURE & RESULTS

Engine speed of 1000 rpm, continuous-

mode operation, using commercial Diesel fuel

Injection pressure fixed at 600 bar and no EGR

Typical CR injection strategy of pre, main and post injections (PMP) starting at -9°, -4° and 11° CA with duration of 400, 625 and 340 μs

Cylinder pressure recorded at 0.1 CA°

increments by means of a pressure transducer

ROHR calculated using the first law, perfect gas

approach

CMOS high-speed camera: frame rate of 4 kHz and exposure time of 166 μs

888 images of the in-cylinder luminosity field, collected from -4° to 30.5° CA, with CA increment of 1.5°, over N= 37

consecutive fired cycles

The original spatial mesh of 529×147 is clipped to 120×120 pixels framing the combustion chamber

- 4 0 - 3 0 - 2 0 - 1 0 0 1 0 2 0 3 0 4 0

C r a n k a n g l e [ d e g r e e s ] 0

1 0 2 0 3 0 4 0 5 0 6 0

Combustion pressure [bar]

0 1 0 2 0 3 0

Drive current [Ampere]

0 4 0 8 0 1 2 0 1 6 0

Rate Of Heat Release [kJ/kg]

(9)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(10)

POD VS. ICA

Proper orthogonal decompositon

Extracts dominant structures -

orthonormal and optimal in the L2 sense

Relatively simple eigenvalue problem to solve

Fields of application: turbulent flows, model reduction, image processing, PIV data & flame luminosity from SI &

Diesel engines

Independent component analysis

Extracts a set of mutually independent signals from the mixture of signals, i.e.

permits to separate the data into underlying

informational components

Optimization problem

maximizing some measure of the independence

Fields of application:

neuroimaging, spectroscopy, combustion engines

(separation of vibration

sources)

(11)

POD VS. ICA

Proper orthogonal decompositon

Extracts dominant structures -

orthonormal and optimal in the L2 sense

Relatively simple eigenvalue problem to solve

Fields of application: turbulent flows, model reduction, image processing, PIV data & flame luminosity from SI &

Diesel engines

Independent component analysis

Extracts a set of mutually independent signals from the mixture of signals, i.e.

permits to separate the data into underlying

informational components

Optimization problem

maximizing some measure of the independence

Fields of application:

neuroimaging, spectroscopy, combustion engines

(separation of vibration

sources)

(12)

Given:

: random vector of temporal mixtures

: temporal (mutually independent) source signals

The mixing model can be written as:

If then matrix is invertible and the model can be rewritten as:

The ICA problem consist of calculating such that is an optimal estimation of

ICA problem can be solved by maximization of the statistical independence of the estimates

ICA: DEFINITION

  t    x t

1

  , , x t

m

   

x

  t    s t

1

  , , s t

n

   

s

x = As

n mA

s = Wx

1

W = A y = Wx

s

y

(13)

ICA: APPROACHES

Maximization of nongaussianity (“nongaussian is independent”)

Maximization of kurtosis (e.g. a fast-point algorithm using kurtosis called FastICA)

Maximization of negentropy (normalized version of differential information entropy)

Minimization of mutual information

Maximum likelihood estimation

Tensorial methods

Nonlinear decorrelation and nonlinear PCA

(14)

ICA: FASTICA ALGORITHM

FastICA algorithm maximizes non-gaussianity by means of a gradient method. The (non-)gaussianity is estimated by the absolute value of kurtosis defined as:

The algorithm is employed on centered (having zero mean) and whitened data (uncorrelated and have unit variances), i.e.:

- raw data

- POD eigenvectors

- POD eigenvalues (on the diagonal)

If the number of ICs is smaller than the number mixtures, the data can be reduced during the whitening using

leading POD modes

   

1 2 T

E

  

x = D E x x

   

4

  

2

2

kurt yE y  3 E y

xE D

n m

(15)

ICA: SEPARATION OF IMAGE MIXTURE

sources independent

components POD modes

mixtures m

ixi n g

se

p

ar

at

io

n

(16)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(17)

CRANK ANGLE RESOLVED MEASUREMENTS

PMP at -9°, -4° and 11° CA

first luminous spots due to ignition of the preinjected fuel

main injection combustion

combustion present on all jets and in the vicinity of the chamber wall

combustio n zone moves towards the bowl

wall

simultaneous ignition of postinjection

jets

maximum of post combustion

luminosity

Images of combustion luminosity for multiple injections in a cycle, at several crank angles

(18)

ICA: CYCLE 8

y

1

y

2

(19)

ICA: CYCLE 9

y

1

y

2

(20)

