Detalhes do Documento

New signal processing approach for structural health monitoring in noisy environments based on impedance measurements

Autor(es): de Castro, Bruno Albuquerque [UNESP] ; Baptista, Fabricio Guimarães [UNESP] ; Ciampa, Francesco

Data: 2019

Identificador Persistente: http://hdl.handle.net/11449/188686

Origem: Oasisbr

Assunto(s): Cross-correlation; Damage index; Feature extraction; Impedance measurements; SHM; Signal processing; Wavelet transform; Cross-correlation; Cross-correlation; Damage index; Damage index; Feature extraction; Feature extraction; Impedance measurements; Impedance measurements; SHM; SHM; Signal processing; Signal processing; Wavelet transform; Wavelet transform


Descrição

Made available in DSpace on 2019-10-06T16:15:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-04-01

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The electro-mechanical impedance (EMI) technique is one of the most promising structural health monitoring (SHM) approaches for material damage detection, which is based on impedance measurements of low-cost piezoelectric transducers. However, numerous practical issues such as signal noise effects caused by environmental conditions can alter signal measurements and limit the capabilities of the EMI technique when the characterization of damage is performed using conventional basic indices. Therefore, this paper proposes a new index for structure feature extraction based on the cross-correlation signal processing technique that can be applied in real noisy environment. The proposed index was evaluated in the frequency domain, where the damage detection is performed directly on the electrical impedance measurements of the transducer, as well as on the time domain, which is based on the wavelet transform applied to the transducer response signal. Experimental tests were carried out on a damaged aluminium structure subject to various signal noise levels. Experimental results revealed that the proposed approach for material feature extraction under noisy environments proved to be effective for detecting damage, thus enhancing the reliability and expanding the applicability of the EMI technique.

São Paulo State University (UNESP) School of Engineering Bauru Department of Electrical Engineering

University of Surrey Department of Mechanical Engineering Sciences

São Paulo State University (UNESP) School of Engineering Bauru Department of Electrical Engineering

FAPESP: #2015/02500-6

FAPESP: #2015/24903-5

Tipo de Documento Artigo científico
Idioma Inglês
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