Combining simulated and experimental data to simulate ultrasonic array data from defects in materials with high structural noise

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)
345 Downloads (Pure)

Abstract

Ultrasonic non-destructive testing inspections using phased arrays are performed on a wide range of components and materials. All real inspections suffer, to varying extents, from coherent noise including image artefacts and speckle caused by complex geometries and grain scatter respectively. By its nature, this noise is not reduced by averaging; however, it degrades the signal to noise ratio of defects and ultimately limits their detectability. When evaluating the effectiveness of an inspection, a large pool of data from samples containing a range of different defects is important to estimate the probability of detection of defects and to help characterise them. For a given inspection, coherent noise is easy to measure experimentally but hard to model realistically. Conversely, the ultrasonic response of defects can be simulated relatively easily. This paper proposes a novel method of simulating realistic array data by combining noise-free simulations of defect responses with coherent noise taken from experimental data. This removes the need for costly physical samples with known defects to be made and allows for large data sets to be created easily.

Original languageEnglish
Article number7579558
Pages (from-to)2198-2206
Number of pages9
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume63
Issue number12
Early online date29 Sep 2016
DOIs
Publication statusPublished - Dec 2016

Keywords

  • Array signal processing
  • copper
  • image fusion
  • modelling
  • noise measurement
  • phased arrays
  • ultrasonic imaging
  • ultrasonic transducer arrays

Fingerprint

Dive into the research topics of 'Combining simulated and experimental data to simulate ultrasonic array data from defects in materials with high structural noise'. Together they form a unique fingerprint.

Cite this