In this article, we propose a data-driven multi-flaw detection strategy based on deep learning
and the boundary element method (BEM). In the training phase, BEM is implemented to …

The identification of internal structural flaws is an important research topic in structural health
monitoring. At present, structural safety inspections based on nondestructive testing …

The surface defect detection (SDD) problem is one of the crucial techniques during
production process, so it has become a key research area to control the quality of industrial …

Abstract Combining Scaled Boundary Finite Element Method (SBFEM) and machine
learning algorithm, the flaw information in the structure is quantitatively reversed based on …

We present a novel multiscale algorithm for nondestructive detection of multiple flaws in
structures, within an inverse problem type setting. The key idea is to apply a two‐step …

Aiming at the problem of low accuracy of unsupervised learning anomaly detection
algorithm, a dual-input anomaly detection method based on deep reinforcement learning …

Anomaly detection for non-linear dynamical system plays an important role in ensuring the
system stability. However, it is usually complex and has to be solved by large-scale …

Structural defect identification is a vital aspect of structural health monitoring used to assess
the safety of engineering structures. However, quantitatively determining the dimensions of …

Bayesian inference is a powerful technique for damage/flaw detection in critical structures.
This paper explores the application of Bayesian inference to identify the flaws …

Deep learning has achieved much success in mechanical intelligent fault diagnosis in
recent years. However, many deep learning methods cannot fully extract fault information to …