Performance Assessment for a Guided Wave-Based SHM System Applied to a Stiffened Composite Structure.

To assess the ability of structural health monitoring (SHM) systems, a variety of prerequisites and contributing factors have to be taken into account. Within this publication, this variety is analyzed for actively introduced guided wave-based SHM systems. For these systems, it is not possible to analyze their performance without taking into account their structure and their applied system parameters.

Dataset on full ultrasonic guided wavefield measurements of a CFRP plate with fully bonded and partially debonded omega stringer.

The fourth dataset dedicated to the Open Guided Waves platform [1] presented in this work aims at a carbon fiber composite plate with an additional omega stringer at constant temperature conditions. The dataset provides full ultrasonic guided wavefields. Two types of signals were used for guided wave excitation, namely chirp signal and tone-burst signal.

Double-Stage DMAS With Fresnel Zone Filtering in Guided Waves Damage Imaging.

Digital beamforming methods in plate-like structures are widely exploited for Lamb waves-based damage imaging. Among them, the delay and sum (DAS) imaging technique is the most popular thanks to its low-computational cost and ease of implementation. However, the imaging outputs are low quality due to the high levels of side lobes and limited off-axis signal rejection, which leads to limited image resolution and contrast.

Towards Interpretable Machine Learning for Automated Damage Detection Based on Ultrasonic Guided Waves.

Data-driven analysis for damage assessment has a large potential in structural health monitoring (SHM) systems, where sensors are permanently attached to the structure, enabling continuous and frequent measurements. In this contribution, we propose a machine learning (ML) approach for automated damage detection, based on an ML toolbox for industrial condition monitoring. The toolbox combines multiple complementary algorithms for feature extraction and selection and automatically chooses the best combination of methods for the dataset at hand.

Feasibility of Model-Assisted Probability of Detection Principles for Structural Health Monitoring Systems Based on Guided Waves for Fiber-Reinforced Composites.

In many industrial sectors, structural health monitoring (SHM) is considered as an addition to nondestructive testing (NDT) that can reduce maintenance effort during the lifetime of a technical facility, structural component, or vehicle. A large number of SHM methods are based on ultrasonic waves, whose properties change depending on structural health. However, the wide application of SHM systems is limited due to the lack of suitable methods to assess their reliability.