Locally Optimal Subsampling Strategies for Full Matrix Capture Measurements in Pipe Inspection

Abstract

In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use of array transducers unfeasible for many applications. In the literature, methods for reducing the number of required channels compared to the full matrix capture scheme have been proposed. Conventionally, these are based on choosing the aperture that is as wide as possible. In this publication, we investigate a scenario from the field of pipe inspection, where cracks have to be detected in specific areas near the weld. Consequently, the width of the aperture has to be chosen according to the region of interest at hand. On the basis of ray-tracing simulations which incorporate a model of the transducer directivity and beam spread at the interface, we derive application specific measures of the energy distribution over the array configuration for given regions of interest. These are used to determine feasible subsampling schemes. For the given scenario, the validity/quality of the derived subsampling schemes are compared on the basis of reconstructions using the conventional total focusing method as well as sparsity driven-reconstructions using the Fast Iterative Shrinkage-Thresholding Algorithm. The results can be used to effectively improve the measurement time for the given application without notable loss in defect detectability.

Online evolution of a phased array for ultrasonic imaging by a novel adaptive data acquisition method

“…By considering the directivity and sensitivity patterns, more elements are placed in regions of high sensitivity, while keeping the number of elements low where sensitivity is lower. This may sound counter-intuitive at first, however the SMC approach followed in this paper follows the adaptive sensing concept where information -and consequently signal-to-noise ration (SNR)-is maximised to the (already identified) area of interest [21]. An alternative SMC approach can be an array element distribution for maximum angular information for the region imaged.…”