Recent advances in sensor technologies and data acquisition systems opened up the era of
big data in the field of structural health monitoring (SHM). Data-driven methods based on …

Among many structural assessment methods, the change of modal characteristics is
considered a well‐accepted damage detection method. However, the presence of …

Application of massive data to structural health monitoring (SHM) may lead to serious
problems such as difficulty, computational inefficiency, and low damage detectability. This …

This article uses the formulation of the structural identification using expectation
maximization (STRIDE) algorithm for compatibility with the truncated physical model (TPM) …

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 …

Historically, structural health monitoring (SHM) has relied on fixed sensors, which remain at
specific locations in a structural system throughout data collection. This paper introduces …

Big data (BD) in structural health monitoring for civil engineers has become possible
because of recent advances in sensor networks, computing, information, and data …

This paper introduces a set of sensitivity metrics to be used along likelihood-based modal
identification methods. In maximum likelihood (ML) estimation theory, the precision of ML …

The technology of hardware-in-the-loop simulations (HILS) plays an important role in the
design of complex systems, for example, the structural health monitoring (SHM) of aircrafts …

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 …