This paper addresses two problems in structural damage identification: locating damage and assessing damage severity, which are incorporated into the classification framework based on the theory of sparse representation (SR) and compressed sensing (CS). The sparsity nature implied in the classification problem itself is exploited, establishing a sparse representation framework for damage identi...

Abstract The paper presents the results on application of Lamb waves based technique for impact damage detection and severity identification. PZT network operates in round-robin mode changing actuator sensor roles transducers order to detect response system presence damage. monitoring is performed via analysis three parameters: change amplitude (dA), energy (dP) cross-correlation (NCC) signals ...

The subject of structural health monitoring and damage identification of structures at the earliest possible stage has been a noteworthy topic for researchers in the last years. Modal strain energy (MSE) based index is one of the efficient methods which are commonly used for detecting damage in structures. It is also more effective and economical to employ some methods for reducing the degrees ...

Inverse analysis of nonlinear dynamic systems is an important area of research in the field of structural health monitoring for civil engineering structures. Structural damage usually involves localized nonlinear behaviors of dynamic systems that evolve into different classes of nonlinearity as well as change system parameter values. Numerous parametric modal analysis techniques (e.g., eigensys...

Inverse analysis of nonlinear dynamic systems is an important area of research in the field of structural health monitoring for civil engineering structures. Structural damage usually involves localized nonlinear behaviors of dynamic systems that evolve into different classes of nonlinearity as well as change system parameter values. Numerous parametric modal analysis techniques (e.g., eigensys...

Wireless smart sensor networks (WSSN) facilitate a new paradigm for structural health monitoring (SHM) of civil infrastructure. Conventionally, SHM systems employing wired sensors and centralized data acquisition have been used to characterize the state of a structure; however, widespread implementation has been limited due to high costs and difficulties in installation. WSSN offer a unique opp...

In this paper, a novel approach proposed for structural damage detection from limited number of sensors using extreme learning machine (ELM). As the number of sensors used to measure modal data is normally limited and usually are less than the number of DOFs in the finite element model, the model reduction approach should be used to match with incomplete measured mode shapes. The second-order a...