This paper aims to review high-dimensional data analytic (HDDA) methods for structural
health monitoring (SHM) and non-destructive evaluation (NDE) applications. High …

Damage diagnosis has been a challenging inverse problem in structural health monitoring.
The main difficulty is characterizing the unknown relation between the measurements and …

Advancement in sensing devices such as wireless sensors and high-rate data acquisition
systems have recently enhanced inherent ability of structural health monitoring (SHM) where …

In SHM, fixed sensor networks with long-term monitoring capabilities, dense sensor arrays,
or high sampling rates are perceived to produce BIGDATA. As the temporal and spatial …

Large quantities of data which contain detailed condition information over an extended
period of time should be utilized to prioritize infrastructure repairs. As the temporal and …

Structural health monitoring (SHM) techniques have been studied over the past few decades
to detect the deficiencies affecting the performance of the structures. Detecting and …

Structures experience large vibrations and stress variations during their life cycles. This
causes reduction in their load-carrying capacity which is the main design criteria for many …

This dissertation focuses on the applications of high-dimensional data analytics in the
context of structural health monitoring and non-destructive evaluation. In high-dimensional …

Damage diagnosis of structures subjected to time-varying environmental and operational
conditions has been a challenging task. This task involves a damage indicator selection to …