Digital Pulse Shape Discrimination Methods for Triple-layer Phoswich Detectors Using Wavelets and Fuzzy Logic

Digital Pulse Shape Discrimination Methods for Triple-layer Phoswich Detectors Using Wavelets and Fuzzy Logic
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Total Pages : 232
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ISBN-10 : OCLC:234077138
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Book Synopsis Digital Pulse Shape Discrimination Methods for Triple-layer Phoswich Detectors Using Wavelets and Fuzzy Logic by : Siavash Yousefi

Download or read book Digital Pulse Shape Discrimination Methods for Triple-layer Phoswich Detectors Using Wavelets and Fuzzy Logic written by Siavash Yousefi and published by . This book was released on 2009 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: A two-channel data acquisition system for simultaneous detection and discrimination of beta particles and gamma rays has been developed. Each channel measures and analyzes the input pulses resulting from the absorption of radiation in the layers of the detector. The detector is a triple-layer phoswich (phosphor sandwich) scintillation detector followed by a photomultiplier tube (PMT). The PMT amplifies the photons and converts them into an electric signal. The signal is digitized and sent to the host computer for further processing. Two new digital algorithms based on Fuzzy Logic and on the Continuous Wavelet Transform have been developed and are discussed in this thesis. In the first method, a de-noising algorithm based on the Wavelet Transform is implemented to reduce the effect of noise introduced by the analog channel and by the photomultiplier tube. Three new timing features are extracted and given as input to a fuzzy interface system. The main goal of fuzziness in a data set is to reduce the system complexity and to provide a model that allows for approximate results. Compared to the method which was originally implemented for this detector, the fuzzy algorithm shows a better performance in separating beta and gamma spectra, especially at high energies. Also, absorption in multiple layers is detected more efficiently. The second algorithm is based on the Continuous Wavelet Transform. The novelty of this method consists in using scale-domain features. Since the output pulse shape of the photomultiplier tube is a non-stationary signal, conventional Fourier methods are not efficient for analyzing these signals and most of the existing pulse shape discrimination methods use time-domain features. Therefore, a time-frequency space is better suited to analyze these non-stationary signals. This method shows better performance over existing time-domain methods in terms of robustness to noise and reliability. The simultaneous detection of beta particles and gamma rays has several applications (for instance detection of underground nuclear explosions). The methods presented in this thesis could also be used in alpha/beta/neutron/gamma discrimination systems for cancer diagnosis and treatment.


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