The analysis of ultrasonic NDE data has traditionally been addressed by a trained operator
manually interpreting data with the support of rudimentary automation tools. Recently, many …

Supervised machine learning techniques are increasingly being combined with ultrasonic
sensor measurements owing to their strong performance. These techniques also offer …

Nondestructive evaluation (NDE) is a set of techniques used for material inspection and
defect detection without causing damage to the inspected component. One of the commonly …

Composite materials are increasingly used as structural components in military and civilian
aircraft. To ensure their high reliability, numerous non-destructive testing (NDT) techniques …

Ultrasonic testing (UT) is commonly used to inspect the geometric shape of internal damage
in composite materials and the test results need to be interpreted by trained experts. In this …

The industrial application of deep neural networks to automate the ultrasonic weldment flaw
classification system has some limitations. The major problem that affects the classification …

Flaw detection in non-destructive testing, especially for complex signals like ultrasonic data,
has thus far relied heavily on the expertise and judgement of trained human inspectors …

Nondestructive testing and evaluation (NDT&E) are commonly used in the industry for their
ability to identify damage and assess material conditions. Ultrasonic testing (UT) is one of …

Recently, with the desperate demand for data-driven deep learning methods in practical
industrial applications, increasing popularity of deep learning methods for machine fault …

This paper proposes an automatic defect localization and sizing procedure for Structural
Health Monitoring based on guided waves imaging. The procedure is applied to an …