Single-Sided Noinvasive Inspection of Multielement Sample Using Fan-Beam Multiplexed Compton Scatter Tomography

As aircraft age, corrosion forms upon unobservable surfaces, particularly at the junction of the sheet aluminum and the steel rivets used to attach the sheets to the airframe, degrading the aircraft s airworthiness. Previous research developed a noninvasive technique for the evaluation of the material composition of aluminum surfaces, utilizing the information encoded in the energy spectra of Compton-scattered gamma emissions. The spectra are gathered by a six-element, high purity germanium detector array. A, first principles, deterministic computer code is used to reconstruct a two-dimensional map of the electron density of aluminum samples. Previous efforts, to image pure aluminum samples, suffered from: artifacts at sample boundaries, inaccurate determination of electron density values, and excessive sampling times of 41-111 hours. In this work images, of an oxidized aluminum sample including an iron insert meant to simulate a vertical two-dimensional slice through a steel rivet in an aluminum surface, have been reconstructed. Sample boundaries have been determined and included in reconstruction. Their inclusion in image reconstruction has reduced the artifacts on the edges of the sample and improved the accuracy of the values for electron density. An image, post-processing code has been implemented utilizing a priori knowledge of the electron densities of iron, aluminum, and air, to increase the accuracy of the density values determined by the reconstruction code. In addition, opening the field of view of the detector array has increased the throughput of the detectors, increasing peak measurements by approximately 900 counts per channel.Air Force Inst of Tech Wright-Patterson AFB OH School of Engineering and Management is the author of 'Single-Sided Noinvasive Inspection of Multielement Sample Using Fan-Beam Multiplexed Compton Scatter Tomography', published 2000 under ISBN 9781423527176 and ISBN 1423527178.