3D Image Reconstruction From Truncated Helical Cone Beam Projection Data - A Linear Prediction Approach

With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence can give exact reconstruction. The theoretically exact helical cone-beam reconstruction algorithm proposed by Katsevich is a breakthrough and has attracted interest in the 3D reconstruction using helical cone-beam Computed Tomography.In many practical situations, the available projection data is incomplete. One such case is where the detector plane does not completely cover the full extent of the object being imaged in lateral direction resulting in truncated projections. This result in artifacts that mask small features near to the periphery of the ROI when reconstructed using the convolution back projection (CBP) method assuming that the projection data is complete. A number of techniques exist which deal with completion of missing data followed by the CBP reconstruction. In 2D, linear prediction (LP)extrapolation has been shown to be efficient for data completion, involving minimal assumptions on the nature of the data, producing smooth extensions of the missing projection data.In this paper, we propose to extend the LP approach for extrapolating helical cone beam truncated data. The projection on the multi row flat panel detectors has missing columns towards either ends in the lateral direction in truncated data situation. The available data from each detector row is modeled using a linear predictor. The available data is extrapolated and this completed projection data is backprojected using the Katsevich algorithm. Simulation results show the efficacy of the proposed method.

Structural Health Monitoring (SHM) Using Strain Gauges, PVDF Film and Fiber Bragg Grating (FBG) Sensors: A Comparative Study

The term Structural Health Monitoring has gained wide acceptance in the recent pastas a means to monitor a structure and provide an early warning of an unsafe conditionusing real-time data. Utilization of structurally integrated, distributed sensors tomonitor the health of a structure through accurate interpretation of sensor signals andreal-time data processing can greatly reduce the inspection burden. The rapidimprovement of the Fiber Bragg Grating sensor technology for strain, vibration andacoustic emission measurements in recent times make them a feasible alternatives tothe traditional strain gauges transducers and conventional Piezoelectric sensors usedfor Non Destructive Evaluation (NDE) and Structural Health Monitoring (SHM).Optical fiber-based sensors offers advantages over conventional strain gauges, PVDFfilm and PZT devices in terms of size, ease of embedment, immunity fromelectromagnetic interference(EMI) and potential for multiplexing a number ofsensors. The objective of this paper is to demonstrate the feasibility of Fiber BraggGrating sensor and compare its utility with the conventional strain gauges and PVDFfilm sensors. For this purpose experiments are being carried out in the laboratory on acomposite wing of a mini air vehicle (MAV). In this paper, the results obtained fromthese preliminary experiments are discussed.

Discrimination of Nuclear Grade Steel Samples Subjected to Different Heat Treatment Procedures Based on Acoustic Emission (AE) Data Profiling at Crack Initiation

The present work is an attempt to study crack initiation in nuclear grade, 9Cr-1Mo ferritic steel using AE as an online NDE tool. Laboratory experiments were conducted on 5 heat treated Compact Tension (CT) specimens made out of nuclear grade 9Cr-1Mo ferritic steel by subjecting them to cyclic tensile load. The CT Specimens were of 12.5 mm thickness. The Acoustic emission test system was setup to acquire the data continuously during the test by mounting AE sensor on one of the surfaces of the specimen. This was done to characterize AE data pertaining to crack initiation and then discriminate the samples in terms of their heat treatment processes based on AE data. The AE signatures at crack initiation could conclusively bring to fore the heat treatment distinction on a sample to sample basis in a qualitative sense.Thus, the results obtained through these investigations establish a step forward in utilizing AE technique as an on-line measurement tool for accurate detection and understanding of crack initiation and its profile in 9Cr-1Mo nuclear grade steel subjected to different processes of heat treatment.