asp project presentation

8/2/2019 ASP Project Presentation

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ECE 8423: Adaptive Signal Processing LIFI using Adaptive Filtering

Overview

Introduction of the problem

Discussion of the physics involved

Simulation of input signal

Analysis of this input signal using single input adaptive filter

Analysis of the results of the filter

Performance of uranium detection system

Conclusions and future work


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Uranium

Contaminated Materials

Buildings and equipment used in nuclear powered electricitygeneration plants

Contaminated by several different compounds of uranium

Several uranium oxides; UO2,U3O8,U4O9, UO3

Uranium nitride; UN2

Each compound has unique spectral properties



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Traditional Analysis

Take swaps and chemically analyze

Exposes workers to radiation

Takes several days to get results

Creates more contaminated material

Also, contaminates chemical analysis equipment



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LIFI Imaging

Laser Induced Fluorescence Imaging

Can be done using a robot, no addition risk to workers

Is remote, no additional contamination

Can provide instant results



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LIFI vs. LIF-ICP

EC

EV

LIF-ICP LIFI


In LIF-ICP the wavelength of the laser excitation must match a

particular molecular transition In LIFI several different laser wavelengths can be used for

excitation In LIFI several wavelengths can be used by the detector for

different compounds This provides several channels of data from the scanner as

inputs to the filtering system


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Sources of Noise in LIFI

Laser pulse-to-pulse power variation (statistical)

Variation in the interaction between the laser beam and compounds

(statistical)

Detector performance variation (statistical)

Variation of background material (causal)



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Simulation of input signal

The input signal for the system has been simulated and its generalexpression can be give by,

The signal coming out of the scanner has varying amplitudes

This is due to the roughness of the wall and also due to differentcomposition of material at various points in the wall

Input Signal = Background + Noise + Template


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Simulation of input signal (Contd.)

x(n) = cos2 (2*pi*500*0.00005*x) + 0.2*rand(1,1024) + 0.3*ones (1,5)

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Original Signal x(n)

Samples

x(n)

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Single input adaptive filter:

Block Diagram

y (n) e (n)

z-

f (n)x (n-)

x (n) = d (n)

+-


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Single input adaptive filter:

Algorithm

Initialize adaptation constant & filter coefficients:

f0 = 0

Define input vector x (n) and delay it by , i.e. x (n- )

Compute output vector as:

y (n) = fntxn-

Compute error vector as:

e (n) = d (n) y (n)

Update filter coefficients:

fn+1 = fn + e(n)xn-


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Results & Discussion

200 300 400 500 600 700 800 900 1000-1

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1ErrorPlot forAlpha=0.01, L=20andDelta=20

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Results & Discussion (Contd.)

MSE Uranium

0.01 0.0140093652476 Absent

0.01 0.0149763423956 Present & detected correctly

0.13 0.0303293418513 Present with false alarms


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Performance of Uranium Detector

Several channels of data available from scanner

Variations in the material background will effect only one channelat a time

A positive output from at least two channels will be required tosignify the presence of uranium

False positives from one channel will be ignored unless it occurs

simultaneously with a false positive from another channel


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Conclusion

Reviewed the physics involved in LIFI of uranium

Chose a suitable filtering technique

Analyzed performance of the filter

Analyzed the performance of the LIFI uranium detection system

using the filter



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Future Work

Test filter using additional simulated data

Obtain actual data from LIFI system to test filtering technique

Comparison of additional filtering techniques



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References

DiBenedetto, J., Abbott, R., Capelle, G., Chavez, G., Lutz, S. and Tesar J.,Proceeding of Air and waste Management Association, 1995.

Dimarcq, V., Giordano, P., Cerez, P., Statistical properties of laser-inducedfluorescence signals, Applied Physics B, Vol 59, 135-145 (1994).

Clarkson,C. M., Optimal and Adaptive Signal Processing, Boca Raton: CRCPress, 1993.

ECE-8423: Class notes



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Questions & Answers

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