A Novel Damage Indicator Based on the Electromechanical Impedance Principle for Structural Damage Identification

• Published in: Sensors (Basel, Switzerland) Vol. 18; no. 7; p. 2199
• Main Authors: Zhou, Pin, Wang, Dansheng, Zhu, Hongping
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08-07-2018; MDPI
• Subjects: Algorithms; beam structure; Damage detection; differential evolution algorithm (DEA); Electric potential; Electromagnetic interference; electromechanical impedance (EMI); Evolutionary algorithms; fourth-order voltage statistical moment (FVSM); Identification; Impedance; lead zirconate titanate (PZT); Metal fatigue; Noise; Sensors; Spectral element method; structural damage identification; Wavelet transforms; structural damage identification; beam structure; fourth-order voltage statistical moment (FVSM); differential evolution algorithm (DEA); electromechanical impedance (EMI); lead zirconate titanate (PZT)
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s18072199

This paper presents a novel structural damage detection indicator, i.e., fourth-order voltage statistical moment (FVSM) based on the electromechanical impedance (EMI) principle, and then proposes a two-step damage detection method based on the novel indicator and a differential evolution algorithm (DEA). In this study, several lead zirconate titanate (PZT) sensors bonded to an experimental steel beam were utilized to acquire the time-domain voltage responses. On this basis, the fourth-order voltage statistical moments (FVSMs) of the voltage responses are computed to locate the damage element in the detected structure, and the proposed damage detection method is utilized to quantify the damage. In addition, theoretical PZT voltage responses are also calculated based on the piezoelectric theory and the spectral element method (SEM). Experimental results verify the accuracy of the theoretical voltage values and the effectiveness of the proposed damage indicator. Results indicate that the FVSM is effective in locating the damage element. Integrated with DEA, the proposed technique is capable of quantifying damage.