Limited view X-ray tomography for dimensional measurements

G.A Jones,P Huthwaite

doi:10.1016/j.ndteint.2017.09.002

Abstract

The growing use of complex and irregularly shaped components for safety-critical applications has increasingly led to the adoption of X-ray CT as an NDE inspection tool. Standard X-ray CT methods require thousands of projections, each distributed evenly through 360∘ to produce an accurate image. The time consuming acquisition of thousands of projections can lead to significant bottlenecks. Recent developments in medical imaging driven by both increasing computational power and the desire to reduce patient X-ray exposure have led to the development of a number of limited view CT methodologies. Thus far these limited view algorithms have been applied to basic synthetic data derived from simple medical phantoms. Here, we use experimental data to rigorously test the capability of limited view algorithms to accurately reconstruct and precisely measure the dimensional features of an additive manufactured sample and a turbine blade. Our findings highlight the importance of prior information in producing accurate reconstructions capable of significantly reducing X-ray projections by at least an order of magnitude. In the turbine blade example a dramatic reduction in projections from 5000 to 24 was observed while still demonstrating the same level of accuracy as standard CT methods. The findings of the study also suggest the importance of sample complexity and the presence of sparsity in the X-ray projections in order to maximise the capabilities of these limited algorithms. With the ever increasing computational power, limited view CT algorithms offer a method for reducing data acquisition time and alleviating manufacturing throughput bottlenecks without compromising image accuracy and quality.

Highlights

IntroductionFor example, feature complex cooling channels and highly optimised curved surfaces, and the rise of additive manufacturing has given huge potential for extremely complex shapes
Modern engineering is increasingly utilising complex components
We have shown that inversion based methods are capable of producing accurate image reconstructions and dimensional measurements with more than an order of magnitude reduction in the number of X-ray projections compared to filtered back-projection methods

Summary

Introduction

For example, feature complex cooling channels and highly optimised curved surfaces, and the rise of additive manufacturing has given huge potential for extremely complex shapes. Such shapes present significant inspection challenges to traditional NDE techniques, as these features can obscure defects or manufacturing errors. One of the major downsides of X-ray CT is the time consuming data acquisition process which can lead to significant bottlenecks To alleviate these bottlenecks in throughput, companies may be forced to purchase additional X-ray CT capability at great cost or reduce individual X-ray exposure times lowering the signal-to-noise rato and image quality. Much theoretical work has been conducted over the past decade on limited view tomography the algorithms developed have been tested on simple synthetic examples (e.g., Shepp - Logan phantom [2]) typically with parallel ray geometry, which poorly mimics true industrial applications where ray path geometries and noise are an issue

Methods

Findings

Discussion

Conclusion