* Work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Security, LLC, Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344

Agenda

• Introduction to NIF and automatic alignment

• Control system architecture

• Coordination and scaling

— 3,800 closed loop adjustments using 12,000 devices

— Management of shared laser components

• Image processing

— Algorithm robustness in a laser environment

— Subpixel accuracy

— Reliability and off-normal image detection

NIF concentrates all the energy in a football stadium-sized facility into a mm3

Beampath Movie

In an analogy to baseball, this requirement is like hitting the strike zone with a pitch thrown from 350 miles away

Beams are aligned along NIF’s 500-meter path to focus on the mm-size target within 10 microns

Target Alignment Sensor

Alignment uses sensors and actuators within Line Replaceable Units

Symmetry & nomenclatureNational Ignition Facility

ArchiveVerify

ShotShot Preparation

Amplifier cooling Shot

Fire pre-amplifier

Archive

30-m

Automated Shot Cycle

• Input shot goals from laser physics model

• Perform automatic alignment

• Configure diagnostics and laser settings

• Conduct countdown (SW: 4-m, HW: 2-s)

• Assess shot outcome and archive data

20-m

Fire main amplifiers

2-s

4 hours

Shot

ICCS shot cycle automatically aligns, fires and diagnoses laser shots every 4 hours

Automatic Alignment

30-m

The automatic alignment system compensates for optical system drift

ISP cw @ISP 032603

-6.00E+00

-5.00E+00

-4.00E+00

-3.00E+00

-2.00E+00

-1.00E+00

0.00E+00

1.00E+00

2.00E+00

3.00E+00

4.00E+00

5.00E+00

0.00 100.00 200.00 300.00 400.00 500.00 600.00 700.00

Minutes from starting time

Po

intin

g e

rro

r (u

R)

x error

y error

Required Tolerance

Pointing error at the Input Sensor

5

4

3

2

1

0

-1

-2

-3

-4

-5

-6 0 100 200 300 400 500 600 700

Minutes from starting time

Micro radians

Requirements led to significant technical challenges

• Minimize operator effort— Situational awareness— Manual controls

• Deliver subpixel accuracies

• Algorithms tolerant to— Varying light levels— Laser diffraction effects— Equipment anomalies

• Reject off-normal images

• Rapidly align 192 beams— Parallel operation— Computational resources— Many devices are shared

Single operator oversees Beam Control

Replicated bundles are activated by starting new processes in the database

The bundle architecture assures full-scale performance of the alignment control system

SupervisoryLayer

Front-EndLayer

ReplicatedBundles

BundleCoordinator

AutomaticAlignment

Bundle 1

VideoSensors

Beam Control

ActuatorControls

BundleCoordinator

AutomaticAlignment

Bundle 24

VideoSensors

Beam Control

ActuatorControls

BundleCoordinator

AutomaticAlignment

Target

VideoSensors

Beam Control

ActuatorControls

Shot Sequencer

Process distribution example for beam control

Common Control System Bundle 11 Controls

ConfigurationLogging

ArchivingReservations

etc.

ShotDirector

Beam ControlSupervisor

AlignmentController

B11Actuators

VideoController

B11Sensors

B11Timing

LINUXCluster

CORBA

B11 Automatic Alignment

B11 Manager

The alignment system maintains the beam within the optical clear aperture

Spatial Filter(Low Pass)

PinholeCentering

PointingMotorized Mirrors

LaserBeam

Lens Beam Tube

Centering definition — Translates beam position without affecting pointing— Sensor configured to near-field mode

Pointing definition— Adjusts angle of propagation without affecting centering— Sensor configured to far-field mode

Generic control loop flow diagram

Done

Adjust Optic

Setup Reference

Locate Reference

Acquire Image

Setup Beam

Locate Beam

Acquire Image

Centering Alignment Principle

The image of the beam reticule (circle) is adjusted to the midpoint between the reference reticules (squares)

Beam Center

CCD Camera

Light Source

ImageAcquisition

ActuatorControls

Network

Automatic

Alignment

Reference Reticule Mask

Motorized Turning Mirrors

Beamline

Beam Reticule Mask

Fixed SamplingMirror

Firewire

Near-field camera image

Control

Far-field camera image

Pointing Alignment Principle

The source sub-image is aligned to the center of the pinhole shadow

Pinhole

CCD Camera

Image Acquisition

Network

Automatic Alignment

ActuatorControls

PinholeLens

Light Source Pinhole

Illuminator

Motorized Turning Mirrors

Firewire

Managers coordinate resources and activities

• Supervisor — Manual controls— Status

• LINUX Cluster— Image processing— Self-leveling

• Segment Manager— Alignment plans— Loop definitions— Sequence control

• Component Manager— Device sharing— Throughput optimization

Bxx Automatic Alignment

Video Sensors

Actuator Devices

Beam Control Supervisor

Segment Manager

Component Manager

Database

- Alignment Plans

- Segments, Loops

- Components

- Devices

LINUXCluster

NIF’s beamline architecture was designed to permit alignment of segments in parallel

