nexsense: developing a portable chemical detector using ... · nexsense: developing a portable...

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Nexsense: Developing a Portable Chemical

Detector Using MathWorks Toolsets

Alison Lucie & Ross McLaren

7th October 2014

© 2014 Selex ES Ltd – All rights reserved

In the next 30 minutes we shall talk about:

– Who we are

• Who are Selex ES?

• What is Nexsense?

– The technology behind Nexsense

• How Nexsense works

• A History of the Development

– An overview of the development process

• Traditional route and why this wasn’t the way to go

• The Nexsense development route

• The key advantages behind this

• Verifying the process

Airborne and Space Systems We partner with our Customers to deliver

world class, tailored and proven airborne

integrated systems, sensors and training

for military and security ISR/ISTAR

manned and unmanned operations

through a successful, customer focused

business


Key Capabilities Multi-platform, world class ISR/ISTAR systemsScalable mission systems, AESA and M-scan multimoderadar, electro-optical turrets, navigation aids, lightweightW/ELINT systems, CNI.

Complete, independent UAS capabilityMission systems, platforms, ground control stations, Battle-labs, training and paid by the hour services.

Combat proven electronics for fixedand rotary wingFixed and repositionable AESA and M-scan radar, complete integrated electronic warfare systems, lightweight high performance DIRCM systems, IRST, high power targeting laser.

Multi-mission highly realistic trainingNetworked, intelligent synthetic environments withmulti-platform interaction for advanced training.

Avionics

High performance computers, human to machine electronic controls

and displays, internal and external lighting systems.

Earth observation and precise positioning systemsMultispectral sensors, star trackers, power equipment, atomic clocks and solar panels.


• Hand held chemical detector, capable of the detection and

identification of a range of toxic industrial chemicals.

• FAIMS - “Field Asymmetric Ion Mobility Spectrometry”

• (a.k.a. HiFAWS – “High Field Asymmetric Wave

Spectrometry)

• Exploits high-field mobility vs. field strength relationship

• Initially developed in FSU and first reported in mid 1990s

• Laboratory-only technique until (relatively) recently

• Advantages over IMS

• Continuous operation (rather than shuttered)

• improved response time & sensitivity

• Can be readily miniaturised – same scaling laws do not

apply

• Pseudo-orthogonality - potential for superior selectivity

Nexsense – Handheld Chemical Detector


Development History

2008

2009

2007

20102011-

Owlstone Tourist:Data gathering & technology familiarisation

First prototype:Self contained sensor, offline data processing

‘Ruggedised’ prototype:Embedded data processing & local display.‘Handheld’ prototype:

Corona discharge ionisation

‘Productionised’ Nexsense


• FAIMS Principles

• Apply asymmetric rectangular waveform across electrodes (perpendicular to flow)

– “Dispersion Field”

• Typically RF (27.12MHz in our application)

• Typically >20kV/cm (up to ~100kV/cm in our application)

– Ions displaced towards top electrode during high field portion

– Ions drift back towards bottom electrode during low field portion

– However, for high fields the amount of drift will be different (non linear K)

• Net drift towards top/bottom electrode

• Drift varies with amplitude of waveform

• Can be corrected by application of DC component to asymmetric waveform – “compensation voltage”

Time

Vo

lts

Background


Background

• FAIMS Principles of Operation

– Ions are swept through filter electrodes which are driven with an asymmetric waveform.

– The ions oscillate through the filter moving a different speeds during the high field period

compared with the low field period

– Compensation voltage added to dispersion voltage to focus ions onto detector

0KK

0KK

T

Ion

detector

-3 -2 -1 0 1 2 3CV

Ion

Cu

rren

t -ΔK +ΔK


Interpretation of Data

CV

DV

Positive

-6 -4 -2 0 2 40

10

20

30

40

50

60

-6 -4 -2 0 2 4 6-5

0

5

10

15

20

25

30

35

CV

Ion

Cu

rre

nt

-6 -4 -2 0 2 4 6-1

0

1

2

3

4

5

6

7

CV

Ion

Cu

rre

nt

-6 -4 -2 0 2 4 6-0.5

0

0.5

1

1.5

2

2.5

CV

Ion

Cu

rre

nt

Sweep contains peaks with Gaussian

cross-section, coefficients:~

Parameter Information

Peak Amplitude Concentration

Peak Width Low field mobility (K0)

Peak Position Differential mobility

Background


Background

• Practical Implementation

– Silicon MEMS device in ceramic package

– Multiple electrode channels arranged in parallel


The 10 TICs


Processing Architecture


‘Traditional’ Development Route (starting point)


‘Traditional’ Development Route - Issues


Where Algorithms Fit Into the Development Route (end point)


• Visualising the data that is to be analysed:• Better understanding of how the data is

captured• Exposed unknown pre-processing chain in

data capture

• Easy Re-use• Visualisation tool developed for sensor

directly useable in MATLAB for fast data

inspection

• Simple to Update• Add functionality as and when identified

• Carved the way• Simple to do, indicated should be simple

process for adding algorithms onto units

directly with MATLAB tools

Visualisation

Data Analysis

Advantages


• Developing & Deploying Algorithms using

the same tools:• Rapid Prototyping

• Access to Toolboxes

• Minimise Human Error• No misinterpretations in code handover

• Each version of code is written once, in

MATLAB

• Simple Development & test cycle• One line of code to build DLL

• Same team to develop code and test

deployment (no handover)

• Easy to Expand• Once the process is tested and verified, it

is easy to upgrade with new algorithm

releases – expand and improve product

capabilities quickly

Advantages


• Suite of M-files to a DLL • One line of code to generate DLL

• Move DLL to sensor, ready to test

• Very quick and simple

• Why DLL?• Why not use MATLAB Coder – verifying the generated C code would easier?

• Use of other toolboxes (e.g. wavelet toolbox)

• Legacy reasons (r2006b)

Practicalities – Deployment Method


• MATLAB Functions• Profiler for finding bottle-necks

• Code Analyser for static analysis

• Check code for McCabe complexity (code needs to be testable)

• Unit Testing• Exercise all paths in the code

• Verify code changes

• Generate DLL• Verbose version created

• Can then verify internal test points with original code

• Acceptance Testing• As part of full system test procedure.

• Detect & Identification needs to be successful => code is working as

expected

• Deploy and Deliver• With documentation formed by all the above stages

Practicalities – Verification


Rapid Routes to Recovery When Things Go Wrong


• Nexsense chemical sensor was developed in a relatively short time period

• Multiple threat identification capability on a hand-held device

• From first built prototype to first production-standard sensor delivered in under a

year

• Use of the MATLAB toolset enabled the demanding schedule to be met

• Rapid development of algorithms using various toolsets (e.g. image processing,

wavelets)

• Rapid deployment to DLL avoided long-lead times for software hand-over (no need

to re-write code)

• Enabled fast re-iterations and testing

• Verification & Validation framework established

• When things went wrong, there was a good architecture in place to enable a fast and

effective recovery plan

Summary

THANK YOU FOR YOUR ATTENTION

nexsense: developing a portable chemical detector using ... · nexsense: developing a portable...

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