Thermal Detection Systems - Geneva International Centre ...€¦ · Thermal Detection Systems Termal Mine Detection ... • material defect analysis by vibrometrical and acoustical

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Dr. Marco Balsi, assistant professor

Salvatore Esposito, graduate student

Department of Electronic Engineering, “La Sapienza” Univ. of Rome

Humanitarian Demining Laboratory, Cisterna di Latina

Thermal Detection Systems

Termal Mine Detection - Marco Balsi -Geneva, GICHD, Sep. 8, 2008

The Humanitarian Demining Laboratory (Laboratorio di Sminamento Umanitario)

promoted by• ‘La Sapienza’ University of Rome• Town Administration of Cisterna di Latina• Tecnologie Solidali, non-profit society

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Humanitarian Demining Laboratory: competences

Department of Electronic Engineering• nonlinear processing, soft-computing, data interpretation,

pattern recognition, learning, data fusion

• embedded systems, DSP, FPGA, sensors

• GPR applications

Department of ‘Technical’ (Applied) Physics• heat diffusion and transmission

Department of Mechanics and Aeronautics• material defect analysis by vibrometrical and acoustical

methods

Department of Structural and Geotechnical Engineering• non-destructive testing of structures and materials

Department of Computer and Systems Sciences• robotics


Mine and ERW detection techniques

established

• visual inspection, manual probing

• metal detectors

• animals

• (mechanical clearance – non properly a detection technique)

being deployed

• GPR

research

• thermal methods

• vibrometrical/acoustical techniques

• X-ray backscattering

• neutron excitation

• laser-induced fluorescence

• nuclear resonance

• gas sensors (electronic noses, and ion mobility spectrometers)

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Thermal Mine and ERW Detection (1)

Passive thermal detection by infrared imaging

from Khanafer and Vafai, 2002



Dynamical thermography

Signal processing: mathematical morphology, PCA, ICA, neural

networks, texture classification, matched filters

Active thermography (microwaves, infrared heaters, ...)

from López Martínez et al., 2004

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Dynamical thermographypro:

• good detection properties (for shallow objects)

• no dependence on metal content

• based on bulk properties rather than material discontinuities (complementary to radar, acoustic)

contra:

• wide-area heating (by sunlight) is relatively slow, so that temperature differences are blurred by heat diffusion;

• wide-area artificial heaters need a large amount of power, that may not be available at operating sites;

• IR cameras are very expensive, maintenance may be difficult at operating sites, and image interpretation is not immediate.

• relatively complicated processing. Needs image interpretation.


Operational Requirements – Research Guidelines

functional

• detection of very-low-metal-content objects

• reliability: data fusion from several physical principles

• automatic labeling of objects, but without hiding decisions fromthe operator (like in medical equipment)

• clarity of warnings (sound, spray of paint...)

• ground referencing (map/GIS)

non-functional

• price

• maintainability, serviceability

• ruggedness

• low-power

special equipment may be useful for laboratory investigation

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New approach

wide-area heating is relatively slow, so that temperature differences are blur-red by heat diffusion;wide-area artificial heaters need a large amount of power, that may not be available at operating sites;

IR cameras are very expensive, maintenance may be difficult at operating sites, and image inter-preta-tion is not immediate.

0 500 1000 1500 2000 25001

1.5

2

2.5

3

3.5

4

4.5

Main indicator: cooling rate


pSand

PYROMETER

d

v

HEATER

Q

Object

C

t

Termal Mine Detection - Marco Balsi - Geneva, GICHD, Sep. 8, 2008

Basic idea: localized heating and sensing

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Experimental setup

PYROMETERS

SAND BOX

HEATERS


Simulations

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Experiments vs. simulations


0 5 0 1 0 0 1 5 0 2 0 0 2 5 0-3

-2

-1

0

1

2

3

Experiments

air

mine

surrogate bees

wax

heater power: 2kW

heater speed 1.5cm/s

sensor lag: 350s

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Artefacts and noise


Data processing and aided decision

0 50 100 150 200 250-3

-2

-1

0

1

2

3

wavelet-based denoising/detrending

generalized orthogonal forward regression

air

mine

surrogate

bees wax

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Feasibility (1)

• complete experiments under way: up to now we can prove reliable detection down to 3cm deep. Appropriate scaling (power, speed) to get to 5cm.

• outdoor experiments being prepared

• scanning time: limited by heating. Currently covering about 2sq.m/hour using a 2kW heater.

• advantages of the proposed system:– low power

– low cost (maintainability, multiple systems in parallel)

– ruggedness

– easy interpretation


Feasibility (2)

• heater on mechanical arm

• sensors on lightweight semi-

autonomous robots

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Data fusion

• use of different physical principles to improve ROC

(false alarms vs. missed detection rate) – sensitivity to different bulk materials, surface discontinuities

• thermal methods good for shallow objects

• GPR better at larger depth, sensitive to dielectric

properties

• acoustical sensitive to stiffness

• data fusion techniques (artificial reasoning, learning

systems) should not override operator


Perspectives

• current year (depending on funding...)

– complete experimental characterization of thermal system

– setup of robotic platforms for outdoor experiments

– experiments for feasibility evaluation of

vibrometrical/acoustical techniques (laser Doppler

vibrometer, microphones)

– simulation of GPR returns, experiments in anechoic

chamber

• future

– data fusion thermal/acoustical

– acquisition of GPR

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Publications (1)

M. Balsi, “A new concept for thermal mine detection by local

heating”, Proc. of International Conference on Requirements

and Technologies for the Detection, Removal and

Neutralization of Landmines and UXO (EUDEM2-SCOT),

Brussels, Belgium, Sep. 15-18, 2003, 424-429.

M. Balsi, M. Corcione, “Thermal detection of buried landmines

by local heating”, International Journal of Systems Science,

Vol. 36, No. 9, 15 July 2005, 589–604.


Publications (2)

M. Balsi, M. Corcione, P. Dell’Omo, “A numerical analysis on

the performance of a novel thermal scanning procedure for

buried landmine detection”, WSEAS Trans. on Systems and

Control 1(2), 2006 ISSN: 1991-8763, 253-261

M. Balsi, M. Corcione, P. Dell’Omo, “Effects of soil non-

homogeneities and climate on the performance ofactive thermal

scanning methods for landmine detection”, WSEAS Trans. on

Systems and Control 1(2), 2006 ISSN: 1991-8763, 267-275

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Publications (3)

M. Balsi, M. Corcione, P. Dell’Omo, S. Esposito, L.

Magliocchetti, “Preliminary experimental validation of a

landmine detection system based on localized heating and

sensing”, SPIE Defense +Security, 16 - 20 March 2008,

Orlando, FL USA - Detection and Sensing of Mines, Explosive

Objects, and Obscured Targets XIII - Conference 6953 -

Proceedings of SPIE Volume 6953

F. Termentini, S. Esposito, M. Balsi, “Experimenting new

technologies for second-level survey in humanitarian demining”,

submitted to Journal of Mine Action


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Thermal Detection Systems - Geneva International Centre ...€¦ · Thermal Detection Systems Termal Mine Detection ... • material defect analysis by vibrometrical and acoustical