ANALYSIS OF IC S AND THEIR COEFFICIENTS

2° CA 5° CA 9.5° CA 2° CA 5° CA 9.5° CA y

1

: combustion along

the fuel jets; swirl motion

y

2

: combustion near the chamber walls

y

1

y

2

y

1

y

2

(21)

ICS VS. ENGINE PARAMETERS

SOC of PMP:

–4°, 1° & 14°

CA main inj.

post inj.

maximum luminosity of the regular combustion process near the fuel jets of the main and post

injection

3.5° CA 17° CA

8° CA

(22)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(23)

CYCLE-TO-CYCLE VARIATIONS

Not all jets burn with the same flame behavior; during combustion development flames are unevenly distributed along the jets’ axes

Post injection starts in a partly burning environment, where the irregular peripheral combustion influences post-injection ignition

2° CA

3.5° CA

14° CA

18.5°

CA

main injection combustion

end of main combustion

; post injection

post injection combustion

(24)

3.5°CA

ICA separates the mean combustion luminosity at each CA

from the irregular flame structure related to cycle variability

(25)

14°CA

Separation is worse when the variability is higher, i.e. at the

end of main combustion when the flames move randomly near

the bowl wall

(26)

18.5°CA

Again, the separation is better when the cyclic variability is

lower, i.e. for the CA characterized by regular combustion

typical of jet burning

(27)

ICS VS. ENGINE PARAMETERS

a

1

peaks where an irregular combustion process takes place (less effective separation) and is low when the burning along the jets dominates

CV of a

2

is at least one order of magnitude higher than the CV of a

1

, confirming that strong deviations from the ideal combustion process are located near the bowl wall

pilot injection

fuel burning in the centre of the bowl

regular burning of the main &

post injection fuel along the jet directions

random flames near the

bowl

irregular end of combustion

(28)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(29)

ICA VS. POD

Independe nt

component s

POD modes

Negentropy, i.e. normalized differential information entropy, measures the

amount of information and is always higher for ICA than for POD; it is estimated as:        

     

1 2 1 2

2 2

3

;

1 1

12 48 kurt

ICA POD

J J y J y J J J

J y E y y

 

   

 

(30)

ICA VS. 1 ST AND 2 ND MOMENT

Analysis of cycle variations (but not crank angle resolved

measurements!) similar conclusions for the first two statistical moments (mean & standard deviation)

Here the "signals" were, in most cases, already spatially separated

Independe nt

component s

1

st

and 2

nd

moment

Crank angle resolved measurments

Cycyle-to-cycle variations

(31)

OUTLINE

Introduction

Experimental setup & procedure

Independent component analysis

Analysis of crank-angle resolved measurements

Cycle-to-cycle variations analysis

Comparison with other methods

Summary & conclusions

(32)

SUMMARY & CONCLUSIONS

A first attempt of the application of ICA to luminosity image data collected in an optical engine was done

Two independent components were found related to:

combustion along the fuel jets presenting low variability over the cycles

near the bowl walls – highly variable; this confirms quantitatively that strong deviations from the ideal combustion process are located near the bowl walls

The analysis is fast and reliable - a single computation takes less than 0.1 s on a standard sequential single processor

Benefits of ICA can be much higher than this simple application example shows. Based on the demonstration case, more

complex data can be analyzed, and what was presented here

is a first and convincing example of how ICA works in an

engine context

(33)
(34)

From the movie

L’Atalante by Jean Vigo (1932)

Dita Parlo (born as Gerda Olga Justine

Kornstädt on 4th Sept 1908 in Szczecin,

Poland

Riferimenti

Documenti correlati

Prenatal ultrasound diagnosis of FHUFS is feasible given that its most consistently reported findings, namely femoral hypoplasia and major facial anomalies, can be recognized in

For an autocatalytic reaction to take place in a BATCH reactor, some minimal amount of product P must be present to make sure that the reaction rate is not

The combustible gases supplied to the chamber of the pulverized coal-fired boiler can be used to stabilize coal dust combustion process at low boiler load. They can replace

They stated that the addition of butanol with a percentage of up to 20% to the biodiesel – diesel fuel blend resulted in a tolerable change in the engine performance,

The theoretical basis of the process of coal self-heating control and definition of the form of the heat emitting source is detected in the 1970s steady relationship between

Within this unit, on the basis of the assumed characteristics of the hourly fuel consumption for the selected engine in the function of the rotational speed and torque,

Effect of piston bowl geometry on combustion and emission characteristics of biodiesel fueled diesel engines, Fuel 120(2014) 66-73. Jinxiang,