Vibration-based structural health monitoring (SHM) is an active research area in civil and mechanical engineering communities. This research area may include damage diagnosis including early damage detection, damage localization, and damage quantification in civil structures, fault detection in mechanical systems, and finite element model updating. In general, model-based and data-based methods are two approaches to the above-mentioned procedures. Model-based techniques usually lie in establishing an elaborate finite element model of a structural system and dynamic information for solving linear and nonlinear equations. Data-based methods utilize statistical pattern recognition paradigm as well as raw vibration data. In recent years, numerous research studies focused on data-based methods due to simplicity and efficiency but model-based techniques still have their advantages. This special issue is intended to pay more attention on advanced model-based, data-based, and hybrid methods for vibration-based SHM applications. The main focus of this special issue is on novel and practical approaches based on vibration data, sensitivity-based or non-sensitivity-based methods, effective and innovative solution techniques of linear and nonlinear inverse and forward problem, new methods of statistical pattern recognition paradigm and machine learning algorithms for data-based approaches, new dynamic features, and applications of advanced model-based and data-based methods to numerical, experimental, and full-scale civil and mechanical systems.

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