Semester

Fall

Date of Graduation

2006

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Lane Department of Computer Science and Electrical Engineering

Committee Chair

Powsiri Klinkhachorn.

Abstract

Energetic ion analyzers and mass spectrometers commonly produce electronic pulses whose amplitude and time depend on the energy, mass, and direction of an incoming ion. Analysis of the nanosecond scale timing and amplitude of these approximately 10-12C charge pulses has required complex, fast analog electronics. Given recent advances in digital electronics, it seems likely that converting much of the analysis to digital form will result in a simpler, lower cost, and lower power electron package. The aim of the thesis is to develop an algorithm to fit a 500 ns long noisy voltage pulse obtained from an ion analyzer to a known pulse shape, and implement it in digital electronics. The measured pulse will have an unknown amplitude, unknown starting time, and also, added random noise. The thesis includes derivation of the algorithm to least-square fit a noisy pulse to determine its height and starting time. A ratio of two pulse heights is used to identify the ion. The fitting process has been implemented using FIR filters.;The algorithm has been implemented in an FPGA which fits pulses sampled by a high-speed 8-bit ADC at 50ns sampling time. Simulation tests have been carried out using Matlab to test the accuracy of the algorithm in finding its height and starting time by varying the noise level in the signal. Results show that the algorithm can detect the pulse even when the SNR in the signal is 3dB or better, and it can detect the starting time of the pulse to within 6ns when the SNR in the signal was approximately 21dB. The pulse height found varies by just 20% when the SNR in the signal is varied from 25 to 7dB.The present algorithm implementation in hardware determines only the amplitude of the pulses. A position sensitive anode board was used to generate the pulses. The results show that the implementation can identify the ion position based on the amplitude of the pulses generated, to typical accuracy of 1%. Techniques for future improvements are also discussed.

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