Reference Adjust

Optic

Beam

1 minute

CheckSetup Setup LocateLocate

A Segment Manager

Alignment Plan 1

Control Loop 1Control Loop 2…

Loop Timing

PreamplifierSegment Manager

Main LaserSegment Manager

1 Pulsed Source

1 CWSource

1 CW Source

3CW Source

Camera

Camera

Camera Camera

Target AreaSegment Manager

A NIF Beamline

The Segment Manager executes alignment plans efficiently to achieve the required performance

• Component Managers— Orchestrate setting up laser configurations— Contain multiple device grouping called

mediated components

• Mediated components— Manages device positions— Can include other mediated components— Reservations lock the configuration

• Task queues— Requests wait until devices become available— Deadlocks eliminated by enforcing priority— Queue optimization actively minimizes

required movements

One out of every four devices in the alignment system are shared

The Component Manager optimizes task processing throughput

The main laser sensor is a mediated component

Image processing must always be reliable

• Precision and accuracy required to 0.3 pixels

• Robustness is challenged by— Gradient illumination— Noise— Diffraction effects— Defocus— Magnification

• Discard off-normal images— Extraneous blobs— Saturation— Clipping

… while still being robust to varying laser conditions !

Example of a Clipped Image

Many processing algorithms are used …

Crystal reflection

Gaussian Beam

Weighted Centroid

Glass Grid

Crosshair Grid

Crosshair Grid

Hough Transform

Fiber Source Dark Stop

Pinhole

Template Match

Reticule

Matched filter

Shot Mask

Spiral Search

Corner Cube

Images undergo three processing steps

Discard Off-normal Images

Calculate Position

Check Position Uncertainty

Good Bad

Image quality is measured by estimating algorithm uncertainty

• Uncertainty Definition

— Instability in the position determination

— Obtained by varying either thresholds or noise

• Threshold-based method (e.g. weighted centroid)

— Image processed with thresholds at 10 different levels

— Delivers subpixel accuracy as a byproduct

— Uncertainty: variability of the position estimates

• Noise-based method (e.g. matched filter)

— Monte Carlo model of known uncertainty is constructed for the image using prescribed amounts of noise

— Uncertainty: estimated from the model based on noise present in the input image

Low uncertainty confirms a high quality input image, with confidence that algorithm results can be trusted

Example of sub-pixel position estimation confirms accuracy is within tolerance

Gaussian Image

0 Distance (p) 76

Inte

nsity

110%

90%

Lineout

1 pixel (x)

Tolerancelimit

1 pixel (Y)

Centroid Plotted at Various Thresholds

Poor laser wavefront prohibits a successful alignment outcome in this uncertainty example

Defocused Gaussian Image

10%

90%

Lineout

5x5 (x,y) pixel grid

Centroid Plotted at Various Thresholds

Tolerancelimit

OUT OF TOLERANCE!OUT OF TOLERANCE!

High uncertainty halts the automatic alignment process

Architectural enhancements achieved the required performance

0

10

20

30

40

50

60

70

80

90

100

2000 2002 2004 2006 2008 2010 2012

4 beam sequentially aligned to Target Chamber

Year

Required alignment time

Target camera bottleneck

Alignment Time(Minutes)

Sequential Mediated

Full automation of all 192 beams is moving rapidly toward completion

0

500

1000

1500

2000

2500

3000

3500

4000

2000 2002 2004 2006 2008 2010 2012

1/3

of

1 b

eam

1/2

of

1 b

eam

4 b

eam

s

4 b

eam

s

2/3

of

8 b

eam

s

2/3

of

16 b

eam

s

2/3

of

96 b

eam

s

192

bea

ms

144

bea

ms

Year

Number Control Loops

We’ve exceeded performance goals with a automatic system that is robust and reliable

Remaining work extends automation of all 192 beams to the target for ignition experiments beginning in 2010

NIF Automatic Alignment

Video Sensors

Actuator Devices

LINUXCluster

Beam Control Supervisor

Segment Manager • Sequence

Component Manager

Database

- Alignment Plans

- Segments

- Loops

- Components

- Devices

Queues

Queues

Many processing algorithms are used …

Crystal Reflection

a) Weighted Centroid

Crosshair Grid

b) Hough Transform

Dark Stop

c) Template Match d) Matched Filter

Shot Mask

5x5 (x,y) pixel grid

Tolerancelimit

OUT OF TOLERANCE!OUT OF TOLERANCE!