@article {Long:2012:1354-2575:380,
title = "Ultrasonic phased array inspection using full matrix capture",
journal = "Insight - Non-Destructive Testing and Condition Monitoring",
parent_itemid = "infobike://bindt/insight",
publishercode ="bindt",
year = "2012",
volume = "54",
number = "7",
publication date ="2012-07-01T00:00:00",
pages = "380-385",
itemtype = "ARTICLE",
issn = "1354-2575",
url = "https://www.ingentaconnect.com/content/bindt/insight/2012/00000054/00000007/art00006",
doi = "doi:10.1784/insi.2012.54.7.380",
author = "Long, R and Russell, J and Cawley, P",
abstract = "Work is being conducted to develop ultrasonic phased array inspection of stainless steel welded pipes with a completely undressed weld cap. The benefit of phased array inspection over single-crystal inspections is the ability to fire the array elements in a particular sequence (often
termed a delay law) to steer and focus the beam, which allows multiple inspections to be conducted with a single transducer. Using a collection of different delay laws, conventional phased array controller software can generate a number of different types of image, such as plane and focused
B-scan images as well as sector-scan images. When conducting an inspection we have chosen to collect the full matrix capture (FMC) of data, which involves the collection of the transmit-receive time domain signals from all element combinations, and post-process the data to form an image. The
advantage of FMC is that it allows multiple inspections to be obtained from a single dataset, removes the dependence on phased array controller software for the processing of data and display of results, and allows more advanced processing algorithms that could not be applied to conventional
data capture. This can improve the detection and characterisation of defects and hence improve safety; it also future-proofs inspection data, which can be archived and processed at a later date. This paper explains the FMC principle and describes the signal processing algorithms. The inspections
were modelled using the CEA CIVA software and compared to experimental results.",
}