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

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. (C) 2019 Elsevier Ltd. All rights reserved.