To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

Railway importance in the transportation industry is increasing continuously, due to the
growing demand of both passenger travel and transportation of goods. However, more than …

Damage detection in bridge structures has always been challenging, particularly for long‐
span bridges with complex structural forms. In this study, a partial‐model‐based damage …

Civil structures are usually prone to damage during their service life and it leads them to loss
their serviceability and safety. Thus, damage assessment can guarantee the integrity of …

This study investigates the application of novel computational techniques for structural
performance monitoring of bridges that enable quantification of temperature-induced …

One quarter of bridges in Canada and the United States need repair. The present study
provides a critical overview of the state-of-the-art existing condition assessment techniques …

Structural Health Monitoring (SHM) is a relatively new branch of civil engineering that
focuses on assessing the health status of infrastructure, such as long-span bridges. Using a …

A series of optimal sensor placement (OSP) techniques is discussed in this paper. A
framework for deciding the optimum number and location of sensors is proposed, to …

There has recently been considerable research published on the applicability of monitoring
systems for improving civil infrastructure management decisions. Less research has been …

Structural damage in a bridge is defined as a significant deviation in the structural response
from its standard operating conditions, not explainable by variations in external …